Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Zhao, Tao | Wu, Qing | Li, Shengchuan | Guo, Rui | Dian, Songyi | Jia, Hairui

Article Type: Research Article

Abstract: In this paper, a general type-2 fuzzy logic controller (GT2FLC), which is optimized by the particle swarm optimization (PSO) algorithm, is applied to a power-line inspection (PLI) robot. The information fusion is used to design the GT2FLC to avoid the rule explosion. The proposed controller has the ability to deal with uncertainties when the PLI robot works on the insulated access cable. In order to compare the performance of the proposed controller with that of other controllers, the type-1 fuzzy logic controller (T1FLC) and the interval type-2 fuzzy logic controller (IT2FLC) are both optimized by the PSO to adjust the …PLI robot. To show the ability of different controllers to deal with uncertainties, external disturbances and parameter perturbations are added to the PLI robot. According to simulations, the performance of the proposed controller is better than that of other controllers, and the proposed controller has better ability to deal with uncertainties. Show more

Keywords: Power-line inspection robot, particle swarm optimization algorithm, general type-2 fuzzy logic controller

DOI: 10.3233/JIFS-182515

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Shen, Chong | Chen, Fan-Hong | Shi, Fu-Gui

Article Type: Research Article

Abstract:  The main objective of this paper is to provide some characterizations of M -fuzzifying convex structures in terms of derived operators. We first introduce the notion of M -fuzzifying convexly derived operators, and then establish the one-to-one correspondence between M -fuzzifying convexly derived operators and M -fuzzifying convex structures. Additionally, it is proved that M -fuzzifying CP mappings can be expressed as formulas of derived sets. Finally, we introduce the notion of M -fuzzifying restricted convexly derived operators and prove that it is isomorphic to M -fuzzifying convex structures.

Keywords: M-fuzzifying convex structure, M-fuzzifying derived operator, M-fuzzifying convexly derived operator, M-fuzzifying restricted convexly derived operator, M-fuzzifying restricted hull operator

DOI: 10.3233/JIFS-182910

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Mougouei, Davoud | Powers, David M.W. | Mougouei, Elahe

Article Type: Research Article

Abstract:  Resource limitations in software projects rarely allow for the security requirements to be fully realized. As such, Prioritization and Selection (PAS) techniques are used to find an optimal subset of the requirements. Consequently, some of the security requirements will be ignored. But ignoring security requirements may (a) leave some of the security threats unattended and (b) negatively impact the effectiveness of the selected requirements. To mitigate this, we have proposed a fuzzy framework, referred to as Prioritization And Partial Selection (PAPS), that reduces the number of ignored security requirements by allowing for partial satisfaction of those requirements. We …achieve this by relaxing the satisfaction conditions of security requirements, when tolerated, based on their priorities specified by a fuzzy inference system. Taking into account the partiality of security in PAPS mitigates the adverse impact of ignoring security requirements and enhances the accuracy of prioritization and selection. Our proposed framework is scalable to a large number of requirements. Show more

Keywords: Security, Requirements, Partial Selection, Fuzzy

DOI: 10.3233/JIFS-182907

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Li, Yongjun | Wei, Jianshuang | Kang, Kai | Wu, Zhouyang

Article Type: Research Article

Abstract:  Aviation customer churn analysis is a difficult point, which has puzzled over airlines. The difficulties lie in the imbalance of customer churn data distribution and noisy data interference. Although some existing sampling techniques and ensemble models are good at dealing with class imbalance problem, noisy examples in dataset seriously affects the sampling quality and predictive accuracy of classifiers. Therefore, the purpose of our work is to effectively solve the problem of noise interference in imbalanced data classification and improve the effect of the ensemble classifier. In this paper, we propose a novel noise filtering algorithm that combined Tomek-link with distance …weighted KNN (TWK), which can effectively filter the noise from both minority and majority class in the imbalanced dataset and prevent relative value samples from being rejected by mistake. We integrate TWK and feature sampling into EasyEnsemble to get a new ensemble model, named FSEE-TWK for short, for customer churn analysis. The introduction of feature sampling to FSEE-TWK accelerate the process of training and avoid model over-fitting. We obtained imbalanced customer data from a major Chinese airline to predict potential churn customers. We use F-Measure and G-Mean to evaluate the performance of the new ensemble model. The experimental results show that the proposed model can effectively improve the classification of datasets and significantly reduce the training time of the model. Show more

Keywords: Aviation customer churn analysis, classification model, ensemble learning, noise filter, under-sampling

DOI: 10.3233/JIFS-182807

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Hamidi, Mohammad | Smarandache, Florentin

Article Type: Research Article

Abstract: This paper considers networks as wireless sensor (hyper)networks and social (hyper)networks by single–valued neutrosophic (directed)(hyper)graphs.The notion of single–valued neutrosophic hypergraphs are extended to single–valuedneutrosophic directed hypergraphs and conversely. We derived single–valued neutrosophic digraphs from single–valued neutrosophic directed hypergraphs via a positive equivalence relation. It tries to use single–valued neutrosophic directed hypergraphs and positive equivalence relation to create the sensor clusters and to access to cluster heads in wireless sensor (hyper)networks. Finally, the concept of α -derivable single–valued neutrosophic digraph is considered as the energy-efficient protocol of wireless sensor networks and is applied this concept as a tool in wireless sensor …(hyper)networks. Show more

Keywords: Single–valued neutrosophic directed (graphs)hypergraphs, positive equivalence relation, α-(semiself-self)derivable single–valued neutrosophic digraph, SN, WSN

DOI: 10.3233/JIFS-190036

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Shan, Chuanhui | Guo, Xirong | Ou, Jun

Article Type: Research Article

Abstract:  Image denoising is a hot topic in many research fields, such as image processing and computer vision. With the development of deep learning, deep neural networks are widely used for image denoising and have achieved good effectiveness. Inspired by the characteristics of feed-forward denoising convolutional neural network (DnCNN) and biological neuron response, we propose a Symmetry-Rectifier Linear Unit (SyReLU) and further offer a corresponding SyReLU activation function, which has a better consistency with biological neuron characteristics in comparison with other activation functions, e.g. Rectifier Linear Unit (ReLU) and Leaky Rectifier Linear Unit(LReLU). Also, in order to denoise image, we use SyReLU …activation function for residual learning of CNN (e.g. DnCNN). Specially, the experimental results indicate DnCNN with SyReLU can achieve better effectiveness than DnCNN with other activation functions (e.g.ReLU and LReLU) for image denosing on Set12 and BSD68 datasets. Briefly, the proposed method plays an important role in the development of activation function and is very useful in deep neural networks for image denosing. Show more

Keywords: Image denoising, Symmetry-Rectifier Linear Unit, convolutional neural networks, SyReLU activation function, residual learning

DOI: 10.3233/JIFS-190017

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Junhua, Duan | Yi-an, Zhu | Dong, Zhong | Lixiang, Zhang | Lin, Zhang

