Journal of Intelligent & Fuzzy Systems - Volume 37, issue 1

Authors: Uma Maheswari, P. | Manickam, P. | Sathesh Kumar, K. | Maseleno, Andino | Shankar, K.

Article Type: Research Article

Abstract:  Named Data Networking (NDN) is a recent Internet model, takes the advantages and resolves the drawbacks of traditional TCP/IP architecture to satisfy the increasing demands on communication. Every NDN router has a pending interest table (PI) to store all the interest packets (I-pkts) waiting for the arrival of data packets (D-pkts). In case of the arrival of enormous I-pkts, it might be hard for an NDN router to store all I-pkts in the limited PIT space. So, a novel PIT management scheme becomes essential for effective PIT utilization. This paper presents a new PIT sharing algorithm based on the hybridization …of bat optimization (BO) algorithm and fuzzy logic (BFPIT), to accommodate number of I-pkts in a sharing NDN (SN) node. The BFPIT algorithm intends to identify the optimal SN node sharing node to store I-pkts of a requestor NDN (RN) node. The proposed BFPIT algorithm operates in two stages: BO algorithm for preliminary SN (PSN) node selection and fuzzy logic for final SN (FSN) node selection. For validation, the proposed method is implemented, and the simulation results are compared with the k-nearest neighbor (k-NN) algorithm. The experimental results revealed that the BFPIT algorithm significantly increases the CHR and minimizes the average content delivery time. Show more

Keywords: Network, NDN, fuzzy logic, PIT, bat optimization

DOI: 10.3233/JIFS-179086

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 293-300, 2019

Authors: Chen, Zhuolun

Article Type: Research Article

Abstract:  Green building is the development of sustainable development concept in architectural field. While the construction industry has brought great benefits to the development of national economy, its high investment, high pollution and inefficient development mode has also produced a huge energy load. Therefore, from the perspective of environmental and economic sustainability, the development of green buildings is particularly important. In this paper, the author makes economic benefit analysis of green building based on fuzzy logic and bilateral game model. By introducing such factors as economic benefits, cognition and government policies, this paper construct an evolutionary game model, which provides a …basis for improving the economic benefits of green buildings. The results show that the first factor affecting enterprise decision-making is the incremental profit of green building developers, followed by the government’s incentive policy. After the evolution of the market, the final strategic choice will be stabilized to higher economic benefits. Generally speaking, green buildings need to effectively control incremental costs and consider scale benefits. Through management efficiency innovation and policy stimulation, the problems of huge investment cost and long payback period can be solved, so as to improve the economic benefits of green building development. Show more

Keywords: Green building, game theory, incentive mechanism, benefit analysis

DOI: 10.3233/JIFS-179087

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 301-313, 2019

Authors: Chen, Yunfei | Du, Taihang | Sun, Shuguang | Jiang, Chundong

Article Type: Research Article

Abstract: In view of the high price of receivers in indoor radio interference sources, a double fingerprint database acquisition and location system based on wireless sensor networks is designed according to the design aim of low input and high efficiency. To meet the demand of the number of at least AP positioning in the positioning area, the main library collection in the overall positioning of fingerprint point and signal intensity, using the improved fuzzy C clustering (Fuzzy C Means, FCM) algorithm and support vector machine (Sport Vector Machine, SVM) location of interference source location and area, area after the parade AP …moving to the main fingerprint lock, before relying on offline collected local fingerprint information database, according to the Euclidean distance model of the objective function, the positioning process into local optimization and application of genetic algorithm (Genetic Algorithms GA) and Particle Swarm (Particle Swarm Optimization, PSO GA-PSO) algorithm to calculate model the optimal solution, converting the location coordinates of the interference source. The experimental results show that the confidence level of the non-sight distance positioning accuracy of 1.3m obtained at least AP is 76.3%, and the method used in the study is of high practical value. Show more

Keywords: Indoor positioning, clustering method, simulated annealing simplex fusion algorithm, GA-PSO fusion algorithm, cruise AP signal receiver

DOI: 10.3233/JIFS-179088

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 315-327, 2019

Authors: Feng, Hui | Yin, Xinghui | Xu, Lizhong | Lv, Guofang | Li, Qi | Wang, Lulu

