Journal of Intelligent & Fuzzy Systems - Volume 41, issue 1

Authors: Ali, Riaz | Abdullah, Saleem | Muhammad, Shakoor | Naeem, Muhammad | Chinram, Ronnason

Article Type: Research Article

Abstract: Due to the indeterminacy and uncertainty of the decision-makers (DM) in the complex decision making problems of daily life, evaluation and aggregation of the information usually becomes a complicated task. In literature many theories and fuzzy sets (FS) are presented for the evaluation of these decision tasks, but most of these theories and fuzzy sets have failed to explain the uncertainty and vagueness in the decision making issues. Therefore, we use complex intuitionistic fuzzy set (CIFS) instead of fuzzy set and intuitionistic fuzzy set (IFS). A new type of aggregation operation is also developed by the use of complex intuitionistic …fuzzy numbers (CIFNs), their accuracy and the score functions are also discussed in detail. Moreover, we utilized the Maclaurin symmetric mean (MSM) operator, which have the ability to capture the relationship among multi-input arguments, as a result, CIF Maclarurin symmetric mean (CIFMSM) operator and CIF dual Maclaurin symmetric mean (CIFDMSM) operator are presented and their characteristics are discussed in detail. On the basis of these operators, a MAGDM method is presented for the solution of group decision making problems. Finally, the validation of the propounded approach is proved by evaluating a numerical example, and by the comparison with the previously researched results. Show more

Keywords: Intuitionistic fuzzy set, complex intuitionistic fuzzy set, multi-attribute group decision making, emergency management program evaluation, Maclaurin symmetric mean operator

DOI: 10.3233/JIFS-202254

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 517-538, 2021

Authors: Deng, Xue | Huang, Cuirong

Article Type: Research Article

Abstract: In the previous uncertain portfolio literature on background risk and mental account, only a general background risk and a few kinds of mental accounts were considered. Based on the above limitations, on the one hand, the multiple background risks are defined by linear weighting of different background asset risks in this paper; on the other hand, the total nine kinds of mental accounts are comprehensively considered. Especially, the risk curve is regarded as the risk measurement of different mental accounts for the first time. Under the framework of uncertainty theory, a novel mean-entropy portfolio model with risk curve and total …mental accounts under multiple background risks is constructed. In addition, transaction fees, chance constraint, upper and lower limits and initial wealth constraints are also considered in our proposed model. In theory, the equivalent forms of the models with different uncertainty distributions (general, normal and zigzag) are presented by three theorems. Simultaneously, the corresponding concrete expressions of risk curves are obtained by another three theorems. In practice, two numerical examples verify the feasibility and effectiveness of our proposed model. Finally, we can obtain the following unique and meaningful findings: (1) investors will underestimate the potential risk if they ignore the existence of multiple background risks; (2) with the increase of the return threshold, the return of the sub-portfolio will inevitably increase, but investors also bear the risk that the risk curve is higher than the confidence curve at this time. Show more

Keywords: Uncertainty theory, mental account, background risk, entropy, risk curve

DOI: 10.3233/JIFS-202256

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 539-561, 2021

Authors: Fu, Yingwen | Lin, Nankai | Lin, Xiaotian | Jiang, Shengyi

Article Type: Research Article

Abstract: Named entity recognition (NER) is fundamental to natural language processing (NLP). Most state-of-the-art researches on NER are based on pre-trained language models (PLMs) or classic neural models. However, these researches are mainly oriented to high-resource languages such as English. While for Indonesian, related resources (both in dataset and technology) are not yet well-developed. Besides, affix is an important word composition for Indonesian language, indicating the essentiality of character and token features for token-wise Indonesian NLP tasks. However, features extracted by currently top-performance models are insufficient. Aiming at Indonesian NER task, in this paper, we build an Indonesian NER dataset (IDNER) …comprising over 50 thousand sentences (over 670 thousand tokens) to alleviate the shortage of labeled resources in Indonesian. Furthermore, we construct a hierarchical structured-attention-based model (HSA) for Indonesian NER to extract sequence features from different perspectives. Specifically, we use an enhanced convolutional structure as well as an enhanced attention structure to extract deeper features from characters and tokens. Experimental results show that HSA establishes competitive performance on IDNER and three benchmark datasets. Show more

Keywords: Indonesian, named entity recognition, named entity corpus, structured-attention, residual gated convolution neural network

DOI: 10.3233/JIFS-202286

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 563-574, 2021

Authors: Zhu, Yan | Fan, Chuanhao | Xiao, Jing | Liu, Shenghua

Article Type: Research Article

Abstract: Quality function deployment (QFD) is a quality management tool that aims to improve customer satisfaction by transforming customer requirements into technical characteristics. It is a crucial procedure to obtain the prioritization of technical characteristics for the products or services in QFD. Traditional QFDs are often implemented by a small number of QFD members. However, with the increasing complexity of product and service design, QFD requires the participation of more QFD members from dispersed departments or institutions. Additionally, the evaluation information given by QFD members may widely differ due to their different knowledge and background. Furthermore, the psychological behaviours of QFD …members also greatly influence the final prioritization of technical characteristics. Hence, this paper proposes a novel QFD framework to prioritize technical characteristics using a consensus-reaching process and prospect theory when large numbers of QFD members are involved. In the large-scale QFD framework, prospect theory is generally utilized to depict the psychological behaviours of QFD members. Then, QFD members are divided into several clusters. Eventually, a consensus-reaching process is established to assist QFD members in reaching a consensus. To verify the practicability of the presented framework, this paper applies it to the evaluation of contingency plan to determine the critical measures. Show more

Keywords: Quality function deployment, consensus-reaching process, prospect theory, large-scale group decision making, contingency plan

DOI: 10.3233/JIFS-202326

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 575-594, 2021

Authors: Jiang, Le | Liu, Hongbin

Article Type: Research Article

Abstract: The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step …being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility. Show more

Keywords: Green supplier selection, interval type-2 fuzzy set, lower membership function, probabilistic linguistic term set, upper membership function

DOI: 10.3233/JIFS-202386

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 595-612, 2021

Authors: Dong, Yan Yan | Wang, Jun Tao

Article Type: Research Article

Abstract: In this paper, we first point out some mistakes in [12 ]. Especially the Theorem 3.9 [12 ] showed that: Let A be residuated lattice and ∅ ≠ X  ⊆ A , then the least ideal containing X can be expressed as: 〈X 〉 = {a  ∈ A |a  ≤ (·· · ((x 1  ⊕ x 2 ) ⊕ x 3 ) ⊕ ·· ·) ⊕ x n , x i  ∈ X , i  = 1, 2 ·· · , n }. But we present an example to illustrate the ideal generation formula may not hold on residuated lattices. Further we give the correct ideal generation formula on residuated lattices. Moreover, we extend the concepts of annihilators …and α -ideals to MTL-algebras and focus on studying the relations between them. Furthermore, we show that the set I α  (M ) of all α -ideals on a linear MTL-algebra M only contains two trivial α -ideals {0} and M . However, the authors [24 ] studied the structure of I α  (M ) in a linear BL-algebra M , which means some results with respect to I α  (M ) given in [24 ] are trivial. Unlike that, we investigate the lattice structure of I α  (M ) on general MTL -algebras. Show more

Keywords: Residuated lattice, MTL-algebra, Ideal generation formula, Annihilator, α-ideal

DOI: 10.3233/JIFS-202417

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 613-623, 2021

Authors: Silmi Juman, Zeinul Abdeen M. | Masoud, Mahmoud | Elhenawy, Mohammed | Bhuiyan, Hanif | Komol, Md Mostafizur Rahman | Battaïa, Olga