Article Type: Research Article

Abstract: Transfer learning has been identified as conducive to improving the speed of machine learning in many areas. In multi-task reinforcement learning, transfer learning can assist the transfer of experiences between different tasks. The research conducted in this article is focused on two aspects. On the one hand, multi-task parallel transfer learning can improve the learning speed of parallel learning tasks. On the other hand, the learning of the current optimal experience can help the target point rewards to be transmitted to the starting point. The value of this self-learning can also accelerate the convergence speed of the reinforcement learning. According …to the research into these two aspects, this paper uses the idea of particle swarm optimization (PSO) to conduct self-learning and interactive learning in multi-task parallel learning. In this paper, a new multi-task learning algorithm named PSO-MTPRL (Multi-Task Parallel Reinforcement Learning based on PSO) is proposed. Based on the idea of PSO algorithm, the Boltzmann strategy, Self-Learning Process (SLP) and Interactive Learning Process (ILP) are selected probabilistically. Based on the characteristic exhibited by reinforcement learning, segmented learning model is recommended. In the early learning stages, the complete Boltzmann exploration strategy is applied, and B-SLP-ILP (Boltzmann-SLP- ILP) learning procedure is conducted exclusively in the middle stage of the learning. In the late learning stages, Boltzmann exploration is involved again. The segmented learning model can help ensure the balance of the exploration and exploitation, in addition to ensuring that all tasks convergence. Show more

Keywords: Multi-task reinforcement learning, parallel reinforcement learning, particle swarm optimization, transfer learning

DOI: 10.3233/JIFS-190209

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Yang, Bin

Article Type: Research Article

Abstract: As a technique for granular computing, rough sets deal with the vagueness and granularity in information systems. Covering-based rough sets are natural extensions of the classical rough sets by relaxing the partitions to coverings and have been applied in many fields. However, many vital issues in covering-based rough sets, including attribute reduction, are NP-hard and therefore the algorithms for addressing them are usually greedy. Hence, it is necessary and helpful to generalize the covering-based rough sets from different viewpoints. In this paper, a new type of covering-based rough sets, named parametric covering-based rough sets, are proposed and some properties and …applications of the parametric covering-based rough sets are investigated. First, a concept of inclusion degree is introduced into covering-based rough set theory to explore some properties of the parametric covering approximation space. Second, the parametric covering-based rough sets are established on the basis of inclusion degree. Moreover, some properties of the parametric covering-based rough sets are introduced. Third, it is found that the calculations of corresponding parametric covering-based lower and upper approximations can be converted into the operations of matrices, which makes the calculations convenient. Finally, a simple application of the parametric covering-based rough sets to network security is introduced. Show more

Keywords: Granular computing, Covering, Rough set, Neighborhood, Inclusion degree, Parametric covering-based rough sets, Network security

DOI: 10.3233/JIFS-182902

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Nilofer, Ms. | Rizwanullah, Mohd.

Article Type: Research Article

Abstract: In this paper a simplification of the CPP is measured, a set of important nodes is given in a linear order and the work is to path all edges at least once in such a technique that the advanced priority nodes are stayed as soon as possible. All roads in the networks are covered by postman tour.postman tour covering all the roads in the network. The solutions found here are valid for the case, where the cost of additional edges traversed is much bigger that the cost of delays and delay for the first priority node is much bigger than …the cost of delay for the second node, and so on. More detailed study of various cost functions may be an interesting topic for future research. Show more

Keywords: Graph, Eulerian tour, road network, higher priority node

DOI: 10.3233/JIFS-190035

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-5, 2019

Authors: Khalid, Asma | Beg, Ismat

Article Type: Research Article

Abstract: The aim of this paper is to introduce the notion of truthfulness in an influence based decision making model. An expert may submit his opinions truthfully or he may dismantle the original situation by undermining the actual opinion, such a decision maker is called an evasive decision maker or an almost truthful decision maker in this paper. It is assumed that experts in the panel are dignified members hence even though they are not habitual liars, they are either “almost truthful” or evasive. To measure their degree of truthfulness, we use the information provided by them in the form of …preference relations. We use this information to state the foundation of influence model of evasive decision makers. Finally, a ranking method is proposed to find best possible solutions. Show more

Keywords: Truthfulness, group decision making, social influence networks, additive reciprocity

DOI: 10.3233/JIFS-182775

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Wu, Hsien-Chung

Article Type: Research Article

Abstract: The intersection and union of non-normal fuzzy sets using general aggregation functions are studied in this paper. The conventional intersection and union of fuzzy sets are based on the membership functions using the max and min functions, or t-norm and s-norm in general in which the fuzzy sets may assume to be normal in order to follow the boundary conditions that include 0 and 1 in the unit interval [0, 1]. When the fuzzy sets are taken to be non-normal, the α -level sets may be empty for some α  ∈ [0, 1]. In this paper, we shall consider the aggregation …functions, instead of t-norm and s-norm, satisfying the concepts of compatibility that are based on the α -level sets of intersection and union. In this case, the emptiness of α -level sets should be avoided, which is the main issue of this paper. Show more

Keywords: Aggregation functions; Interval range; Normal fuzzy sets; Set intersection; Set union.

DOI: 10.3233/JIFS-190270

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2019

Authors: Wen, Li-Hua | Shi, Zhi-Hua | Liu, Hong-Yao

Article Type: Research Article

Abstract: There are various kinds of common natural disasters, including flood, drought, typhoon, geological disaster, forest fire and major biological disaster. Natural disaster is an abnormal event in the evolution of geographical environment, but it has become one of the most important natural factors hindering the development of human society. With the economic development and population expansion of human beings, water resource shortage is becoming more and more serious, so drought has always been a major natural disaster faced by mankind. This paper studies the GIS-based risk assessment and regionalization of Taihang Mountain drought and flood disasters. In the process of …regional environmental quality assessment, GIS technology is used to conduct an objective and comprehensive evaluation of the environmental quality of the whole region. This paper then constructs the combination of GIS technology and QUEST algorithm. Based on the decision tree model of Taihang Mountain drought disaster risk assessment, the risk of drought disaster in Taihang Mountain is evaluated. The results show that the distribution of drought disaster in Taihang Mountains is similar to that of drought disaster risk. The risk of drought disaster mainly distributes in the middle and west of Taihang Mountains. The risk in the east of Taihang Mountains is the lowest. The risk in the west of Taihang Mountains increases gradually. Generally speaking, the drought resistance of southern Taihang Mountains is higher than that of northern Taihang Mountains. Show more

Keywords: GIS, Taihang Mountain, drought disaster, risk assessment, zoning

DOI: 10.3233/JIFS-179308

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Luo, Junhui | Liu, Xianlin | Mi, Decai | Chen, Deqiang | He, Zhifen | Xu, Longwang

Article Type: Research Article

Abstract: In Guangxi marine soft foundation of a highway, the research of the intelligent dynamic response of marine roadbeds under traffic loading is carried out. To describe the interaction characteristics of vehicles and soft marine foundation, fine-analyzing the mechanical mechanism of various kinds of damage in early stage and the key factors affecting on the car, it need step up pavement coupling. Accordingly, it was based on the assumption of rigid pavement based on the Lagrange method, meet the viscoelastic foundation of the infinite beam, using sine wave road model of MW. Sayers vehicle road coupling system is used to calculate …and analyze the time history curve of traffic load. Then, plugged the loads into that the finite element, the initial dynamic stress and the counting of the influence of marine soft foundation depth was obtained under traffic loading. The results show that the vehicle road coupling system based on the balance mechanics method is effective. It can be extended to consider the stress of traffic loads and ocean soft foundation, and calculate the depth, considering the viscoelastic boundary. It effectively predicts the stress of marine soft soil foundation, and has important guiding significance for theoretical research and engineering practice. Show more