Article Type: Research Article

Abstract:  In this paper, we propose an underwater object detection method, which uses improved spectral residual (SR) saliency detection and fuzzy segmentation. We adopt a two-phase mechanism, which divides visual object detection into detecting saliency map and image segmentation to obtain “proto object”. We compare the logarithmic spectrum differences between optical images in the atmosphere and in the water. Combining with the absorption characteristics of the propagation of light in water, we use the logarithmic spectrum of underwater images and logarithmic spectrums in R, G and B channels to generate new logarithmic spectrum, so as to highlight more object information and …obtain better saliency map. Then, using Fuzzy c-Means (FCM) clustering method to segment saliency map, we gather better similar information of the object and highlight the entire body of the objects. We tested the effectiveness of our method in underwater object detection in different underwater optical environments. The results show that our method can eliminate most of the background noise and improve the accuracy of underwater visual object detection. Show more

Keywords: Underwater object detection, saliency detection, spectral residual, Fuzzy c-Means, logarithmic spectrum

DOI: 10.3233/JIFS-179089

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 329-339, 2019

Authors: Yin, Qiang | Hu, Jiabing | Tong, Hangming | Song, Shaoyun | Zhang, Guoquan

Article Type: Research Article

Abstract: Due to the continuous improvement of industrial production requirements and green manufacturing demand, manufacturing enterprises and factories need to constantly optimize and improve the system structure. Based on the actual problems in the actual coal blending process, this paper analyzes the reason of the coal blending error in coal blending process and the optimization scheme of intelligent control of coal blending process. We optimized the overall structure of the coal blending system, improved the coal blending system which use the fuzzy control system. At the same time, we used MATLAB to simulate and analyse the simulation results. This paper gives …an illustration to the optimal structure and system of the coal blending system, effectively improves the accuracy and stability of the coal blending process control system, reduces the coal blending error and improves the quality of coal blending in general. Show more

Keywords: Green manufacturing, PID, intelligent control, fuzzy self-tuning, coal blending

DOI: 10.3233/JIFS-179090

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 341-349, 2019

Authors: Li, Ke | Zhang, Jinyi | Lei, Yingke | Ra, Cyn

Article Type: Research Article

Abstract: In the complex and changeable war environment, how to intercept the enemy’s communication signals and study the source individual fingerprint identification to obtain the information of the other party’s communication equipment and weapon system is an important basis for understanding the enemy. Due to the subtle differences in hardware between each communication device, there are individual characteristics that differ from other devices. Fingerprint identification of communication radiation source, by studying the individual characteristics carried in the communication signal, can identify which communication equipment is coming from. Tracing the communication equipment, an important basis is provided for determining the communication system …composition and strategic intention of the other party, and for the development of our action plan, which has important strategic significance in the field of communication confrontation. Based on this, this paper studies the bispectrum feature extraction method of communication emitter signal, constructs a classifier of communication emitter, and verifies the superiority of rectangular integral bispectrum method through experiments. The classifier is trained by using reduced dimension bispectrum feature vector of signal. Show more

Keywords: Communication radiation source, fingerprint, extraction method

DOI: 10.3233/JIFS-179091

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 351-359, 2019

Authors: Shen, Jie | Chen, He | Xu, Mengxi | Wang, Chao | Liu, Hui

Article Type: Research Article

Abstract: The conventional JSEG algorithm has a powerful detection capability on the homogeneity of regional texture features because it combines the spectral information with image texture features during the segmentation. However, the conventional JSEG method is not very accurate for the target edge localization in segmentation results. To solve this problem, this paper proposes an improved segmentation method of remotely sensed image based on JSEG algorithm and fuzzy c-means (FCM) with spatial constraints. Firstly, the FCM clustering method based on spatial neighborhood terms is used to replace the traditional HCM clustering method in the quantization step. Then the region growing method …is applied to segment the class diagram after FCM clustering. Finally, the proposed method uses the improved regional merger approach to merger the over divided region after segmentation. According to the J index, the proposed algorithm is improved by 31% and 12% compared with the traditional JSEG segmentation method and improved by 17% and 8% compared with the FNEA segmentation algorithm for aerial image and the SPOT 5 image. The experimental results show that the proposed segmentation algorithm has good noise immunity because of the fuzzy clustering of spatial constraints and can extract the edge of the target more accurately. Show more

Keywords: Remote sensing, image segmentation, J value segmentation (JSEG), fuzzy c-means (FCM), regional consolidation