Article Type: Research Article

Abstract: The uncapacitated transportation problem (UTP) deals with minimizing the transportation costs related to the delivery of a homogeneous product from multi-suppliers to multi-consumers. The application of the UTP can be extended to other areas of operations research, including inventory control, personnel assignment, signature matching, product distribution with uncertainty, multi-period production and inventory planning, employment scheduling, and cash management. Such a UTP with interval-defined demands and suppliers capacities (UTPIDS) is investigated in this paper. In UTPIDS, the demands and suppliers capacities may not be known exactly but vary within an interval due to variation in the economic conditions of the global …economy. Following the variation, the minimal total cost of the transportation can also be varied within an interval and thus, the cost bounds can be obtained. Here, although the lower bound solution can be attained methodologically, the correct estimation of the worst case realization (the exact upper bound) on the minimal total transportation cost of the UTPIDS is an NP-hard problem. So, the decision-makers seek for minimizing the transportation costs and they are interested in the estimation of the worst case realization on these minimal costs for better decision making especially, for proper investment and return. In literature very few approaches are available to find this estimation of the worst case realization with some shortcomings. First, we demonstrate that the available heuristic methods fail to obtain the correct estimation of the worst case realization always. In this situation, development of a better heuristic method to find the better near optimal estimation of the worst case realization on the minimal total costs of the UTPIDS is desirable. Then this paper provides a new polynomial time algorithm that runs in O (N2) time (N, higher of the numbers of source and destination nodes) for better estimation. A comparative assessment on solutions of available benchmark instances, some randomly generated numerical example problems and a real-world application shows promising performance of the current technique. So, our new finding would definitely be benefited to practitioners, academics and decision makers who deal with such type of decision making instances. Show more

Keywords: Heuristics, upper bound, least aggregated expense, NP-hard problem

DOI: 10.3233/JIFS-202436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 625-637, 2021

Authors: Pak, Sunae | Choe, Huichol | Sin, Kinam | Kwon, Sunghyok

Article Type: Research Article

Abstract: In this paper, we investigate the necessary and sufficient conditions for existence of solutions for initial value problem of fuzzy Bagley-Torvik equation and the solution representation by using the multivariate Mittag-Leffler function. First we convert fuzzy initial value problem into the cut problem (system of fractional differential equations with inequality constraints) and obtain existence results for the solution of the cut problem under (1,1)- differentiability. Next we study the conditions for the solutions of the cut problem to constitute the solution of a fuzzy initial value problem and suggest a necessary and sufficient condition for the (1,1)-solution. Also, some examples …are given to verify the effectiveness of our proposed method. The necessary and sufficient condition, solution representation for (1,2)-solution of initial value problem of fuzzy fractional Bagley-Torvik equation are shown in Appendix. Show more

Keywords: Fuzzy Fuzzy Bagley-Torvik equation, generalized Hukuhara differentiability, multivariate Mittag-Leffler function

DOI: 10.3233/JIFS-202453

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 639-654, 2021

Authors: AlAlaween, Wafa’ H. | AlAlawin, Abdallah H. | Al-Durgham, Lamees | Albashabsheh, Nibal T.

Article Type: Research Article

Abstract: A new integrated modelling architecture based on the concept of the fuzzy logic is presented to represent the turning process. Such an architecture consists of two stages. In the first stage, fuzzy logic systems (FLSs) having various topologies are employed to extract rule bases using perhaps limited amount of sparse data. In the second stage, the fuzzy rules extracted are assessed and integrated using the singular value decomposition-QR factorization (SVD-QR) paradigm in order to minimize the computational efforts. Such a step leads to reducing the number of fuzzy rules and results in a reduced FLS model. Such a reduced model …is then employed to represent the turning process and predict both the cutting force and the surface roughness. In addition, it provides a comprehensive understanding of the turning process presented linguistically in the form of If/Then rules. The proposed structure has been validated using a set of laboratory experiments. It has been noticed that it can predict both the cutting force and the surface roughness successfully. In addition, such an integrated architecture outperforms the artificial neural network, the well-known FLS, the radial basis functions and the multilinear regression model, where the overall improvement is of approximately 19%, 13%, 14% and 270%, respectively. Show more

Keywords: Fuzzy logic system, singular value decomposition-QR factorization (SVD-QR) algorithm, turning process

DOI: 10.3233/JIFS-202457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 655-667, 2021

Authors: Hikal, Noha A. | Shams, Mahmoud Y. | Salem, Hanaa | Eid, Marwa M.

Article Type: Research Article

Abstract: Mobile Ad hock Networks (MANETs) are currently used for developing the privacy and accuracy of modern networks. Furthermore, MANET applications are fit to be data-oriented systems, that introduce a secure and more robust data transmission protocol making it a topmost priority in the design. The lack of infrastructure in the existence of dynamic topology as well as limited resources of MANET is a major challenge facing those interested in the field. Further, the nonexistence of a formerly authorized trust relationship within the connected nodes produces instability of the detection process in MANETs. Basically, by adding adapted LEACH routing protocol to …MANET, enhancement of the preserved nodes vitality will be achieved, moreover, the load balancing with data loss reduction provides MANET ability to tracks along with shortest and limited paths. This paper proposes a newly developed detection scheme for both active and passive black-hole attacks in MANETs. Moreover, the scheme deals with assessing a group of selected features for each node-based AdaBoost-SVM algorithm. These features are collected from cluster members nodes based on Ad hoc On-demand Multipath Distance Vector (OMDV) with LEACH routing protocol clustering approaches. Although SVM is considered a more stable classifier, there are great influences of the AdaBoost weight adaption algorithm to enhance the classification process in terms of strengthening the weights of extracted features. This hybrid algorithm is essential for active black-hole attacks as well as for identifying passive black-hole attacks in MANET. The proposed scheme is tested against the effect of mobility variation to determine the accuracy of the detection process including the routing overhead protocol. The experimental results investigated that the accuracy of detecting both active and passive black-holes attacks in MANET reached 97% with a promising time complexity for different mobility conditions. Moreover, the proposed scheme provides an accurate decision about malicious vs benign node dropping behavior using an adjustable threshold value. Show more

Keywords: Ada-boost, support vector machine, AOMDV, black-hole attack, and MANET

DOI: 10.3233/JIFS-202471

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 669-682, 2021

Authors: Dhamija, Ashutosh | Dubey, R. B.

Article Type: Research Article

Abstract: Face recognition is one of the most challenging and demanding field, since aging affects the shape and structure of the face. Age invariant face recognition is a relatively new area in face recognition studies, which in real-world implementations recently gained considerable interest due to its huge potential and relevance. The Age invariant face recognition, however, is still evolving and evolving, providing substantial potential for further study and progress in accuracy. Major issues with the age invariant face recognition involve major variations in appearance, texture, and facial features and discrepancies in position and illumination. These problems restrict the age invariant face …recognition systems developed and intensify identity recognition tasks. To address this problem, a new technique Quadratic Support Vector Machine- Principal Component Analysis (QSVM-PCA) is introduced. Experimental results suggest that our QSVM-PCA achieved better results especially when the age range is larger than other existing techniques of face-aging dataset of FGNET. The maximum accuracy achieved by demonstrated methodology is 98.87%. Show more