Keywords: Marine soft, traffic load, pavement coupling, finite element, viscoelastic boundary, intelligent

DOI: 10.3233/JIFS-179317

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Pang, Hui | Dong, Shaohua | Zhang, Xinwei

Article Type: Research Article

Abstract: In this paper, under the circumstance of uncertain customer demand, the enterprises on the same node in multiple supply chains conduct horizontal inventory coordination according to their own inventory and demand. Based on the combination of horizontal inventory replenishment and vertical normal replenishment, the related mathematical model has been established. By studying the inventory strategy in the decentralized and centralized decision-making, the dual marginalization effects are found in the network system composed of multiple supply chain. So the revenue sharing contract is introduced to solve this problem. It has been found in the study that after adopting the horizontal inventory …coordination mechanism of the supply chain, the profit of the members in the supply chain system and the overall profit of the system are both higher than those which didn’t adopt the mechanism. The improved multi-objective genetic algorithm is used to calculate and verify the problem. In particular, after the revenue sharing contract is adopted, the profits are further enhanced. Show more

Keywords: Inventory coordination, economic order quantity, inventory strategy, revenue sharing, multi-objective genetic algorithm

DOI: 10.3233/JIFS-179316

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Chen, Limin | Ma, Mengli | Sun, Lixin

Article Type: Research Article

Abstract:  In the current agricultural product consumption market, the consumer’s demand for agricultural products tends to be diversified and individualized, and they need stricter links of cold chain logistics distribution of agricultural products. The cold chain logistics of fresh agricultural products is also the business of high energy consumption and high carbon emission in the logistics industry. The contradictory relationship between it and the “low-carbon economy” advocated today leads to the necessity to consider the relationship between economic benefit and environmental impact in the process of rapid development. Based on this, this paper, from the perspective of low-carbon economy, based on …the analysis of the necessity of optimizing the distribution path of cold chain logistics of agricultural products, constructs a model for this and puts forward a swarm intelligence optimization algorithm-particle swarm optimization (PSO) algorithm. The algorithm is improved from inertia weight, convergence factor, learning factor, and population size and so on. The optimized PSO algorithm is compared with the traditional PSO algorithm. Finally, the simulation results show that the improved algorithm can be used to optimize the distribution path of cold chain logistics of agricultural products effectively, and the specific optimization countermeasures are put forward according to the actual situation. Show more

Keywords: Low carbon economy, cold chain logistics, agricultural products, distribution system, optimization

DOI: 10.3233/JIFS-179304

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Wei, Pengcheng | Li, Li

Article Type: Research Article

Abstract: How to recommend learning resources to users accurately to meet the individual needs of users becomes the key issue with the increasing number of online education users. A personalized recommendation system was proposed in this paper based on user preference behavior data analysis to analyze the online education recommendation model. It determines the criteria set of the recommendation system with the product attribute mining method, and then uses the personalized recommendation algorithm for user preference modeling to explore the user’s preference for each criterion, thereby producing more accurate recommendations. The simulation results of the algorithm proposed in this paper show …that the multi-criteria recommendation algorithm using user distance similarity works best. Using this personalized recommendation algorithm based on user preference can effectively improve the recommendation quality. Show more

Keywords: User behavior, data analysis, online education

DOI: 10.3233/JIFS-179307

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Shen, Chen | Lin, Hongfei | Hao, Huihui | Yang, Zhihao | Wang, Jian | Zhang, Shaowu

Article Type: Research Article

Abstract: With the rapid development of clinical and laboratory medicine, the field of bioinformatics boasts of extensive clinical records and research literature. Retrieving effective information from this huge data has become a challenging task. Hence, Intelligent text summarization, which enables users to find and understand relevant source texts more quickly and effortlessly, becomes a very significant and valuable field of research. In this study, we propose an improved TextRank algorithm with weight calculation based on sentence graph to solve this problem. For the experimental dataset obtained from Pubmed, we represent terms as vectors by using Skip-gram model. We design three methods …which utilize word embeddings to calculate weights between sentences. Then we build an undirected graph with sentences as nodes. At last, we use the improved TextRank algorithm to calculate the importance of sentences and further generated summarizations base on its ranking. The experimental results and analysis on the datasets demonstrate the effectiveness of the proposed model. Show more

Keywords: Intelligent, text summarization, graph-based ranking, similarity calculation

DOI: 10.3233/JIFS-179315

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Yao, Fuguang

Article Type: Research Article

Abstract: At present, China has great difficulty in obtaining the reliability of teaching data sources. In order to further improve the effectiveness of data mining and reduce the difficulty of data acquisition, this paper studies the design and simulation of integrated education information teaching system based on fuzzy logic. Bayesian algorithm can perform data mining, feature recognition and classification on data in big data, so that it can effectively process massive data sources. By weighting the different network structures, the number of undirected edges in the network is reduced, and then small data sets that can be processed by multiple traditional …algorithms are sampled from the big data set, and data is generated by using the Bayesian network toolkit Samiam. The modules respectively generate data sets of different sizes and construct a teaching data source generation model. The experimental results show that RSEM on Child and Alarm data can take less time and achieve an accuracy of 86.17% compared with the whole data set under the same effect. This paper proposes a Bayesian network structure integration model, which can solve the problem of data acquisition difficulties, and is also a further improvement of data mining technology. Show more

Keywords: Deep learning, data mining, teaching data source

DOI: 10.3233/JIFS-179303

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Yang, Yanguo | Yu, Jiaqi | Fu, Yubin | Hu, Jiangtao

Article Type: Research Article

Abstract: As there are many uncertain factors in the geological hazard risk, great challenges are brought to the comprehensive evaluation of it. In order to improve the comprehensiveness and accuracy of geological hazard risk assessment, a cloud fuzzy clustering algorithm is constructed in this paper, which can effectively estimate and evaluate uncertain variables. The weight value of the risk cloud droplets is calculated as the input. By setting up clustering conditions and function output conditions, the cluster weights of the inputs which meet requirements can be obtained by multiple clustering iterations. Through the introduction of time parameters, the influence of time …factors on data importance and the risk severity of geological disaster emergencies are fully considered. The experimental results show that the calculated risk degree cluster weights are less than 1, which verifies the feasibility and practicability of the algorithm. The research in this paper shows that the clustering dynamic assessment of geological hazards can help to improve the accuracy of risk assessment and provide reference and help for the prevention and control of regional geological hazards. Show more

Keywords: Fuzzy, clustering algorithm, geological hazards

DOI: 10.3233/JIFS-179311

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Cui, Ranran

Article Type: Research Article

Abstract: We shall consider intelligent homological dimensions of 0-direct union of finite Rees matrix semigroups. First we give some characterizations of Rees matrix semigroup algebras. Then if K is a ring and S has a Rees matrix ideal M, we give the bounds of r.gl.dim K[S] in terms of r.gl.dim K  [T i ] and r.gl.dim K[S/M]. The bounds for r.gl.dim K[S] are given, supposing that the finite monoid S is a 0-direct union of some finite Rees matrix semigroups which are in forms of S i  = M (T i  ; I i  ; Λ i  ; P i ). …In addition, it is determined that K[S] has finite homological dimension if and only if each T i has finite homological dimension. Show more