DOI: 10.3233/JIFS-179092

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 361-370, 2019

Authors: Liu, Lizheng | Liu, Fangai | Ky, Byron

Article Type: Research Article

Abstract: Due to the increased development and applications of satellite communication, GPS equipment, video tracking and other communication technologies, the trajectory prediction of various SIs can be accurately predicted and tracked. Based on these technologies, mobile targets are extensively used in many applications. A large amount of trajectory data predicted by trajectory can be collected from the positioning terminal of the moving target by the signal-receiving device. This paper analyzes the application of computer technology in trajectory prediction of moving objects in data mining algorithm and proposes a trajectory analysis method based on structure and cloud computing motion capture algorithm. The …motion and trajectory characteristics of moving target trajectories are analyzed from microcosmic angle. By comparing the structural features of the extracted trajectory and the trajectory predicted by the trajectory of the moving object, the motion characteristics of the object can be analyzed more comprehensively. In addition, the sensitivity of the trajectory structure can be flexibly adjusted by setting the weight of the trajectory structure, so that the trajectory of the moving target can be analyzed and predicted in an effective and flexible way. Show more

Keywords: Data mining algorithm, moving target trajectory, prediction, computer technology, application

DOI: 10.3233/JIFS-179093

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 371-379, 2019

Authors: Gu, Yanhui | Zhu, Shuzhen | Yang, Zhiping | Zhao, Yuanjun

Article Type: Research Article

Abstract: In this paper we suggest a new approach to assessment of banking systemic risk contagion. Rather than the static analysis method, we introduce a dynamic analysis method to simulate the contagion of banking systemic risk. Banking systemic risk contagion is similar to the spread of infectious disease. In this paper, analysis is made on the process of banking systemic risk contagion by means of Matlab simulation based on network dynamic time-variant contagion kinetics model. The conclusion shows that high banking risk contagion rate, low risk immunization rate or low risk isolation protection rate all are the basic reasons for that …the “risk contagion reproductive rate” reaches the threshold value to make banking systemic risk contagion uncontrollable, and it is suggested to ensure banking system safety by taking measures from the three aspects pointed out above and combining with prudential supervision policies. Show more

Keywords: Network dynamic time-varying, contagion kinetics model, banking systemic risk contagion, risk contagion rate, risk immunization rate, risk isolation protection rate

DOI: 10.3233/JIFS-179094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 381-395, 2019

Authors: Sheng, Pengcheng | Ma, Jingang | Wang, Dapeng | Wang, Wenyang | Elhoseny, M.

Article Type: Research Article

Abstract: Specific to the trajectory planning of intelligent electric vehicles with multi-constraints in some unknown environment, using rolling optimization principle of predictive model control for reference, an online trajectory planning algorithm based on a rolling window is proposed. Making full use of the local environmental information measured in real-time by intelligent electric vehicle, the path of continuous curvature is generated in the planning window by the Quintic Bézier curve and is optimized by the sequential quadratic planning algorithm. Furthermore, the optimal speed sequence for a given path is planed using the S-shaped curve velocity algorithm. Combining with the actual application scenario …of an intelligent electric vehicle, the algorithm is simulated, and the trajectory planning experiment is carried out based on the actual environmental data. The results show that a safe trajectory with continuous curvature and optimal speed can be produced by using this algorithm in some unknown environment scenarios. Show more

Keywords: Intelligent electric vehicle, rolling window, trajectory planning, quintic bézier curve, s-shaped curve

DOI: 10.3233/JIFS-179095

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 397-407, 2019

Authors: Huang, He | Deng, Haojiang | Sheng, Yiqiang | Ye, Xiaozhou

Article Type: Research Article

Abstract:  Deep learning methods have been widely used in today’s network security systems for their outperforming in detecting rates of the patterns of anomalous network actions. Particularly, in the field of malware traffic classification, time reduction for a detecting process is of great importance and can stop network damage at an early stage. To achieve a balance between the detection rate and time consumption, practical structures of relative systems are usually simple, complicating the application of appropriate accelerating methods. In this study, we propose a novel ant-colony -based clustering algorithm, which can efficiently select the most valuable data points for the …next step of learning. In addition, to take advantage of the widely-used convolutional neural network architecture, we defined the mapping-image of each raw traffic data, and then transformed the intrusion detection problem into an image recognition problem. Before each training iteration, we applied the clustering algorithm to locate the most-featured part of each specific type of network traffic. Next, we utilized this featured part in the training, by considering its depth and shallow information, so that its precision and robustness can be improved. Preliminary experiments demonstrate that our method not only achieves high-detection-rate results but also manages to utilize much less processing time with proper parameter tuning of the neural networks. Show more

Keywords: Deep learning, convolutional neural network, intrusion detection system, network anomaly detection, heuristic clustering