Keywords: Age-invariant face recognition, feature extraction, PCA and QSVM

DOI: 10.3233/JIFS-202485

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 683-697, 2021

Authors: Yang, Yulei | Zhang, Jin | Sun, Wenjie | Pu, Yun

Article Type: Research Article

Abstract: Under the background of the new medical reform, the pharmaceutical industry is in constant transformation and upgrading, and the establishment of a rational and efficient pharmaceutical logistics system is imminent. Carbon emission, cost and time are set as the target to construct the model of location-routing-inventory optimization of highway, rail and air transport hubs with capacity limits. Then the warehouse of pharmaceutical logistics hub is selected, and the distribution path of pharmaceutical logistics and the inventory strategy are planned to realize the scientific decision of the system. The NSGA-III algorithm is used to solve the problem. The diversity of the …population is maintained by the well-distributed reference points, and the optimal solution set of nondominant Pareto is obtained. Spacing, HRS, PR and GD are used to measure the performance of the algorithm. The example analysis shows that the number of Pareto optimal solutions solved by the algorithm is large and evenly distributed, and convergence and operation efficiency of algorithm is good. The sensitivity analysis of three kinds of freight rates shows that the influence of the freight rates on the objective function value should be fully considered when making decisions. The method focuses on the problem of optimizing the layout of multi-modal transport hubs and improves the existing theories of it. Show more

Keywords: Pharmaceutical warehouse, carbon emission, location-routing-inventory problem, NSGA-III

DOI: 10.3233/JIFS-202508

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 699-713, 2021

Authors: Mousa, A.A. | Higazy, M. | Abdel-Khalek, S. | Hussein, Mohamed A. | Farouk, Ahmed

Article Type: Research Article

Abstract: The application and analysis of effective blood supply chain network under natural disaster imposed many critical challenges which addressed through an optimization of multiple objectives functions. In this article, relies on reference point algorithm, a user-preference based enriched swarm optimization algorithm is proposed where, inner reference points were produced depending on the perturbed reference point. For each inner reference point, weakly/ɛ -properly Pareto optimal solution was generated using augmented achievement function. All the generated solutions (points) are presented as potential positions for particles in the particle swarm optimization PSO. The proposed algorithm has been reinforced with a novel chaotic contraction …operator to retain the feasibility of the particles. To prove the validity of our algorithm, the obtained results are compared with true Pareto optimal front and three of the most salient evolutionary algorithms using inverted generational distance metric IGD. In addition it was implement to detect the most cost and time efficient blood supply chain to provide the required blood types demand on the blood transfusion center in emergence situation, where, it is required to solve this real life application with predefined supply time and predefined supply cost, which is considered as reference point to get the nearby Pareto optimal solution. By the experimental outcomes, we proved that the proposed algorithm is capable to find the set of Paetro optimal solutions nearby the predefined reference points. Show more

Keywords: Particle swam optimization, reference point, multi-objective optimization, blood supply chain

DOI: 10.3233/JIFS-202529

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 715-733, 2021

Authors: Ranjith Pillai, R. | Murali, Ganesan

Article Type: Research Article

Abstract: Miniature flexible parallel robots, popularly used for micro positioning application demands the use of non conventional actuators. Shape memory alloys (SMA) are popular smart actuators because of its light weight, integration compatibility, ease of actuation and high power density. Inclusion of shape memory alloy actuators to the parallel robot brings in control challenges due to its nonlinearity, coupling effects and cocontraction of antagonistic pair of actuators in the mechanism in order to achieve bi directional motion. In this paper, a PID like fuzzy controller is designed and applied to a nonlinear SMA spring actuator connected to a symmetric 2 DOF …miniature parallel robot. The fuzzy rules are designed from the general response plot and modified to be applied to a parallel mechanism which involves cocontraction of antagonistic actuators. The paper has also presented the control and electrical circuit design used in the experimental set up. The fuzzy control is implemented in the hardware controller with model based position feedback and tested for the trajectory tracking characteristics of the end effector with disturbances. Experimental results are presented with quantitative analysis to show the effectiveness of the proposed controller in handling nonlinearities and disturbances compared to the conventional PID control and nonlinear Sliding mode control (NSMC). The test results has demonstrated the superior nature of proposed control over other controllers in the trajectory tracking with disturbances and also linearizing the hysteresis of controlled system. Show more

Keywords: SMA actuated parallel robot, PID like fuzzy control, control of cocontraction of actuators, flexible robot, SMA spring control

DOI: 10.3233/JIFS-202572

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 735-755, 2021

Authors: Adu, Kwabena | Yu, Yongbin | Cai, Jingye | Dela Tattrah, Victor | Adu Ansere, James | Tashi, Nyima

Article Type: Research Article

Abstract: The squash function in capsule networks (CapsNets) dynamic routing is less capable of performing discrimination of non-informative capsules which leads to abnormal activation value distribution of capsules. In this paper, we propose vertical squash (VSquash) to improve the original squash by preventing the activation values of capsules in the primary capsule layer to shrink non-informative capsules, promote discriminative capsules and avoid high information sensitivity. Furthermore, a new neural network, (i) skip-connected convolutional capsule (S-CCCapsule), (ii) Integrated skip-connected convolutional capsules (ISCC) and (iii) Ensemble skip-connected convolutional capsules (ESCC) based on CapsNets are presented where the VSquash is applied in the dynamic …routing. In order to achieve uniform distribution of coupling coefficient of probabilities between capsules, we use the Sigmoid function rather than Softmax function. Experiments on Guangzhou Women and Children’s Medical Center (GWCMC), Radiological Society of North America (RSNA) and Mendeley CXR Pneumonia datasets were performed to validate the effectiveness of our proposed methods. We found that our proposed methods produce better accuracy compared to other methods based on model evaluation metrics such as confusion matrix, sensitivity, specificity and Area under the curve (AUC). Our method for pneumonia detection performs better than practicing radiologists. It minimizes human error and reduces diagnosis time. Show more

Keywords: Artificial intelligence, capsule network, convolutional neural network, deep learning, pneumonia, x-ray imaging

DOI: 10.3233/JIFS-202638

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 757-781, 2021

Authors: Huang, Danyang | Zhou, Zhiheng | Deng, Ming | Li, Zhihao

Article Type: Research Article

Abstract: Detecting vehicle at night is critical to both assistant driving systems and autonomous driving systems. In this paper, we propose a deep network scheme assisted by light information with good generalization to detect vehicle at night. Our approach is divided into two branches, the object stream and the pixel stream. The object stream generates a batch of bounding boxes, and the pixel stream utilizes the vehicle light information to calibrate the bounding boxes of the object stream. In the object stream, we propose a new structure, Direction Attention Pooling (DAP), to improve the accuracy of the prior boxes. DAP leads …into attention mechanism. The feature maps obtained from backbone network is divided into two branches. One branch obtains direction perception information through IRNN layer, and the other branch learns attention weights. The weights are multiplied with the direction perception features in an element-wise manner. In the pixel stream, we propose a corner localization algorithm based on Bayes to get more accurate corners with the vehicle light pixels. The locations of the corners are considered as a discrete random variable. When the mask of the object is known, solving the probability distribution of the corner of the object is the next step. The corners with the highest probability is the correct corner. On the nighttime vehicle detection datasets CHUK and SYSU, our method achieves the accuracy of 97.2% and 96.86%, which outperforms other state-of-the-art methods by at least 0.31% and 0.34%. Show more

Keywords: Nighttime vehicle detection, advanced driver-assistance systems, attention mechanism, deep learning

DOI: 10.3233/JIFS-202676

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 783-801, 2021

Authors: Noorullah, R.M. | Mohammed, Moulana

Article Type: Research Article

Abstract: Topic models are widely used in building clusters of documents for more than a decade, yet problems occurring in choosing the optimal number of topics. The main problem is the lack of a stable metric of the quality of topics obtained during the construction of topic models. The authors analyzed from previous works, most of the models used in determining the number of topics are non-parametric and the quality of topics determined by using perplexity and coherence measures and concluded that they are not applicable in solving this problem. In this paper, we used the parametric method, which is an …extension of the traditional topic model with visual access tendency for visualization of the number of topics (clusters) to complement clustering and to choose the optimal number of topics based on results of cluster validity indices. Developed hybrid topic models are demonstrated with different Twitter datasets on various topics in obtaining the optimal number of topics and in measuring the quality of clusters. The experimental results showed that the Visual Non-negative Matrix Factorization (VNMF) topic model performs well in determining the optimal number of topics with interactive visualization and in performance measure of the quality of clusters with validity indices. Show more