Keywords: Homological dimension, *-ideal chain, primitively decomposable abundant semigroups, inverse semigroup, intelligent

DOI: 10.3233/JIFS-179313

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-5, 2019

Authors: Lin, Yu | Yu, Xuejun | Glaubitt, Walther

Article Type: Research Article

Abstract: At present, distributed systems have been widely used, and a lot of research has been done on the reliability of distributed systems. However, trusted 3.0 based distributed system node trust behavior recognition research is still relatively rare. This paper focuses on the identification process and evaluation method of distributed node trust behavior. In this paper, call links and resource consumption of software behavior are obtained by burying points during the development phase. Based on the idea of “sense of words and deeds”, this paper compares the pre-acquired trust call links with the resource consumption sample data, in order to obtain …a credible real-time software behavior model. This paper will focus on the analysis and extend to the distributed environment, and conduct a trusted analysis of software behavior, which provides a new idea for software trusted behavior analysis. Show more

Keywords: Trust 3.0, distributed nodes, trusted behavior, identification model

DOI: 10.3233/JIFS-179296

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Li, Yan

Article Type: Research Article

Abstract: With the development and wide application of wireless sensor networks, a data detection method based on time series is proposed to solve the problem that the sampling values of sensors vary greatly in harsh environments and the detection results of events are inaccurate with the increase of fault nodes in wireless sensor networks. The median of the normal data collected by the sensor is used to establish the reference value, and then the confidence interval is constructed. Finally, a method based on calculating the difference degree of the data interval is proposed to determine the source of the anomaly. The …experimental results show that the proposed method keeps the detection rate of abnormal data in sensor networks above 98% and the false alarm rate below 0.6%. It has certain reliability and practicability. Show more

Keywords: Anomaly detection, wireless sensor network, data buffer, confidence interval, difference

DOI: 10.3233/JIFS-179298

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Zhang, Yueling | Pu, Geguang | Zhang, Min | Y, William

Article Type: Research Article

Abstract: Deep Neural Network is an application of Big Data, and the robustness of Big Data is one of the most important issues. This paper proposes a new approach named PCD for computing adversarial examples for Deep Neural Network (DNN) and increase the robustness of Big Data. In safety-critical applications, adversarial examples are big threats to the reliability of DNNs. PCD generates adversarial examples by generating different coverage of pooling functions using gradient ascent. Among the 2707 input images, PCD generates 672 adversarial examples with L ∞ distances less than 0.3. Comparing to PGD (state-of-art tool …for generating adversarial examples with distances less than 0.3), PCD finds 1.5 times more adversarial examples than PGD (449) does. Show more

Keywords: Deep neural network, robustness, coverage, big data

DOI: 10.3233/JIFS-179295

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Lu, Hsin-Ke | Lin, Peng-Chun | Chu, Kuo-Chung | Chen, Alexander N | Yuan, An

Article Type: Research Article

Abstract: According to the reports of a NGO-World Blind Union in 2017, approximately 253 million people have visual impairment. Besides, the statistics of Taiwan’s Ministry of Health and Welfare also reported that the number keep growing in these two decades. Therefore, how to assist them to have better daily life experiences will be a significant issue. The purposes of this study were designing and constructing a guidance system in order to assist them to know their spatial position and further to guide them to arrive their destination. In this system, the researchers used the integration of smartphone, wearable devices and iBeacon …technique to achieve the purpose of guide. Furthermore, this system allowed caregivers to contact the visually impaired and know their real-time circumstances through the internet in order to enhance their sense of security in unfamiliar indoor environment. For system evaluation, the researchers adopted a SUMI questionnaire suitable for evaluating the usability of the system through users’ feedbacks. According to the research survey, this system can provide the visually impaired with a safer indoor guidance in order to improve their ability and confidence in independent walking. Show more

Keywords: Visual impairment, indoor positioning, beacon, navigation

DOI: 10.3233/JIFS-179301

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Yin, Xiaoqi | Qian, Jiansheng | Guo, Xingge | Fu, Chengfang | Lin, Guohua

Article Type: Research Article

Abstract: Measurement matrix is an important link which has important influence on signal sampling and reconstruction algorithm. Although the traditional random measurement matrix has good effect in reconstruction signal, the hardware implementation is difficult and it requires a lot of storage space. LDPC codes has a sparse check matrix with low density and strong orthogonality. When the RIP conditions are satisfied, the columns and rows are not correlated. In view of the problems existing in the measurement matrix, the deterministic measurement matrix based on the sparsity of photograph LDPC codes is constructed in this paper. Each submatrix is obtained through the …circular shift of other submatrices, which is easy to be implemented on hardware. Experimental results show that the sparse matrix performance of LDPC codes is improved in PSNR and dNMSE compared to the traditional methods by using the same orthogonal matching pursuit (OMP) algorithm for optimization and the same compression ratio. At the same time, it consumes less time in the reconstruction of remote sensing image, and the running speed is greatly improved, which can meet the real-time demand, it also provides an effective measurement matrix construction method for the practical application of compressed sensing theory. Show more

Keywords: Compressed sensing, sparse matrix, LDPC, photograph, orthogonal matching pursuit, wavelet transform

DOI: 10.3233/JIFS-179294

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Li, Yu | Yuan, Kun | Cai, Qian | Yu, Fengyuan | Cai, Chengfeng | Li, Xiaoying | Liu, Pengfeng | Qian, Meiyu | Yu, Juan | Peng, Xiaomei | Chen, Hongguan | Qin, Runtian | Wang, Ziwei | Huang, Nanxi | Liu, Kongling | Cheng, Zhi

Article Type: Research Article

Abstract: People can rely on complex tactile systems to perceive the basic physical properties of an object, and take the corresponding action and pressure to grab the object. However, this task is not easy for mechanical manipulator. The feedback of most manipulators is limited to pressure, it is difficult for manipulators to identify the other properties of the object by touch. A new manipulator method is designed in this paper. The tactile images are reflected by flexible tactile sensor in this manipulator system. A large number of tactile images are used to build training set by which the capsule network is …trained to evaluate images. When an object is captured by a manipulator, and parameters such as shape, rigidity, weight and density of target objects are analyzed. Pseudo color transformation of tactile images is performed, in this way, the changes of each parameter of tactile signals can be observed visibly. It is innovative to process the tactile image by using capsule network and realize the evolutionary bionic tactile function. Show more

Keywords: Capsule network, image processing, bionic manipulator, pseudo color image

DOI: 10.3233/JIFS-179302

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Khan, Asghar | Hadi, Asmat | Ibrar, Muhammad | Jun, Y.B.