DOI: 10.3233/JIFS-179096

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 409-423, 2019

Authors: Yang, Xiaodong | Lin, Xiaoxia | Lin, Xiaole

Article Type: Research Article

Abstract: With the continuous development of internet and information technology, human beings need to process a lot of information and data. When processing a large amount of information, data mining technology must be used. In order to better mine the required data information quickly based on condition matching, an optimized Apriori and FP - Growth association rule mining algorithm is proposed. Based on the algorithm flow and evaluation model, an optimization and up-date scheme is proposed, an effective data transmission evaluation model is established by effectively evaluating the state of data analysis, and the corresponding evaluation results are given. By introducing …the idea of improved decomposition database to reduce the collection of infrequent databases, the algorithm adaptability is improved. In order to verify the feasibility and reliability of the method, the case experiment is demonstrated. Based on the experimental results, the algorithm is more effective in actual operation efficiency and data mining precision. Show more

Keywords: Apriori algorithm, FP-Growth algorithm, data minin

DOI: 10.3233/JIFS-179097

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 425-432, 2019

Authors: Gang, Wang

Article Type: Research Article

Abstract: Under the tide of artificial intelligence, automobile, the most commonly used means of transportation, is about to enter a new era of automation and driverless driving. Road testing of driverless cars designed by many companies in China and other countries has begun and is imminent. However, there is still a gap in the study of the legal adaptation of driverless vehicles, especially the existing road traffic safety laws for driverless enterprises. To promote the rapid application of new technology of driverless vehicles, this paper considers the influence of people, vehicles, roads and traffic management on driverless vehicles, and constructs a …highway safety evaluation model based on support vector machine. In 2003, the model parameters were optimized to reduce the possible criminal dilemma of driverless vehicles. The simulation results show that the research has good theoretical value and practical space. Show more

Keywords: Intelligent algorithm, driverless vehicle, criminal law, research

DOI: 10.3233/JIFS-179098

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 433-440, 2019

Authors: Xueying, Tian | Panke, Nie

Article Type: Research Article

Abstract: This article has been retracted, and the online PDF has been watermarked “RETRACTED”. A retraction notice is available at https://doi.org/10.3233/JIFS-219218 .

DOI: 10.3233/JIFS-179099

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 441-454, 2019

Authors: Wang, Rui | Yang, Shuchen | Wang, Dongxue

Article Type: Research Article

Abstract: Active vibration control is a new subject developed in the last twenty years. It mainly studies the theory, method and measure of active vibration control of structures. After introducing the linear quadratic optimal control algorithm, the numerical simulation of the linear quadratic optimal control for a piezoelectric flexible cantilever beam is carried out. The model of the flexible cantilever beam is established firstly, including the differential equation of motion, the moment equation of the actuator and the output equation of the sensor. Then the optimal feedback gain matrix of the system is obtained by using the linear quadratic optimal control. …In this paper, genetic algorithm is used to optimize the above parameters of BP neural network, and the improved BP neural network is applied to the study of nonlinear model of dynamic coal blending. A method based on piezoelectric self-sensing method is proposed as a test method. A piezoelectric wafer of piezoelectric bimorph is used as the sensing element, analyzing the relationship between the acceleration parameters of the piezoelectric bimorph and the induced charge generated by the sensing element, and a test circuit device for driving force is designed. The method uses genetic algorithm to calculate the control force online and uses the neural network to simulate the dynamic characteristics of the plate, thus replacing the cantilever plate for dynamic analysis. The system fully utilizes the characteristics of genetic algorithms and neural networks and is a new type of vibration control system with promising future. Show more

Keywords: Piezoelectric intelligent structure, neural network, driving force

DOI: 10.3233/JIFS-179100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 455-465, 2019

Authors: Yu, Wang | Huafeng, Wang

Article Type: Research Article

Abstract: Macroeconomics is a very complex and huge system. With the improvement of China’s market economy, it is of great theoretical significance and practical value to apply quantitative economics methods and models to study the macroeconomic state and forecast the economic development trend. The development of regional economy is restricted by natural conditions and social and humanistic conditions, and it is a complex system with many factors and levels. By using grey system theory, data processing can reduce its randomness and strengthen the inherent trend of data, so it is possible to use as few data as possible to establish a …model describing economic system. Through empirical test, the author analyses the main factors of unbalanced regional economic development and puts forward the comparative advantages of regional development. According to the simulation results, the predicted results are stable and reliable. The conclusion of the study has a certain reference value for the formulation of macroeconomic policies. By strengthening the guidance of government classification, the regional economic disparity will be narrowed continuously. Show more