Keywords: Interactive visualization, visual non-negative matrix factorization model, an optimal number of topics, cluster validity indices, twitter data clustering

DOI: 10.3233/JIFS-202707

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 803-817, 2021

Authors: Shabir, Muhammad | Mushtaq, Rimsha | Naz, Munazza

Article Type: Research Article

Abstract: In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of …these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop. Show more

Keywords: N-soft set, algebraic structure, top complement, bottom complement, TOPSIS

DOI: 10.3233/JIFS-202717

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 819-839, 2021

Authors: Cheng, Haodong | Han, Meng | Zhang, Ni | Li, Xiaojuan | Wang, Le

Article Type: Research Article

Abstract: Traditional association rule mining has been widely studied, but this is not applicable to practical applications that must consider factors such as the unit profit of the item and the purchase quantity. High-utility itemset mining (HUIM) aims to find high-utility patterns by considering the number of items purchased and the unit profit. However, most high-utility itemset mining algorithms are designed for static databases. In real-world applications (such as market analysis and business decisions), databases are usually updated by inserting new data dynamically. Some researchers have proposed algorithms for finding high-utility itemsets in dynamically updated databases. Different from the batch processing …algorithms that always process the databases from scratch, the incremental HUIM algorithms update and output high-utility itemsets in an incremental manner, thereby reducing the cost of finding high-utility itemsets. This paper provides the latest research on incremental high-utility itemset mining algorithms, including methods of storing itemsets and utilities based on tree, list, array and hash set storage structures. It also points out several important derivative algorithms and research challenges for incremental high-utility itemset mining. Show more

Keywords: Survey, pattern mining, incremental mining, high-utility patterns, frequent itemsets

DOI: 10.3233/JIFS-202745

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 841-866, 2021

Authors: Yang, Zhan | Li, Chengliang | Zhao, Zhongying | Li, Chao

Article Type: Research Article

Abstract: Aspect-based sentiment classification, a fine-grained sentiment analysis task, aims to predict the sentiment polarity for a specified aspect. However, the existing aspect-based sentiment classification approaches cannot fully model the dependency-relationship between words and are easily disturbed by irrelevant aspects. To address this problem, we propose a novel approach named Dependency-Relationship Embedding and Attention Mechanism-based LSTM. DA-LSTM first merges the word hidden vector output by LSTM with the dependency-relationship embedding to form a combined vector. This vector is then fed into the attention mechanism together with the aspect information which can avoid interference to calculate the final word representation for sentiment …classification. Our extensive experiments on benchmark data sets clearly show the effectiveness of DA-LSTM. Show more

Keywords: Aspect-based sentiment analysis, sentiment classification, dependency-relationship, attention mechanism

DOI: 10.3233/JIFS-202747

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 867-877, 2021

Authors: Sayed, Osama Rashed | Sayed, Nabil Hasan | Chen, Gui-Xiu

Article Type: Research Article

Abstract: In the present paper, a characterization of the intuitionistic fuzzy sets, the interval-valued intuitionistic fuzzy sets and their set-operations are given. By making use of these characterizations, the relationships between the interval-valued intuitionistic fuzzy topology and four fuzzy topologies associated to it are studied. For this reason, some subclasses of the family of interval-valued intuitionistic fuzzy topologies on a set which we call pre-suitable and suitable are introduced. Furthermore, the concepts of homeomorphism functions and compactness in the framework of interval-valued intuitionistic fuzzy topological spaces are introduced and studied.

Keywords: Interval-valued intuitionistic fuzzy set, interval-valued intuitionistic fuzzy topology, fuzzy topology, homeomorphism, compactness

DOI: 10.3233/JIFS-202757

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 879-889, 2021

Authors: Zhang, Qiang | Zhang, Luyu | Sun, Bingzhen

Article Type: Research Article

Abstract: In 2020, the spread of the COVID-19 epidemic has attracted global attention. As a large-scale group that is receiving higher education, college students also show greater mood swings. How to reduce the psychological harm of anxiety to college students is a problem that needs to be solved urgently. Based on this, this paper proposes an evaluation model for the anxiety level of college students in different regions under the influence of COVID-19. First of all, the general influence index of college student’s anxiety level is obtained by correlation analysis. Secondly, the logical OR of the double quantization variable precision fuzzy …set model and the degree fuzzy rough set model is used to establish the evaluation model of the anxiety level of college students under the influence of COVID-19. Finally, used big data, the idea of fuzzy upper and lower approximation, combined with the principle of maximum membership in fuzzy set theory, achieved the quantitative ranking of the anxiety levels of college students in different areas. The research shows that when the accuracy of decision-making is 45%, the anxiety level of the township college students group and the provincial capital or municipality college students group is higher. When the accuracy of decision-making is 65%, the anxiety level of the provincial capital or municipality college students group is higher than others. Show more

Keywords: Fuzzy rough set, two universes, COVID-19, college students anxiety level

DOI: 10.3233/JIFS-202760

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 891-902, 2021

Authors: Aishwarya, N. | BennilaThangammal, C. | Praveena, N.G.

Article Type: Research Article

Abstract: Getting a complete description of scene with all the relevant objects in focus is a hot research area in surveillance, medicine and machine vision applications. In this work, transform based fusion method called as NSCT-FMO, is introduced to integrate the image pairs having different focus features. The NSCT-FMO approach basically contains four steps. Initially, the NSCT is applied on the input images to acquire the approximation and detailed structural information. Then, the approximation sub band coefficients are merged by employing the novel Focus Measure Optimization (FMO) approach. Next, the detailed sub-images are combined using Phase Congruency (PC). Finally, an inverse …NSCT operation is conducted on synthesized sub images to obtain the initial synthesized image. To optimize the initial fused image, an initial decision map is first constructed and morphological post-processing technique is applied to get the final map. With the help of resultant map, the final synthesized output is produced by the selection of focused pixels from input images. Simulation analysis show that the NSCT-FMO approach achieves fair results as compared to traditional MST based methods both in qualitative and quantitative assessments. Show more

Keywords: Image fusion, multi-focus, NSCT, focus measure, decision map

DOI: 10.3233/JIFS-202803

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 903-915, 2021

Authors: Luo, Man

Article Type: Research Article

Abstract: The construction of hydraulic projects inevitably involves land requisition and resettlement, with considerable impact on the society, the environment, and the economy of the project site, and leading to social stability risk events. Therefore, it is necessary to systematically assess social stability risk to put forward corresponding countermeasures. By applying WSR theory (Wuli-Shili-Renli Theory) to the investigation of the case-study of the Jiangxiang Reservoir Project, this paper constructs an evaluation index system for the risk to social stability from land requisition and resettlement, from the three dimensions of “physics”, “matter”, and “human principle”. The GAHP (Group-decision Analytic Hierarchy Process) method …is used to determine the index weights, while the index values of each risk factor are determined by using the interval valued hesitant fuzzy sets (IVHFSs) method. A comprehensive assessment of risks to social stability from land requisition and resettlement in the Jiangxiang Reservoir Project is performed, and coping strategies for major social stability risk factors are proposed. This paper effectively supports the development of assessments of risks to social stability from land requisition and resettlement in other hydraulic projects. Show more

Keywords: Social stability risk assessment, land requisition and resettlement, hydraulic project