Article Type: Research Article

Abstract: Using the notions of a soft set and a fuzzy set, Jun’s introduced a new type of notion called a hybrid structure, which is a generalization of soft set and fuzzy set. In this paper, we apply hybrid structure in hemirings and introduce the concept of hybrid h -ideals of hemirings and the related properties are investigated. Some operational properties of hybrid structures are first investigated. The concepts of a hybrid h -sum and a hybrid h -product are discussed and the related properties are investigated. The notions of hybrid h -ideals, hybrid h -bi-ideals and hybrid h -quasi-ideals are …introduced and several properties are provided. The notion of a hybrid level set is introduced and the basic properties of hybrid h -ideals, hybrid h -bi-ideals and hybrid h -quasi-ideals are studied in detail. The characterizations of h -hemiregular hemirings are discussed and several important results of a h -hemiregular hemirings are provided. Show more

Keywords: Hybrid structure, hybrid structures operations, hybrid h-sum, hybrid h-product, hybrid h-ideals, hybrid h-bi (h-quasi)-ideals, h-Hemiregular hemirings.

DOI: 10.3233/JIFS-171587

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2019

Authors: Athira, T.M. | John, Sunil Jacob | Garg, Harish

Article Type: Research Article

Abstract:  A Pythagorean fuzzy soft set is a parameterized family of Pythagorean fuzzy sets and a generalization of intuitionistic fuzzy soft sets. In this paper, the notions of entropy and distance measures are defined for the Pythagorean fuzzy soft sets (PFSSs). Since, the already existing techniques for finding entropy and distance measures are not working for PFSSs, it is necessary to introduce these techniques in the contest of PFSSs. This work proposes a characterization of the Pythagorean fuzzy soft entropy. Also, the expressions for the standard distance measures like Hamming distance and Euclidean distance are obtained. Further, the applications of PFSSs …in decision making problem and pattern recognition problem are discussed. Finally, comparative studies with other existing equations are also carried out. Show more

Keywords: Pythagorean fuzzy soft sets, fuzzy soft sets, entropy, distance measure, decision making problem, pattern recognition problem

DOI: 10.3233/JIFS-190217

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2019

Authors: Ghosh, Sumonta | Rashmanlou, Hossein | Mofidnakhaei, F. | Pal, Anita

Article Type: Research Article

Abstract:  Apart from other labeling signed product and total signed product labeling already have been applied on different kind of graphs. Signed product cordial labeling for the graph G  = (V , E ), where each vertex is labelled by 1 or -1 and edge label is induced by multiplication of two of it end vertices with the following restriction that the absolute difference between total number of vertices labelled by 1 and -1 is at most 1, similarly for the edges also. Total signed product cordial labeling follows property that absolute difference between total number of vertices and edges labelled by …-1 and total number of vertices and edges labelled by 1 is at most 1. In this paper, we have considered Cartesian product between two balanced bipartite graphs and apply above labeling on it. We have designed some suitable algorithms which will driven by any kind of computer programming language. Illustration with example and complexity of the algorithms are analysed successfully. Show more

Keywords: Cartesian product, Signed product cordial labeling, Total signed product cordial labeling, complete bipartite graph

DOI: 10.3233/JIFS-182746

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Gulistan, Muhammad | Rashid, Sheikh | Jun, Young Bae | Kadry, Seifedine | Khan, Salma

Article Type: Research Article

Abstract:  The generalization of different types of fuzzy sets is on the way since the discovery of fuzzy sets by Zadeh 1965 based on mathematical logic. Some of them are, the interval-valued fuzzy sets, N -fuzzy sets and interval-valued N -fuzzy sets, where N -fuzzy sets are used to the co-domain [−1, 0] for the membership function. Cubic sets are the combination of interval-valued fuzzy sets and fuzzy sets presented in 2012 by Jun et al. Since the cubic sets considered only the positive aspects of a certain thing …in many physical problems and ignore the negative aspects totally. So to cover the negative part the need was felt to extend the concept of cubic sets along the co-domain [−1, 0]. Thus in this paper, we initiate a new theory by mixing the cubic sets with N-fuzzy sets and define the new notion of N -cubic sets. We are inspired by the hybrid nature of the cubic sets which can handle positive characteristics of a certain thing in a much better way as compared to the fuzzy sets. Whereas, our case will be more helpful in order to characterize the negative characteristics of a certain thing in a more affective way as compared to N -fuzzy sets. Motivating from the idea of cubic sets, we initiate to combine the interval-valued N -fuzzy sets and N -fuzzy sets to produce a new class of cubic sets known as N -cubic sets based on mathematical logics. We define N -cubic sets and define many different operations like P-union (resp., P-intersection) R-union (resp., R-intersection) and complement. The notions of external and internal N -cubic sets and related operations and properties are investigated. We discuss some algebraic properties of N -cubic sets and define some aggregation operators which will be helpful in order to find more algebraic and practical applications in the future. At the end we present a N -cubic-decision making Problem by using the developed procedure. Show more

Keywords: N-fuzzy sets, cubic sets, N-cubic sets, aggregation operators, applications

DOI: 10.3233/JIFS-182595

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2019

Authors: Jian, Jie | Zhan, Nian | Su, Jiafu

Article Type: Research Article

Abstract: In the field of engineering economy, engineering investment selection is a common problem, where the preference information is usually intuitionistic and fuzzy. To deal with the consistency and integrity of the information in the selection process, the aim of this article is to extend the superiority and inferiority ranking method and use the interval-valued intuitionistic fuzzy theory, where the individual evaluation values and the weights information of criteria and decision-makers are all described by interval-valued intuitionistic fuzzy numbers. First, some concepts of interval-valued intuitionistic fuzzy set are introduced. Then, the interval-valued intuitionistic fuzzy superiority and inferiority ranking (IVIF-SIR) method is …developed. Moreover, an engineering investment selection model based on IVIF-SIR method is investigated. Finally, an illustration of choosing investment alternatives is used to prove the developed approach and a comparative study is also use to demonstrate the effectiveness. Show more

Keywords: SIR method, multiple criteria group decision making, interval-valued intuitionistic fuzzy Set

DOI: 10.3233/JIFS-190001

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-1, 2019

Authors: Moiduddin, Khaja | Mian, Syed Hammad | Alkhalefah, Hisham | Umer, Usama

Article Type: Research Article

Abstract: A multitude of rapid prototyping (RP) systems and technologies have come up since the introduction of additive process. Owing to the enlarging number of these systems with distinctive efficacy, the problem of selecting an appropriate system for a particular requirement is a cumbersome task. Henceforth, this work comes up with a strategy based on multi-attribute decision making to select a most suitable RP system. The presence of subjectivity in decision making as well as the existence of imprecision from various sources emphasize the methods which must consider uncertainty and vagueness. A decision advisor based on uncertainty theories, including fuzzy analytical …hierarchy process (FAHP) and grey relational analysis (GRA) has been introduced. It provides a comprehensive database comprising thirty nine commercially available RP systems. The evaluation attributes consisting of machine cost, accuracy, layer thickness, machine speed, material cost, net build size volume, machine weight, surface roughness, and material strength were utilized to characterize the different machines. The FAHP based on trapezoidal fuzzy number was implemented to determine the priority weights of various attributes, while the GRA was employed to realize the best RP system and technology. The authors believe that this system has the potential to transform into a fully developed RP selection system. Show more