Keywords: Grey relevance, complex set, economic indicators, empirical test

DOI: 10.3233/JIFS-179101

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 467-480, 2019

Authors: Wang, Hongli | Islam, Kamrul

Article Type: Research Article

Abstract: Tracking audit of poverty alleviation policy is an important guarantee to win the battle against poverty. Effective prevention and control of audit risk in tracking audit of poverty alleviation policy is the key to ensure the improvement of audit quality. According to the characteristics of financial audit, this paper analyzes the main factors affecting the operation of loan enterprises, puts forward a neural network model for financial audit, and gives the solution of the model. This paper takes poverty alleviation audit as an example, centering on the goal of full coverage of the audit, and based on poverty alleviation data, …integrating relevant data in relevant fields to build poverty alleviation fund audit, so as to achieve full coverage of poverty alleviation audit. Utilize emerging technologies, give full play to the role of full coverage of audit supervision and supervision on precision poverty alleviation, and participate in project consulting and auditing in advance, real-time online tracking audit, and post-performance performance evaluation audit. We will promote the construction of accurate poverty alleviation information, strengthen economic responsibility audits, and more effectively monitor the authenticity of poverty alleviation funds, effectively implement poverty alleviation projects, and achieve accurate poverty alleviation efficiently. The model can better help the auditors to accurately determine the basic status of the audit object and provide a strong guarantee for quickly determining the audit focus. Show more

Keywords: BP neural network, poverty alleviation funds, audit mode

DOI: 10.3233/JIFS-179102

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 481-491, 2019

Authors: Liu, Xin | Zhou, Yanju | Wang, Zongrun

Article Type: Research Article

Abstract: For the acquisition of user behavior preference in social network, usually a data mining will be conducted on the nearest neighborhood users or latestprojects based on the user’s historical behavior data, so as to find similar behaviorrelationship for quantitative analysis; it can also focus on the awareness on the user-related context information based on cognitive psychology, so as to find its internal links forthe potential mining. However, these methods ignore the intrinsic link between the browsing behavior and the preferred topics in the user link connection, resulting in the limited precision and accuracy of the preference acquisition. Inspired by the …theory of complex network link prediction and the topic model, anacquisition method for users’ browsing behavior preference was proposed in this paper. In the multi-dimensional network link environment, by measuring the importance of the node via network centrality and search the social network link via setting the similarity threshold, the real-time multi-link information and the big data about users’ browsing under each link were acquired, then the data were filteredand cleaned by using adjustable parameters. On this basis, according to the least squares criterion the data underwent a fusion and were used to construct a data node distribution model for user browsing behavior, then the frequent feature items of user browsing behavior preference were extracted. Based on the extracted feature terms, the variational Bayes approximation reasoning method was used to construct the preference topic model. Finally, the hierarchical VSM model representation method was used to establish the preference acquisition model of user browsing behavior, and the model was updated in real time by user feedback processing mechanism. The experimental results on the real data set showed that the link search method and the preference topic model provided by this paper are accurate and efficient. Compared with the classical cooperative filtering method and the context-awareness method, the precision, accuracy and effectiveness of the preference acquisition model provided this paper are significantly improved, and its adaptability has been significantly strengthened. Show more

Keywords: Social network link, topic model, user browsing behavior, preference acquisition

DOI: 10.3233/JIFS-179103

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 493-508, 2019

Authors: Ji, Linzhang | Cheng, Daolai | Yi, Chuijie | Zick, Sandra

Article Type: Research Article

Abstract: At present, the CAAC has established the only “Aircraft Cabin Sound Information Sample Library” in China, which provides strong support for the theoretical analysis method based on the CVR non-discourse sound blind source separation. The separation of aircraft background acoustic blindness based on EEMD-ICA is studied. The performance of different algorithms for the separation of CVR non-discourse background acoustic typical observation signals is compared, and an incompletely constrained adaptive natural gradient algorithm is found for signals that change drastically over time and have a near-zero amplitude over a more extended period. In addition, when there is redundant information or noise …on the CVR background acoustic signal, an independent component analysis method is used to reduce the dimensionality of the observed signal, which is essential for extracting valuable information from confounded signals and provides a reference for dealing with changing mixed signals. Show more

Keywords: EEMD-ICA, aircraft, Background acoustic blind separation

DOI: 10.3233/JIFS-179104

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 509-516, 2019

Authors: Han, Kaiyan | Liu, Xiaoping | Ping, Shao-kang | Wang, Ping

Article Type: Research Article

Abstract:  The research is carried out the kinematics analysis of combined technical actions in hip-hop movements by the methods of three-dimensional analysis of motion biomechanics. Based on three aspects of the movement track, motion characteristics and core technical action analysis, the results show that: the facet joint play the role of driving action; The movement can be changed by changing the direction of the force when connected; And the body should be reduced the buffer in the way the fingertips or toes touching the ground first when doing actions.