DOI: 10.3233/JIFS-202805

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 917-928, 2021

Authors: Mahmood, Nabeel | Qin, Rongjun | Butalia, Tarunjit Singh

Article Type: Research Article

Abstract: A risk assessment model is developed to estimate the potential combined influence of concurrent safety risks facing on-foot construction worker at a certain point in space or instant of time. The model is based on a holistic approach that comprehensively systemizes principal types and subjective values of possible safety risk events. Fuzzy fault tree is built using a deductive approach to identify possible concurrent basic and conditional risk events, not risk symptoms, from the major subgroups of triggering, enabling and environment-related risks. The inclusive risk breakdown structure helps in combating assessment underestimation related to overlooking influential risks. Adequate logic gates …are suggested at tree junctions to overcome assessment overestimation related to accumulating the effect of dependent, redundant, and non-concurrent risks, and ignoring the effectiveness of safety precautions and measures that may reduce or eliminate risks. Operational logic gates are applied to properly combine the residual risk of static (non-moving) events and dynamic (moving) events that can concurrently influence safety. The model is programmed into an interactive interfaced intelligent system to simulate cases of risk assessment input, computations, and output. The system shows the advantages of using the model as a prognostic or diagnostic tool to estimate top risk event. Subjective linguistic risk values can be induced for basic risk events at the bottom of the tree, and conditional risk events controlling residual risk values can be induced at different levels of the tree. Fuzzy logic plays a key role in hosting subjective risk evaluation into computational truth values to generate realistic and meaningful assessment values that are helpful for risk control. Show more

Keywords: On-foot building construction worker, safety risk assessment model, concurrent risk events, static dynamic risks, operational logic gates, fuzzy fault tree analysis, linguistic truth values

DOI: 10.3233/JIFS-202915

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 929-954, 2021

Authors: Riaz, Muhammad | Ali, Nawazish | Davvaz, Bijan | Aslam, Muhammad

Article Type: Research Article

Abstract: The aim of this paper is to introduce the concepts of soft rough q-rung orthopair fuzzy set (SRqROFS) and q-rung orthopair fuzzy soft rough set (qROPFSRS) based on soft rough set and fuzzy soft relation, respectively. We define some fundamental operations on both SRqROFS and qROPFSRS and discuss some key properties of these models by using upper and lower approximation operators. The suggested models are superior than existing soft rough sets, intuitionistic fuzzy soft rough sets and Pythagorean fuzzy soft rough sets. These models are more efficient to deal with vagueness in multi-criteria decision-making (MCDM) problems. We develop Algorithm i …(i  = 1, 2, 3, 4, 5) for the construction of SRqROFS, construction of qROFSRS, selection of a smart phone, ranking of beautiful public parks, and ranking of government challenges, respectively. The notions of upper reduct and lower reduct based on the upper approximations and lower approximations by variation of the decision attributes are also proposed. The applications of the proposed MCDM methods are demonstrated by respective numerical examples. The idea of core is used to find a unanimous optimal decision which is obtained by taking the intersection of all lower reducts and upper reducts. Show more

Keywords: Soft rough q-rung orthopair fuzzy set, q-rung orthopair fuzzy soft rough set, upper reduct, lower reduct, core, multi-criteria decision-making

DOI: 10.3233/JIFS-202916

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 955-973, 2021

Authors: Rath, Adyasha | Patnaik, Srikanta | Panda, Ganapati

Article Type: Research Article

Abstract: The density of population in cities is growing at a faster rate to make the life of people in cities comfortable and save. The city needs to be smart. It can be mainly achieved by intelligent decision making process using computational intelligence based systems. Keeping this in view, many researchers and organizations are working to develop and implement computational intelligence decision support systems. To obtain a comprehensive overview on the current status on SI based smart city community the present investigation has been made. To achieve this objective recently published standard articles on this important sub area have been collected …and reviewed. The summary of the review has been presented in systematic manner to facilitate the researchers who are currently working in the area of smart city community. The important findings of the review have been made and presented. The important performance measures in various aspects of smart city obtained by the computational intelligence methods have been listed. It is expected that the findings and the contribution of the paper will benefit the researchers, the related government and private organizations in terms of furthering their research efforts and producing different smart products pertaining to community development and improvement of comfort level of the dwellers of the smart city. Show more

Keywords: Smart city, computational intelligence, machine learning, intelligent transportation system, smart healthcare, smart environment, smart education, cyber security

DOI: 10.3233/JIFS-202919

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 975-991, 2021

Authors: Priyadharshini, V.M. | Valarmathi, A.

Article Type: Research Article

Abstract: Online social networks (OSNs) are utilized by millions of people from the entire world to communicate with others through Facebook and Twitter. The removal of fake accounts will increase the efficiency of the protection in OSNs. The construction of the OSN model has the nodes and the links to identify the fake profiles on Twitter. This paper proposes a novel technique to detect spam profiles and the proposed classifier is to classify the profile images from the dataset. The malicious profile detection technique is used to identify the fake profiles with the concept of a Twitter crawler that implements the …extraction of data from the profile. The feature set analysis has been implemented with the feature related analysis. The user behavior detection utilizes the adjacent matrix to measure the similarity values within the friend’s profiles. The multi-variant Support Vector Machine classifier is developed for efficient classification with the kernel function. The proposed technique is compared with the well-known techniques of ECRModel, ISMA and DeepLink that the detection rate is 2.5% higher than the related techniques, the computation time is 220 s lesser than the related techniques and the proposed technique has 3.1% higher accuracy. Show more

Keywords: Online social networks, twitter, spam detection, classification, malicious node

DOI: 10.3233/JIFS-202937

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 993-1007, 2021

Authors: Zhang, Huiyuan | Wei, Guiwu | Chen, Xudong

Article Type: Research Article

Abstract: The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes …through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified. Show more

Keywords: Multiple attribute group decision making (MAGDM), spherical fuzzy sets (SFSs), MABAC method, cumulative prospect theory (CPT), entropy method, combined weights, green supplier selection

DOI: 10.3233/JIFS-202954

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1009-1019, 2021

Authors: Demirci, Işıl Açık | Gürdal, Mehmet

Article Type: Research Article

Abstract: In this work, we study the lacunary I -statistical convergence concept of complex uncertain triple sequence. Four types of lacunary I -statistically convergent complex uncertain triple sequences are presented, namely lacunary I -statistical convergence in measure, in mean, in distribution and with respect to almost surely, and some basic properties are proved.

Keywords: Triple sequence, statistical convergence, ideal convergence, triple lacunary sequence, complex uncertain variable, uncertainty space

DOI: 10.3233/JIFS-202964

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1021-1029, 2021

Authors: Wu, Qiongling | Lin, Jian | Zhang, Shaohan | Tian, Zhiyong

Article Type: Research Article

Abstract: This paper constructs the continuous-Young optimal weighted arithmetic averaging (C-YOWA) operator and the continuous-Young optimal weighted geometric (C-YOWG) operator based on definite integral and Young inequality. A series of special cases and main properties of the proposed aggregation operators are also investigated. In order to integrate heterogeneous interval data and obtain more accurate prediction results, the heterogeneous interval combination prediction (HICP) model based on C-YOWA operator, C-YOWG operator and Theil coefficient is proposed. The HICP model consider not only the existence of both additive and multiplicative interval information, but also the preference information of experts. Finally, the model is applied …to the empirical analysis of wind energy prediction. The comparison of results shows that the established model can effectively improve the accuracy of prediction. Show more

Keywords: Combination prediction, continuous aggregation operator, interval number, young inequality, Theil coefficient