Keywords: Rapid prototyping, fuzzy analytical hierarchy process, trapezoidal fuzzy number, grey relational analysis, additive manufacturing, sustainability

DOI: 10.3233/JIFS-190128

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-27, 2019

Authors: Jia, Lifen | Ni, Yaodong

Article Type: Research Article

Abstract: Uncertain Differential equations are a type of differential equations driven by the Liu processes rather than the Wiener processes. Depending on the order of differentials it contains, an uncertain differential equation could be classified into first-order uncertain differential equation, second-order uncertain differential equation, third-order uncertain differential equation, and so on. The concepts of stability in various senses for the uncertain differential equations could be specified and applied to the uncertain spring vibration differential equations. However, to the best knowledge of mine, many types of stability have been proposed for first-order uncertain differential equations, for example, stability in mean, stability …in p -th moment, stability in distribution, almost sure stability and exponential stability. However, stability in measure and stability in mean of high-order uncertain differential equations have been proposed. But only the concept of stability in mean and the concept of stability in measure have been proposed for high-order uncertain differential equations. In this paper, following the concept of stability in p -th moment for first-order uncertain differential equations, we present the concept of stability in p -th moment for general uncertain spring vibration differential equations which are a type of second-order uncertain differential equations. Show more

Keywords: Spring vibration equation, stability, uncertain differential equation, uncertain process, uncertainty theory

DOI: 10.3233/JIFS-182864

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Poornappriya, T.S. | Durairaj, M.

Article Type: Research Article

Abstract: The prompt enhancement of Telecom turned to be a vibrant and economical industry, which comprises an intrinsically great perspective for customer churn, requiring exact churn prediction models. In recent times, there has been phenomenal responsiveness in the development of feature selection methods for a large number of datasets. Through this research work, a High Relevancy and Low Redundancy (HRLR) approach by consuming Vague Set (VS) has proposed for selecting the subset of features from the features set. This proposed method is based on the Minimum Redundancy and Maximum Relevancy (MRMR) approach by using Vague Set. The proposed HRLR-VS method is …based on the filtered approach feature selection, where the features are selected only when the measure of feature-class relevancy is maximized and a measure of feature-feature redundancy is minimized. The collaboration of similarity measures and ranking algorithms are prepared by utilizing the vital notions of Vague Sets information energies by Information Gain, Gain Ratio, and Chi-Square methods. The projected approach has been employed with the Particle Swarm Optimization for probing the best feature subset. Further, it measures the efficacy of the projected approach HRHL-VS for telecommunication dataset. The performance metrics like Accuracy, Kappa Statistics, True Positive Rate, Precision, F-Measure, Recall, MAE, RRSE, RMSE and RAE are considered in this paper for evaluating the proposed HRLR-VS method. The proposed HRRL-VS method has compared with existing literature approaches like mRMR and FCBF. From the result obtained in this paper, the proposed HRLR-VS method better results in all aspects for selecting the feature subset in telecommunication dataset. Show more

Keywords: Feature Selection, Vague Set, Information Gain, Gain Ratio, Chi-Square, Particle Swarm Optimization, Euclidean Distance, Cosine Similarity, Pearson’s Correlation Coefficient

DOI: 10.3233/JIFS-190242

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2019

Authors: Duan, Xiongying | Zhang, Fan | Liao, Minfu | Zou, Jiyan | Lv, Yang

Article Type: Research Article

Abstract: Controlled switching strategy can reduce overvoltages due to UHV transmission line closing. However, the traditional method is difficult to determine the quantitative relationship between the closing performance of circuit breakers and the risk of failure of transmission lines. Based on the risk of failure data calculated by the statistical method, an adaptive network-based fuzzy inference system (ANFIS) model for forecasting risk of failure that occurs during the closing of transmission lines is presented. An ANFIS model is employed to map the closing performance of circuit breakers and the risk of failure of the UHV transmission line. The model is based …on a system of fuzzy-rules written on the basis of previous results, the knowledge and experience. The fuzzication of input variables is carried out using fuzzy sets with the Gauss membership functions. “Grid partition” was used to generate the fuzzy inference system, and a hybrid learning rule was used to optimize the fuzzy system parameters. After the appropriate model is established through training and checking, it can forecast the risk of failure in different closing performance of circuit breakers. Then, it is easy to analyze the closing performance of circuit breakers in different risk of failure requirements. Show more

Keywords: ANFIS, closing performance, ultra-high-voltage, controlled switching, risk of failure

DOI: 10.3233/JIFS-179319

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Gan, Haiqing | Zheng, Chuiyong | Cui, Hantao

Article Type: Research Article

Abstract:  In this paper, in the so-called centralized charging and unified distribution mode, a two-stage optimization model is proposed for capacity planning and ordered discharging strategies of centralized charging stations considering the peak-shaving effects. Firstly, the operating states of battery pack are analyzed at each moment by combining with distribution modes, then the first stage planning is processed, that is, by taking the numbers of battery pack and generators as the control variables, the mathematical model aiming at minimizing the construction cost of centralized charging stations can be solved by Simulated Annealing Particle Swarm Optimization (SAPSO). Next, in the second stage …planning, in order to maximize the peaking effect of the centralized charging station, the cost function aiming at minimizing load variance is proposed, and the discharge power of each time can be obtained by using yalmip toolbox. Finally, simulation results are provided to verify the effectiveness and usefulness of the proposed optimization model. Show more

Keywords: Two-stage optimization model, centralized charging station, ordered discharge strategy, SAPSO algorithm

DOI: 10.3233/JIFS-179321

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019

Authors: Ding, Xiaobing | Liu, Zhigang | Hu, Hua | Huang, Yuanchun | Yu, Jie

Article Type: Research Article

Abstract: In this work, we proposed a new systematic metro operation risk identification method (MORIM) and risk grade classification method (RGLM) based on the daily dispatching fault log. We collected and analysed the operation risks during Metro operation, and the database SQL was designed for calculating the probability of risks. Then, we converted the equipment malfunction, train delay, large passenger flow etc. to time delay, so as to realize the quantitative calculation of the risks. We clustered risk sources by data mining, from which, we can get the risk cluster centre, and the emergency response scheme can be accurately made to …match the clustered risks. Finally, the systematic method was validated by a case study. It was found that the method was accurate and the conclusion was reliable. This paper can provide theory and decision support for Metro operation safety management and it has good practical significance for larger cities to dispose the conditions of large passenger flow. Show more

Keywords: Some general terms, some subject-specific terms. there should be no less than 5 and no more than 12 keywords

DOI: 10.3233/JIFS-179284

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2019

Authors: Ji, Jiang-Tao | Yang, Lin-Hui | Jin, Xin | Ma, Hao | Pang, Jing | Huang, Rong-Biao | Du, Meng-Meng