Keywords: Hip-hop movement, bio-mechanics, three-dimensional analysis, fuzzy system

DOI: 10.3233/JIFS-179105

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 517-525, 2019

Authors: Jing, Yun | Guo, Siye | Zhang, Zhenhua | Jeng, Embrima

Article Type: Research Article

Abstract:  The propose of this paper is building the flow shop model with full-loaded constraints and maximum wagons within the stage. Based on sequence theory, technical operations of marshalling station are described as process of flow shop. By definition of key trains, the adjustment of the classification schedule of inbound trains is attributed to the adjustment of key trains for reducing invalid solution. Based on the LS rules to construct an initial solution, tabu search algorithm (TS) dynamically adjusts taboo step, and build a network model of static wagon-flow allocation for the objective function, to ensure the feasibility of solutions. Finally, …the example demonstrates the effectiveness of the algorithm, and differences between full-loaded and full-cars constrains. Show more

Keywords: Marshaling station, wagon-flow allocating, sequence theory, taboo search, full-loaded

DOI: 10.3233/JIFS-179106

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 527-536, 2019

Authors: Hou, Jing | Meng, Jianfeng | Zhu, Lianmei

Article Type: Research Article

Abstract: Support vector machine need to choose kernel function according to data distribution characteristics, while iterative algorithm of function parameter optimization can effectively improve the validity of data analysis. Using a sample of A-share listed firms in China from 2007–2017, this paper discusses the impact of corporate innovation on stock price crash risk and the moderating effect of investors’ attention on the relationship between the two under the triple effect of enhancing confidence, interpreting information and releasing panic. The results show that: (1) the innovation output is negatively correlated with the stock price crash risk, and the inhibition of substantive innovation …is more significant than that of strategic innovation; Investors’ focus mainly has the effect of enhancing investor confidence, thus strengthening the negative correlation between the two. (2) R&D is positively correlated with the stock price crash risk. Investors’ focus helps to alleviate the information asymmetry and play the effect of information interpretation, thus weakening the positive correlation between the two; (3) the capitalization of development expenses in R&D has not really promoted the enterprise value but has become a means for insider to reduce their holdings and cash. The stock price crash risk is aggravated by the widespread sell-off caused by panic reaction of investors. The research in this paper has certain theoretical and practical significance to improve the substantial innovation of corporates, restrain insider trading behavior, protect the interests of investors and then maintain the stable development of capital market. Show more

Keywords: Fuzzy mathematics, stock price crash risk, corporate innovation, investor focus

DOI: 10.3233/JIFS-179107

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 537-549, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 551-551, 2019

Authors: Rahman, Atta

Article Type: Research Article

Abstract: In this research, a novel block-based, integer wavelet transform (IWT) domain digital image watermarking scheme for optimum information embedding using a Fuzzy Rule Based System (FRBS) is proposed. There are three famous conflicting parameters in digital image watermarking, namely, robustness, imperceptibility and payload are linked with each other and a change in one parameter affects others and vice versa. That’s why it is hard to optimize them, jointly because of the inherent non-linearity and in the literature, any pair of parameters is optimized while third is assumed as fixed. In this proposal, this non-linear problem is solved using FRBS by …using the logical relationship among three parameters and it consequently suggests the image from the image-bank that may convey the desired payload (capacity) with maximum imperceptibility and robustness. The proposed FRBS is two-fold. Firstly, selection of candidate image blocks from the given image and secondly selection of the candidate coefficients from the already chosen blocks for embedding the desired payload. Images having coefficients greater than a certain threshold are chosen and the payload is embedded. Consequently, the watermarked images are passed through various attacks and the image with maximum robustness is selected. The effectiveness of the proposed scheme is demonstrated through MATLAB simulations and comparison with state-of-the-art techniques. Show more

Keywords: Digital image watermarking, IWT, optimum embedding, PSNR, block-based

DOI: 10.3233/JIFS-162405

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 553-564, 2019

Authors: Pakhira, Nilesh | Maiti, Manas Kumar | Maiti, Manoranjan

Article Type: Research Article

Abstract: Here two-level supply chain model is considered for a deteriorating item where the retailer’s warehouse in the market place has a limited capacity. Therefore the retailer can rent a warehouse (RW) if needed with a higher cost compared to own warehouse (OW). This model includes one wholesaler and one retailer and our aim is to maximize the total profit. The demand rate in retailer is stock-dependent and in case of any shortages, the demand is partially backlogged. Retailer also introduces some promotional cost to boost the base demand of the item. It is established that if the wholesaler shares a …part of promotional cost then channel profit as well as individual profit increase. The supply chain model is also considered for imprecise environment when different inventory parameters are fuzzy/rough in nature. In this case individual profits as well as channel profit become fuzzy/rough in nature. As optimization of fuzzy/rough objective is not well defined, following credibility/trust measure of fuzzy/rough event, an approach is proposed for comparison of fuzzy/rough objectives and a Particle Swarm Optimization (PSO) algorithm is used to find marketing decisions. Models are illustrated with numerical examples. Show more

Keywords: Deterioration, Two-warehouse model, Promotional Cost, Credibility/Trust measure, Particle Swarm Optimization

DOI: 10.3233/JIFS-16913

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 565-581, 2019

Authors: Fahmi, A. | Amin, F. | Abdullah, S. | Aslam, M. | Ul Amin, N.