DOI: 10.3233/JIFS-210004

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1031-1048, 2021

Authors: Dong, Yuanxiang | Deng, Xinglu | Hu, Xinyu | Chen, Weijie

Article Type: Research Article

Abstract: Suppliers can be regarded as unavoidable sources of external risks in modern supply chains, which may cause disruption of supply chains. A resilient supplier usually has a high adaptive ability to reduce the vulnerability against disruptions and recover from disruption to keep continuity in operations. This paper develops an effective multi-attribute group decision-making (MAGDM) framework for resilient supplier selection. Because of the many uncertainties in resilient supplier selection, the dual hesitant fuzzy soft sets (DHFSSs), a very flexible tool to express uncertain and complex information of decision-makers, is utilized to cope with it. In order to obtain the resilient supplier’s …partial order relationship and consider the psychological behavior of decision-makers, this paper proposes the MAGDM framework with DHFSSs based on the TOPSIS method and prospect theory for resilient supplier selection. Furthermore, we consider the consensus level among experts of different backgrounds and experiences and propose a consensus measure method based dual hesitant fuzzy soft numbers (DHFSNs) before selecting a resilient supplier. The expert weights are calculated by the group consensus level between the expert and the group opinions. Meanwhile, we define the entropy of DHFSSs to determine the attribute weights objectively in the decision-making process. Based on this, the proposed method is applied to a practical manufacturing enterprise with an international supply chain for a resilient supplier selection problem. Finally, by performing a sensitivity analysis and a comparative analysis, the results demonstrate the robustness and validity of the proposed method. Show more

Keywords: Resilient supplier selection, group decision making, dual hesitant fuzz soft sets, consensus measure, entropy

DOI: 10.3233/JIFS-210025

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1049-1067, 2021

Authors: Liao, Wei | Wei, Xiaohui | Lai, Jizhou

Article Type: Research Article

Abstract: A novel actor-critic algorithm is introduced and applied to zero-sum differential game. The proposed novel structure consists of two actors and a critic. Different actors represent the control policies of different players, and the critic is used to approximate the state-action utility function. Instead of neural network, the fuzzy inference system is applied as approximators for the actors and critic so that the specific practical meaning can be represented by the linguistic fuzzy rules. Since the goals of the players in the game are completely opposite, the actors for different players are simultaneously updated in opposite directions during the training. …One actor is updated updated toward the direction that can minimize the Q value while the other updated toward the direction that can maximize the Q value. A pursuit-evasion problem with two pursuers and one evader is taken as an example to illustrate the validity of our method. In this problem, the two pursuers the same actor and the symmetry in the problem is used to improve the replay buffer. At the end of this paper, some confrontations between the policies with different training episodes are conducted. Show more

Keywords: Fuzzy inference system, differential game, reinforcement learning, pursuit-evasion problem, deterministic policy gradient

DOI: 10.3233/JIFS-210032

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1069-1082, 2021

Authors: Priyadarshi, Ankur | Saha, Sujan Kumar

Article Type: Research Article

Abstract: In this paper, we present our effort on the development of a Maithili Named Entity Recognition (NER) system. Maithili is one of the official languages of India, with around 50 million native speakers. Although various NER systems have been developed in several Indian languages, we did not find any openly available NER resource or system in Maithili. For the development, we manually annotated a Maithili NER corpus containing around 200K words. We prepared a baseline classifier using Conditional Random Fields (CRF). Then we ran many experiments using various recurrent neural networks (RNN). We collected larger raw corpus to obtain better …word embedding and character embedding. In our experiments, we found, neural models are better than CRF; a CRF layer is effective for the prediction of the final output in the RNN models; character embedding is effective in Maithili language. We also investigated the effectiveness of gazetteer lists in neural models. We prepared a few gazetteer lists from various web resources and used those in the neural models. The incorporation of the gazetteer layer caused performance improvement. The final system achieved an f-measure of 91.6% with 94.9% precision and 88.53% recall. Show more

Keywords: Named entity recognition, Maithili language, corpus annotation, LSTM model, gazetteer lists

DOI: 10.3233/JIFS-210051

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1083-1095, 2021

Authors: Rehman, Hafiz Asadul | Zafar, Kashif | Khan, Ayesha | Imtiaz, Abdullah

Article Type: Research Article

Abstract: Discovering structural, functional and evolutionary information in biological sequences have been considered as a core research area in Bioinformatics. Multiple Sequence Alignment (MSA) tries to align all sequences in a given query set to provide us ease in annotation of new sequences. Traditional methods to find the optimal alignment are computationally expensive in real time. This research presents an enhanced version of Bird Swarm Algorithm (BSA), based on bio inspired optimization. Enhanced Bird Swarm Align Algorithm (EBSAA) is proposed for multiple sequence alignment problem to determine the optimal alignment among different sequences. Twenty-one different datasets have been used in order …to compare performance of EBSAA with Genetic Algorithm (GA) and Particle Swarm Align Algorithm (PSAA). The proposed technique results in better alignment as compared to GA and PSAA in most of the cases. Show more

Keywords: Multiple sequence alignment, Particle swarm optimization, Bioinformatics, Genetic algorithm, swarm intelligence, bird swarm algorithm

DOI: 10.3233/JIFS-210055

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1097-1114, 2021

Authors: Zhou, Ze-Nan | Zhou, Zhiheng | Huang, Junchu

Article Type: Research Article

Abstract: Patch-based deep convolutional neural network (DCNN) has been proved to have advanced performance in no-reference image quality assessment (NR-IQA). However, these methods generally take global quality score as the quality score of each patch mainly since local quality score is not provided. Unfortunately, the perceived quality of image patch is difficult to maintain a high degree of consistency. Thus, the use of the same global quality score in different patches of the same image may hinder training of DCNNs. In this paper, we propose a universal and nearly cost-free model called Gaussian Random Jitter (GRJ). According to the uncertainty of …the perceived quality, GRJ divided the training images into high-confidence distorted images and low-confidence distorted images, and reasonably assigned different local quality scores to each patch through specific gaussian functions with the global quality score as the mean value and the undetermined hyperparameter as the standard deviation. We took one of the most advanced patch-based DCNNs models as backbone and tested the improved performance over three widely used image quality databases. We show that our model can further improve the performance of patch-based models and even help them comparable with those of state-of-the-art NR-IQA algorithms. Show more

Keywords: Patch, gaussian distribution, convolutional neural networks, no-reference image quality assessment

DOI: 10.3233/JIFS-210063

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1115-1124, 2021

Authors: Imran, Muhammad | Ali, Yasir | Malik, Mehar Ali | Hasnat, Kiran

Article Type: Research Article

Abstract: Chromatic spectrum of a colored graph G is a multiset of eigenvalues of colored adjacency matrix of G . The nullity of a disconnected graph is equal to sum of nullities of its components but we show that this result does not hold for colored graphs. In this paper, we investigate the chromatic spectrum of three different classes of 2-regular bipartite colored graphs. In these classes of graphs, it is proved that the nullity of G is not sum of nullities of components of G . We also highlight some important properties and conjectures to extend this problem …to general graphs. Show more

Keywords: Spectrum of graph, nullity of graph, graph coloring

DOI: 10.3233/JIFS-210066

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1125-1133, 2021

Authors: Liu, Haitao | Zhang, Qiang

Article Type: Research Article

Abstract: This paper studies cooperative games in which players have multiple attributes. Such games are applicable to situations in which each player has a finite number of independent additive attributes in cooperative games and the payoffs of coalitions are endogenous functions of these attributes. The additive attributes cooperative game, which is a special case of the multiattribute cooperative game, is studied with respect to the core, the conditions for existence and boundedness and methods of transformation regarding a general cooperative game. A coalitional polynomial form is also proposed to discuss the structure of coalition. Moreover, a Shapley-like solution called the efficient …resource (ER) solution for additive attributes cooperative games is studied via the axiomatical method, and the ER solution of two additive attribute games with equivalent total resources coincides with the Shapley value. Finally, some examples of additive attribute games are given. Show more

Keywords: Multiple attributes, cooperative games, Shapley value, core, solution

DOI: 10.3233/JIFS-210088

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1135-1150, 2021

Authors: Zulqarnain, Rana Muhammad | Xin, Xiao Long | Garg, Harish | Ali, Rifaqat