Article Type: Research Article

Abstract: Pot seedling transplanting is the main way of vegetable planting, there were some problems of labor intensity and low level of automation in the process of mechanized transplanting of vegetable pot seedling. Aiming at this problem, this paper designed an intelligent transplanting system for vegetable pot seedling, which included the function of the seeding storage mechanism, the seedling feeding mechanism, the ejecting seedling mechanism, the pinch mechanism and the planting mechanism, the system monitors the whole movement process of planting through pressure sensing, stroke detection and limit switch, obtains each planting stage of the seedlings during planting, and uses the …CCD camera to identify the key steps of planting and seedlings to determine whether it is missing. Three broccoli seedlings with different moisture content and the age of 42d were used as the experimental object of seedlings planting experiment. Results indicated that: Under the conditions of meeting the agronomic requirements of vegetable pot seedlings, when the speed of picking-up seedlings was 75 seedlings per minute, which resulted in a 95% success rate of picking-up seedlings and 5% leaked seedlings rate, the planting effect of vegetable pot seedlings was the best. The research can provide useful reference for the development of intelligent transplanting technology of vegetable pot seedling. Show more

Keywords: Vegetable pot seedling, intelligent transplanting system, PLC control, design

DOI: 10.3233/JIFS-179322

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: Liu, Lindong | Dai, Jingwen | Yang, Junwei | Jin, Miao | Jiang, Wei | Lu, Xingyu

Article Type: Research Article

Abstract: The occupational health and safety problems caused by indoor dust and toxic gases in industrial plants are becoming increasingly serious. Vertical push-pull ventilation can effectively control dust and toxic gases and avoid indoor environmental pollution. The velocity of the air supply hood and exhaust hood in the push-pull ventilation intelligent device directly affects the control effect of the dust and toxic gases. However, no scholar has given a reasonable ratio of the air supply and exhaust velocity of the vertical push-pull ventilation device. Therefore, this paper uses the combination of Fluent numerical simulation technology and smoke visualization experiment to explore …the best ratio of the air supply and exhaust velocity in the push-pull ventilation flow field. The research shows that the traces of the wind flow obtained by numerical analysis under different k which is the ratio of the air supply and exhaust velocity is consistent with the traces of visualized smoke in the actual experiment; The optimal ratio of air supply and exhaust is k  = 1.75, which can effectively guarantee the indoor environment, occupational health and work efficiency of the operators. Show more

Keywords: Dust and toxic gases, push-pull ventilation, ratio of the air supply, exhaust velocity, smoke visualization, intelligent

DOI: 10.3233/JIFS-179318

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Cui, Le | Cheng, Libo | Jiang, Xiaoming | Chen, Zhanfang | Albarka,

Article Type: Research Article

Abstract: Outlier detection has always been a more active research topic in statistical diagnosis. Outliers are ubiquitous at data analysis areas in current and may produce erroneous results. In multivariate linear regression model, the existence of outliers will directly affect the modeling, parameter estimation and prediction. A set of data contains abnormal values, which will have a great impact on the estimation of the mean and standard deviation of the data, and also affect the estimation results of the least squares method. In the paper, on the basis of the linear regression model and deleting model and mean shift model, from …the perspective of residual sum of squares and by introducing sample quantile to estimate the overall parameters robustly, a special statistic which is combined with the sample quantile method is used to detected the outliers. Finally, an example is analyzed and compared with the traditional method. The results show that the method is more effective. Show more

Keywords: Regression analysis, outlier, data deletion model, mean shift model, residual sum of squares, sample quantile

DOI: 10.3233/JIFS-179300

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Xin, Feng | Zhongbin, Li | Manzhang, Tu | Nishan, Chen

Article Type: Research Article

Abstract:  A precise recruitment can improve the efficiency of human resource management and enhance the core competitiveness of enterprises. However, the information asymmetry in recruitment leads enterprises to make recruitment decisions in fuzzy evaluation environments, thus reducing the accuracy of recruitment. This paper applies a robust approach to the recruitment optimization problem in an interval-valued fuzzy evaluation environment in which the actual abilities of applicants are randomly distributed within given intervals. The objective of this paper is to establish a robust recruitment scheme with the minimal maximum regret for recruitment revenue. Both exact and heuristic algorithms are proposed to solve the …problem, which is proven to be NP hard. Computational experiments are conducted to evaluate the performance of the proposed algorithms. In addition, the paper reveals the key factors that affect the ability of an enterprise to implement accurate employment schemes. Corresponding suggestions on enterprise recruitment management are also proposed. Show more

Keywords: Robust optimization, fuzzy evaluation, hill climbing algorithm, information asymmetry, precise use of talent

DOI: 10.3233/JIFS-190152

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-1, 2019

Authors: Fayaz, Muhammad | Ullah, Israr | Shah, Abdul Salam | Kim, DoHyeun

Article Type: Research Article

Abstract: Intelligent optimized energy management and prediction model in electric vehicles received attraction of the researchers in the last couple of years. Several techniques and models have been proposed in the literature for optimized energy management and control, but the trade-off between occupant comfort index and the energy consumption is still a significant challenge to the research community. In this paper, we have proposed a model based on learning to optimization and learning to control for user comfort maximization and efficient energy consumption. The proposed model is comprised of three layers; prediction module, learning to optimization module and learning to control …module. In the prediction module, we have used the Kalman filter for noise removal and prediction of environmental parameters. In learning to optimization module, the bat algorithm has been used for user comfort maximization and energy consumption minimization. Furthermore, we have used the learning module with optimization module in order to tune the user preferences parameters in the comfort index formula used in the bat optimization algorithm. Likewise, the learning module has been used with the conventional fuzzy logic controller in order to improve its performance. In the conventional fuzzy logic controller, the membership functions boundaries are usually determined through hit and trial method, and once the membership functions are determined, they remain fixed for the entire process. In the learning to control module, the membership functions tunnig is carried out. The membership functions are continuously tuned to get effective results. Experimental results indicate that the proposed method performs better as compared to the conventional methods and achieves improved user comfort with reduced energy consumption. Show more

Keywords: Energy optimization, energy consumption, user comfort, bat algorithm, electric vehicles, learning to control

DOI: 10.3233/JIFS-190095

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2019

Authors: Yang, Ming

Article Type: Research Article

Abstract: There are many optional basic frameworks of the Internet of Things, which result in high energy consumption for Internet of Things monitoring platform of straw recycling, and can not improve the thermal energy conversion rate of the straw recycling monitoring system effectively. Thus, the design is based on smart surveillance system of Internet of Things of straw recycling process. The WMNBM14s chip and the STM32F103 chip are used in the basic frame of Internet of Things to collect and process the straw recycling data in the monitoring system, and obtain the data processing result of the straw recycling process. The …data processing result of the straw recycling process is transmitted to Internet of Things Control Terminal through the BCM43362 wireless chip. The experimental results show that the designed platform has low energy consumption and can improve the thermal energy conversion rate of the straw recovery system. Show more

Keywords: Genetic algorithm, straw recycling process, Internet of Things monitoring system, BCM43362

DOI: 10.3233/JIFS-179310

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Wu, Yongfen

Article Type: Research Article

Abstract: This paper reprocesses the information of the boundary intelligent contour so as to effectively extract the codes of image contour features. The algorithm based on the coordinates of contour extracted through the level set evolution algorithm is used to obtain several 2D contour matrixes with the same size after repeated conversions. Moreover, the matrixes are diagonally, column-wise and horizontally coded to obtain new coded features. The anti-interference analysis of algorithm indicates that the algorithm of extracting feature code has variable and flexible extraction schemes and high stability. Distinguishable information can be obtained in similar images more easily. In order to …prove the validity of the proposed algorithm, feature code exaction algorithm is used to facial expression recognition, and a facial expression recognition model on the basis of facial part contour code exaction is established. According to the experimental results, this facial expression recognition system can eliminate the interference with recognition resulted from the similarity of samples. The comprehensive recognition rate of facial expression is up to 97.20% . Show more