Article Type: Research Article

Abstract:  This paper presents a new concept of trapezoidal cubic fuzzy numbers and solves the plant location selection (PLS) problem based on a new decision method with cubic fuzzy information captured through trapezoidal cubic fuzzy numbers. In the decision process, the unknown weights of the criteria are unearthed by using the Shannon entropy theory and the weights of the decision makers by integrating the Evidence theory with Bayes approximation. Based on trapezoidal cubic fuzzy numbers, we extend the classical VIKOR method to solve the MAGDM problems under cubic fuzzy environment based on the TrCFNs on proposed method.

Keywords: The definition and arithmetical operations of trapezoidal cubic fuzzy numbers, A MAGDM approach based on an extended VIKOR method using trapezoidal cubic fuzzy numbers, The extended VIKOR method using trapezoidal cubic fuzzy numbers, plant location selection, shannon entropy

DOI: 10.3233/JIFS-171049

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 583-596, 2019

Authors: Hassan, Sabo Miya | Ibrahim, Rosdiazli | Saad, Nordin | Asirvadam, Vijanth Sagayan | Bingi, Kishore

Article Type: Research Article

Abstract: The accelerated particle swarm optimisation (APSO) is an improved variant of the PSO algorithm that guarantees convergence through the use of only global best to update both velocity and position of particles. However, like its predecessor, the APSO is also prone to being trapped in local minima. Therefore, this paper proposes two hybrid algorithms synergizing the social ability of the APSO and the exploitative ability of both spiral dynamic algorithm (SDA) and Adaptive SDA (ASDA). The exploration phase of the proposed algorithms APSO-SDA and APSO-ASDA, will be achieved through the APSO algorithm. The exploration phase solutions of the APSO are …then fed to the SDA and ASDA to achieve the exploitation phase. The proposed algorithms have been evaluated with benchmark function and have also been used to tune a filtered predictive proportional-integral (FPPI) controller for WirelessHART networked control systems (WHNCS). The results obtained from Friedman’s rank test show that the proposed APSO-SDA and APSO-ASDA outperformed their constituent algorithms. Time domain analysis of the FPPI controller also show that the APSO-SDA and APSO-ASDA outperformed the APSO, SDA and ASDA in terms of settling times and overshoot. Show more

Keywords: Accelerated PSO, Hybrid optimisation algorithm, predictive PI controller, spiral dynamic algorithm, WirelessHART

DOI: 10.3233/JIFS-171288

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 597-610, 2019

Authors: Shirazi, Abdoreza Noori | Mozaffari, Babak | Soleymani, Soodabeh

Article Type: Research Article

Abstract:  In recent years, because of the regeneration and development of power systems many of their technical and economical characteristics have been changed in different sections of generation, transmission, distribution and consumption. This issue has great impact on transmission systems because of the increased demand and limitation in creation of new lines. System stability against disturbances of big signal is one of the important issues that have been under threat as a result of this issue. In such circumstances, FACTS devices have great impact on increase of control ability and power system stability. One of the most effective FACTS devices is …generalized unified power flow controller (GUPFC). It can combine the capabilities of SSSC, STATCOM and TCPAR by control of different parameters of network and can be used as a multipurpose tool. In this essay, designing a neuro-fuzzy controller for GUPFC to improve transient stability has been investigated. For this purposed, a controllable compensator has been designed to increase transient stability margin and damp transient oscillation in such systems by use of lyapunov stability criterion. Since transient energy function of system is a suitable tool for investigating of stability issue, optimization of GUPFC energy function has been noticed in order to reach the highest margin of transient stability. This idea is the basis of producing required teaching information in ANFIS network and can be used as a GUPFC controller. In this essay, the impact of GUPFC on single machine system, infinite bus (SMIB) and 9-bus system (Anderson and Fouad, 1977) by use of supposed method has been studied. Moreover by simulation of other FACTS devices such as UPFC and IPFC, the priority of GUPFC has been shown and the comparison of its result has been proved. Show more