Article Type: Research Article

Abstract: In this article, we investigate the multi-criteria decision-making complications under Pythagorean fuzzy soft information. The Pythagorean fuzzy soft set (PFSS) is a proper extension of the Pythagorean fuzzy set (PFS) which discusses the parametrization of the attributes of alternatives. It is also a generalization of the intuitionistic fuzzy soft set (IFSS). The PFSS is used to precisely evaluate the deficiencies, anxiety, and hesitation in decision-making (DM). The most essential determination of the current study is to advance some operational laws along with aggregation operators (AOs) within the Pythagorean fuzzy soft environs such as Pythagorean fuzzy soft interaction weighted average (PFSIWA) …and Pythagorean fuzzy soft interaction weighted geometric (PFSIWG) operators with their desirable features. Furthermore, a DM technique has been established based on the developed operators to solve multi-criteria decision-making (MCDM) problems. Moreover, an application of the projected method is presented for the selection of an effective hand sanitizer during the COVID-19 pandemic. A comparative analysis with the merits, effectivity, tractability, along with some available research deduces the effectiveness of this approach. Show more

Keywords: Pythagorean fuzzy sets, Pythagorean fuzzy soft sets, PFSIWA operator, PFSIWG operator, hand sanitizer

DOI: 10.3233/JIFS-210098

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1151-1171, 2021

Authors: Lina, Wang | Zeshui, Xu

Article Type: Research Article

Abstract: Risk management is a significant part of the success of a public-private partnership (PPP) project. There are four phrases for the process of risk management: Constructing a risk management environment, identifying risk factors, evaluating risk factors, and allocating risk factors. After identifying risk factors, it is imperative to analyze and evaluate critical risk factors, which can help participants formulate strategies to allocate risk factors, and thus alleviate the possible adverse results. The objectives of analyzing and evaluating risk factors focus on two aspects: The possibilities of risk occurrence and the degrees of risk loss. On behalf of determining the critical …risk factors effectively, we take the probability degree and linguistic expressions into consideration to manifest experts’ perspectives. We consider critical risk factors in terms of the probabilistic linguistic terms with weakened hedges from the evidential reasoning approach view. The linguistic terms with weakened hedges are applied to express the degree of risk risk loss, and the possibilities of risk occurrence collect from the probabilities of linguistic terms with weakened hedges. First, the commonality function and plausibility function are applied to correct the possibilities of risk occurrence for linguistic terms with weakened hedges. Next, we build a risk evaluation model from experts’ risk propensity and risk perceptions. Moreover, a case study of the risk analyzing and evaluating process of a PPP project is applied to illustrate the availability and effectiveness of the proposed model. We contrast the introduced model with other approaches. Finally, the advantages of this model intend to improve the linguistic terms with weakened hedges for the probabilistic linguistic terms with weakened hedges and evaluate risk factors considering the evidence reasoning approach. Show more

Keywords: Risk evaluation, Probabilistic linguistic terms with weakened hedges, Evidential reasoning theory, Public-private partnership project

DOI: 10.3233/JIFS-210101

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1173-1191, 2021

Authors: Zhao, Yifan | Tian, Shuicheng

Article Type: Research Article

Abstract: Aiming at the problem of large error and long time of early warning response in the traditional system, this paper designs a hazard identification early warning system based on random forest algorithm in underground coal mine. By random classification decision forest created dangerous content in different areas of the downhole information input into the decision tree as a test sample, according to the result of the output of the leaf node determine the risk level of decision trees, and USES the high precision of decision forest classification ability the threat level assessment test sample, radically reducing hazards identification error. Then, …based on the evaluation results, combined with the threshold value of warning criteria to identify the gas exceeding limit area, and determine the fire source warning level, so as to realize the hazard source identification and warning. The simulation results show that the average hazard location identification error of the system is only 4.1%, and the warning response time can be controlled within 9 s. Show more

Keywords: Underground hazard sources, identify early warning, random forest algorithm, decision forest, risk assessment, alarm criteria threshold

DOI: 10.3233/JIFS-210105

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1193-1202, 2021

Authors: Kavitha, N | Ruba Soundar, K | Sathis Kumar, T

Article Type: Research Article

Abstract: In recent years, the Face recognition task has been an active research area in computer vision and biometrics. Many feature extraction and classification algorithms are proposed to perform face recognition. However, the former usually suffer from the wide variations in face images, while the latter usually discard the local facial features, which are proven to be important for face recognition. In this paper, a novel framework based on merging the advantages of the Key points Local Binary/Tetra Pattern (KP-LTrP) and Improved Hough Transform (IHT) with the Improved DragonFly Algorithm-Kernel Ensemble Learning Machine (IDFA-KELM) is proposed to address the face recognition …problem in unconstrained conditions. Initially, the face images are collected from the publicly available dataset. Then noises in the input image are removed by performing preprocessing using Adaptive Kuwahara filter (AKF). After preprocessing, the face from the preprocessed image is detected using the Tree-Structured Part Model (TSPM) structure. Then, features, such as KP-LTrP, and IHT are extracted from the detected face and the extracted feature is reduced using the Information gain based Kernel Principal Component Analysis (IG-KPCA) algorithm. Then, finally, these reduced features are inputted to IDFA-KELM for performing FR. The outcomes of the proposed method are examined and contrasted with the other existing techniques to confirm that the proposed IDFA-KELM detects human faces efficiently from the input images. Show more

Keywords: Face recognition, kernel ensemble learning machine, adaptive kuwahara filter, improved dragonfly algorithm

DOI: 10.3233/JIFS-210130

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1203-1216, 2021

Authors: Li, Lulu

Article Type: Research Article

Abstract: Set-valued data is a significant kind of data, such as data obtained from different search engines, market data, patients’ symptoms and behaviours. An information system (IS) based on incomplete set-valued data is called an incomplete set-valued information system (ISVIS), which generalized model of a single-valued incomplete information system. This paper gives feature selection for an ISVIS by means of uncertainty measurement. Firstly, the similarity degree between two information values on a given feature of an ISVIS is proposed. Then, the tolerance relation on the object set with respect to a given feature subset in an ISVIS is obtained. Next, λ …-reduction in an ISVIS is presented. What’s more, connections between the proposed feature selection and uncertainty measurement are exhibited. Lastly, feature selection algorithms based on λ -discernibility matrix, λ -information granulation, λ -information entropy and λ -significance in an ISVIS are provided. In order to better prove the practical significance of the provided algorithms, a numerical experiment is carried out, and experiment results show the number of features and average size of features by each feature selection algorithm. Show more

Keywords: Rough set theory, ISVIS, feature selection, similarity degree, λ-reduction, λ-discernibility matrix, λ-information granulation, λ-information entropy, λ-significance, algorithm

DOI: 10.3233/JIFS-210135

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1217-1235, 2021

Authors: Wang, Lu

Article Type: Research Article

Abstract: With the prosperity of national economy and the development of highway construction, highway freight transportation plays an increasingly important role in the market economy. Due to its great flexible characteristic, highway freight transportation has been the main mode of transportation in China. On the macro level, there are many factors affecting the development of highway freight transportation especially under the background of the new era. Based on the historical data of the development of highway freight transportation, grey entropy analysis method is applied to analyze the significance of influencing factors for the development of highway freight transportation whose key indicator …is highway freight turnover. Then GM (1, N) model is established to predict the development trend of highway freight turnover and its significant influencing factors. Finally, main problems existing in highway freight transportation and development prospect were discussed and analyzed. The research results show that the three most significant factors affecting the development of road freight turnover in China are the total state revenue, GDP and average distance of highway freight. The established GM (1, N) model can conduct high precision prediction for the development of highway freight transportation. Opportunities and challenges of highway freight transportation industry coexist and its development prospect is promising. It is expected to provide beneficial references for the development strategy and decision-making of highway freight transportation in China. Show more