Keywords: Image contour, feature extraction, feature code, image recognition, intelligent

DOI: 10.3233/JIFS-179314

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2019

Authors: GU, Quan | LU, Na | LIU, Lin

Article Type: Research Article

Abstract: This paper attempts to apply recurrent neural networks (RNN) to price forecasts and financial trading. Compared with previous neural networks models, the recurrent neural network can better use the previous information to infer subsequent events, which is more suitable for price time series analysis. Long Short-Term Memory (LSTM) has made structural changes to the RNN to avoid long-term dependency problems. The empirical research uses the 2010–2017 price panel data of four kinds of soybean futures in China’s futures market, and confirms the model’s improved predictive ability through statistical tests. The empirical analysis of futures trading verifies the practice of these …model strategies in terms of risked return. This paper improves and expands the application of recurrent neural networks model, and provides a new idea for applying artificial neural network algorithm to futures trading. Show more

Keywords: Deep learning, algorithmic trading, trend trading, commodity futures introduction

DOI: 10.3233/JIFS-179280

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2019

Authors: Jiang, Yu | Zhu, Hua | Ding, Cong | Pfeiffer, Olivia

Article Type: Research Article

Abstract: As the rolling element bearing continues to soar in industry, the requirement for accurate bearing degradation prognostics becomes more and more crucial. A single Fuzzy predictor may suffer from its model parameters optimization. To this end, this paper proposed a new ensemble Fuzzy predictor model for estimating the degradation of a bearing using tribological responses among the rollers and the bearing races. This new method employs the genetic algorithm (GA) to assign an optimal weight vector to a set of adaptive network-based Fuzzy inference system (ANFIS) models. The ensemble of the predicted values of the ANFIS models is used as …the prediction of the bearing degradation. Experimental data acquired from the degradation test of five rolling element bearings was used to evaluate the prediction performance of the proposed method. The analysis result demonstrates that the ensemble ANFIS model enables to improve the prediction accuracy against a single ANFIS one. The contribution of this paper is that the ensemble of the ANFIS models is not addressed in existing research and should be optimized. Show more

Keywords: Fuzzy, ensemble learning, prognostics, machine learning

DOI: 10.3233/JIFS-179277

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2019

Authors: Ji, Wenjiang | Zhu, Lei | Wang, Yichuan | Liu, Zheng | Hei, Xinhong

Article Type: Research Article

Abstract: Vehicular ad hoc networks (VANET) is seen as an effective solution to ensure the driving safety and efficiency. As a key foundation, the road side unit (RSU) connect with each other to form a backbone network in VANET. The authentication of RSUs is the main tasks to prevent the secure communication in VANET suffering from various attacks caused by cunning adversaries. In this paper, we propose a new type of verifiable secret sharing (VSS) scheme based on bivariate polynomial to achieving the RSU authentication in a secret sharing way. Our proposed VSS based authentication includes two phases. In phase 1, …the t RSUs that participate in secret reconstruction collaborate to detect whether there exist illegitimate ones; in phase 2, the t legitimate RSUs reveal their shares for secret reconstruction, and the fake shares can be identified. Our VSS facilitates the RSU authentication since (1) any RSUs participate in secret reconstruction can be confirmed legitimate, (2) any fake shares revealed in secret reconstruction can be identified, (3) a globalized group temporary session key will be established after the VSS process. In addition, our VSS scheme is unconditional secure since the security of our VSS is not based on any computational assumption. Show more

Keywords: Vehicular ad hoc networks, security, RSU authentication, verifiable secret sharing

DOI: 10.3233/JIFS-179286

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2019

Authors: Zhang, Qin | Wilson, Fred

Article Type: Research Article

Abstract: Text classification technology, an important basis for text mining and information retrieval, is mainly to determine the text category according to the text content under a predetermined set of categories. Traditional manual text categorization has gradually failed to meet the needs, while automatic text categorization based on artificial intelligence has become an important research direction in the field of natural language processing. To this end, this paper introduced the RBNN-based classification algorithm by considering the high dimensionality, non-linearity and complex correlation between feature items, and the theoretical and feasibility analysis were carried out so as to apply it to text …feature dimension reduction. Also, the effects of the distribution density of the radial basis function in the radial basis neural network and the normalized form of the input data on the classification results were studied. Through the computer simulation experiment, the influence rule of distribution density of the radial basis function in the radial basis neural network and the normalized form of the input data on the training precision and test accuracy of the classification process were demonstrated in the form of curves, which provides guidance for the application of RBNN in pattern recognition. Show more

Keywords: Application and simulation, radial basis function neural network, big data set classification, RBNN, classification algorithm

DOI: 10.3233/JIFS-179279

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2019

Authors: Wang, Jie | Gao, Hui | Lu, Mao

Article Type: Research Article

Abstract: In this article, we expand the dual generalized weighted BM (DGWBM) and the dual generalized weighted geometric BM (DGWGBM) operator with interval neutrosophic numbers (INNs) to propose the dual generalized interval neutrosophic number BM (DGINNBM) operator, dual generalized interval neutrosophic number WBM (DGINNWBM) operator, dual generalized interval neutrosophic numbers GBM (DGINNGBM) operator and dual generalized interval neutrosophic numbers WGBM (DGINNWGBM) operator, then the MADM methods are proposed with these operators. In the end, we utilize an applicable example for strategic supplier selection to prove the proposed methods.

Keywords: Multiple attribute decision making (MADM), Interval neutrosophic numbers (INNs), dual generalized weighted BM (DGWBM) operator, dual generalized weighted geometric Bonferroni mean (DGWGBM) operator, strategic supplier selection

DOI: 10.3233/JIFS-179235

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2019

Authors: Cao, Yan | Wei, Wanyu | Huang, Liang | Qiao, Hu | Du, Jiang

Article Type: Research Article

Abstract: Uncertain sporadic risks have prominent features such as small probability, difficult to predict, fast diffusion, and complex types, which greatly increase the difficulty of control. Severe incidental risk events often affect the normal operation of the supply chain system, so it is particularly important to respond to risks in a timely and effective manner. Based on fuzzy logic, this paper studies the coping strategies of three-level supply chain systems composed of manufacturers, distribution centers and retailers under uncertain risks. Firstly, fuzzy logic is used to highly quantify fuzzy variables to calculate specific changes caused by the uncertain risks to members …in supply chain, and effectively predict overall changes of the supply chain system; Secondly, the member information is updated in the post-change supply chain system. On this basis, the member maximum loss model is established, the maximum loss amount and the amount of each strategy loss are calculated, and a risk response strategy plan is formulated. Finally, a coping strategy is stored for a quick call when similar risks occur again. The feasibility and effectiveness of the model and method are verified by specific examples and variable sensitivity analysis. Show more

Keywords: Manufacturing supply chain, risk response, maximum loss, decision analysis, fuzzy logic

DOI: 10.3233/JIFS-179287

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2019