Keywords: Highway freight transportation, significance analysis, grey entropy analysis method, GM (1, N) prediction model

DOI: 10.3233/JIFS-210141

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1237-1246, 2021

Authors: Tao, Ning | Xiaodong, Duan | Lu, An | Tao, Gou

Article Type: Research Article

Abstract: A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and …company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified. Show more

Keywords: Flexible job-shop scheduling, deteriorating effect, emergency order insertion, disruption management, multi-phase quantum particle swarm optimization

DOI: 10.3233/JIFS-210166

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1247-1259, 2021

Authors: Bahrami, Vahid | Kalhor, Ahmad | Masouleh, Mehdi Tale

Article Type: Research Article

Abstract: This study intends to investigate the dynamic model estimation and the design of an adaptive neural network based controller for a passive planar robot, performing 2-DoF motion pattern which is in interaction with an actuated cable-driven robot. In fact, the main goal of applying this structure is to use a number of light cables to drive serial robot links and track the desired reference model by the robot’s end-effector. The under study system can be used as a rehabilitation setup which is helpful for those with arm disability. In this way, upon applying sliding mode error dynamics, it is necessary …to determine a vector that contains the matrices related to the robot dynamics. However, finding these matrices requires the use of computational approaches such as Newton-Euler or Lagrange. In addition, since the purpose of this paper is to express comprehensive methods, so with increasing the number of links and degrees of freedom of the robot, finding the dynamics of the robot becomes more difficult. Therefore, the Adaptive Neural Network (ANN) with specific inputs has been used for estimation unknown matrices of the system and the controller design has been performed based on it. So, the main idea in using an adaptive controller is the fact there is no pre-knowledge for the dynamic modeling of the system since the human arm could have different dynamic properties. Hence, the controller is formed by an ANN and robust term. In this way, the adaptation laws of the parameters are extracted by Lyapunov approach, and as a result, as aforementioned, the asymptotic stability of the whole of the system is guaranteed. Simulation results certify the efficiency of the proposed method. Finally, using the Roots Mean Square Error (RMSE) criteria, it has been revealed that, in the presence of bounded disturbance with different amplitude, adding the robust term to the controller leads to improve the tracking error about 34% and 62%, respectively. Show more

Keywords: Dynamic model estimation, adaptive neural network controller, lyapunov approach, passive planar robot, actuated cable-driven robot and rehabilitation setup

DOI: 10.3233/JIFS-210180

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1261-1280, 2021

Authors: Wenbo Huang, First A. | Changyuan Wang, Second B. | Hongbo Jia, Third C.

Article Type: Research Article

Abstract: Traditional intention inference methods rely solely on EEG, eye movement or tactile feedback, and the recognition rate is low. To improve the accuracy of a pilot’s intention recognition, a human-computer interaction intention inference method is proposed in this paper with the fusion of EEG, eye movement and tactile feedback. Firstly, EEG signals are collected near the frontal lobe of the human brain to extract features, which includes eight channels, i.e., AF7, F7, FT7, T7, AF8, F8, FT8, and T8. Secondly, the signal datas are preprocessed by baseline removal, normalization, and least-squares noise reduction. Thirdly, the support vector machine (SVM) is …applied to carry out multiple binary classifications of the eye movement direction. Finally, the 8-direction recognition of the eye movement direction is realized through data fusion. Experimental results have shown that the accuracy of classification with the proposed method can reach 75.77%, 76.7%, 83.38%, 83.64%, 60.49%,60.93%, 66.03% and 64.49%, respectively. Compared with traditional methods, the classification accuracy and the realization process of the proposed algorithm are higher and simpler. The feasibility and effectiveness of EEG signals are further verified to identify eye movement directions for intention recognition. Show more

Keywords: EM, EEG, tactile feedback, wireless sensor network, flying driving, brain electrical signals, data fusion

DOI: 10.3233/JIFS-210191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1281-1296, 2021

Authors: Narendiranath Babu, T. | Senthilnathan, N. | Pancholi, Shailesh | Nikhil Kumar, S.P. | Rama Prabha, D. | Mohammed, Noor | Wahab, Razia Sultana

Article Type: Research Article

Abstract: This study aims at developing a novel method for condition monitoring technique for detection and classification of developing faults and increase the working life of continuous variable transmission (CVT) using Daubechies Wavelet 06 (DB-06). The vibration data is collected for 4 different types of faults and healthy condition. Using a magnetic accelerometer and signal analyser, vibration data is collected from the system in the time-domain which is then used as input for a MATLAB code producing the plot of the frequency-domain signal. Maximum frequency is determined to diagnose the faults which are induced over three different belts. Collected data for …large scale automotive system (CVT) is used to train the network and then it is tested based on random data points. Faults were classified using ANN with a classification rate of 90.8 %. Show more

Keywords: Continuous variable transmission (CVT), Daubechies wavelet, fault diagnosis, fault classification, artificial neural network

DOI: 10.3233/JIFS-210199

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1297-1307, 2021

Authors: Guo, Wang | Liu, Xingmou | Ma, You | Zhang, Rongjie

Article Type: Research Article

Abstract: The correct identification of gene recombination cold/hot spots is of great significance for studying meiotic recombination and genetic evolution. However, most of the existing recombination spots recognition methods ignore the global sequence information hidden in the DNA sequence, resulting in their low recognition accuracy. A computational predictor called iRSpot-DCC was proposed in this paper to improve the accuracy of cold/hot spots identification. In this approach, we propose a feature extraction method based on dinucleotide correlation coefficients that focus more on extracting potential DNA global sequence information. Then, 234 representative features vectors are filtered by SVM weight calculation. Finally, a convolutional …neural network with better performance than SVM is selected as a classifier. The experimental results of 5-fold cross-validation test on two standard benchmark datasets showed that the prediction accuracy of our recognition method reached 95.11%, and the Mathew correlation coefficient (MCC) reaches 90.04%, outperforming most other methods. Therefore, iRspot-DCC is a high-precision cold/hot spots identification method for gene recombination, which effectively extracts potential global sequence information from DNA sequences. Show more

Keywords: Recombination spots, correlation coefficient, DNA property matrix, support vector machines, convolutional neural network

DOI: 10.3233/JIFS-210213

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1309-1317, 2021

Authors: Shahzadi, Sundas | Rasool, Areen | Sarwar, Musavarah | Akram, Muhammad

Article Type: Research Article

Abstract: Bipolarity plays a key role in different domains such as technology, social networking and biological sciences for illustrating real-world phenomenon using bipolar fuzzy models. In this article, novel concepts of bipolar fuzzy competition hypergraphs are introduced and discuss the application of the proposed model. The main contribution is to illustrate different methods for the construction of bipolar fuzzy competition hypergraphs and their variants. Authors study various new concepts including bipolar fuzzy row hypergraphs, bipolar fuzzy column hypergraphs, bipolar fuzzy k -competition hypergraphs, bipolar fuzzy neighborhood hypergraphs and strong hyperedges. Besides, we develop some relations between bipolar fuzzy k …-competition hypergraphs and bipolar fuzzy neighborhood hypergraphs. Moreover, authors design an algorithm to compute the strength of competition among companies in business market. A comparative analysis of the proposed model is discuss with the existing models such bipolar fuzzy competition graphs and fuzzy competition hypergraphs. Show more

Keywords: Bipolar fuzzy competition hypergraphs, bipolar fuzzy k-competition hypergraphs, bipolar fuzzy neighborhood hypergraphs

DOI: 10.3233/JIFS-210216

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 1319-1339, 2021