Keywords: Generalized unified power flow controller (GUPFC), transient stability, lyapunov energy function, critical cleaning time (CCT), neuro-fuzzy control

DOI: 10.3233/JIFS-171488

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 611-623, 2019

Authors: Cai, Nannan | Li, Shugang | Yu, Zhaoxu | Shi, Miaojing

Article Type: Research Article

Abstract: Selecting thepotential brand spokesperson on social network (SN), who has the huge growth potential and will own the largest number of fans in the future, can providehigher returns at lessrisks. In this study, smart link prediction algorithm (SLPA) is proposed to predict the evolvements of SNs and the brand spokesperson with the great future potential is selected based on the prediction results of SN evolution. In SLPA, mean roughness classification uniformity (MRCU) is developed to select the high efficient link prediction algorithm (LPA) for node pairs to be predicted from the local similarity based and quasi-local similarity based LPAs. MRCU …uses the rough set theory and granular computing to describe the similarity of LPAs, consequently the LPA selected with MRCU can share as much similarity as possible with the other base LPAs. Furthermore, SLPA adopts the branch and bound method to smartly cluster node pairs by adaptively selecting optimal LPA for given node pairs and excluding the ones with the least possibility of linking, and consequently the most reliable results of node pairs with the highest linkable possibility are acquired. The experimental results on three SN datasets confirm the validity of SLPA in selecting band spokesperson. Show more

Keywords: Brand spokesperson, rough set, link prediction, branch and bound

DOI: 10.3233/JIFS-171802

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 625-634, 2019

Authors: Chen, G. Y. | Xie, W. F.

Article Type: Research Article

Abstract: Hyperspectral imaging provides new opportunities for improving face recognition accuracy. However, it poses such challenges as difficulty in data acquisition, low signal to noise ratio (SNR), and high dimensionality. In this paper, we propose a novel method for hyperspectral face recognition with good recognition rates. We first reduce noise adaptively from each spectral band and then crop each face. We perform minimum noise fraction (MNF) transform to the cropped face data cube in order to extract a number of MNF bands. We extract histogram of oriented gradients (HOG) features from each MNF band. We conducted some experiments to test this …new method for hyperspectral face recognition with very promising results. For Hong Kong Polytechnic University Hyperspectral Face Database (PolyU-HSFD), we achieved an average correct recognition rate of 95.4% with standard deviation of 2.6 (95.4% ±2.6). For CMU Hyperspectral Face Database (CMU-HSFD), we achieved an average correct recognition rate of 98.1% with standard deviation of 0.8 (98.1% ±0.8). The reasons why we choose MNF for hyperspectral face recognition are because it can separate noise from fine features in the face data cube and at the same time reduce the dimensionality of the face data cube. In this way, our proposed face recognition method will be faster than those methods without dimensionality reduction. Show more

Keywords: Hyperspectral face recognition, minimum noise fraction (MNF), histogram of oriented gradients (HOG)

DOI: 10.3233/JIFS-17283

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 635-643, 2019

Authors: Layegh Rafat, Mahmood | Shabakhty, Naser | Bahrpeyma, Abdolhamid

Article Type: Research Article

Abstract: Reliability-based dome optimization (RBDO) is one of the most robust methods nowadays, which has made it possible to achieve a high degree of safety and optimum structural design at the same time. The purpose of optimization, based on the reliability of space domes, is to find the best set of sections of the structural members, which leads to the minimum structural weight, incorporating the probabilistic constrains. In the contest of reliability or probabilistic constrain, the applied loads, the module of elasticity, and the cross-sections of the members are considered as random variables with the specified probability distributions. The particle swarm …method (PSO) is used as optimization algorithm because it is a simple and robust method in the case of nonlinear objective functions. In order to investigate the effect of probabilistic constraints selections based on three displacement, stress, and combination of displacement and stress, three space domes with different height to span ratios are considered in this research. The results indicate the optimal structural weight of space domes vary with changes the height-to-span ratio and type of the constraint model selections. Therefore, in order to obtain the optimum space domes in regards to the structural weight, incorporation of both probabilistic constraints of combined stress and displacement is essential in design step. Show more

Keywords: Space domes, particle swarm method, reliability index, probabilistic constraints, reliability-based optimization

DOI: 10.3233/JIFS-18034

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 645-655, 2019

Authors: Chu, Chun-Hsiao | Lin, Scott Shu-Cheng | Julian, Peterson

Article Type: Research Article

Abstract:  Xu (2017) published a paper in Journal of Intelligent and Fuzzy Systems in which he constructs a new distance measure that not only satisfies the axiom of intuitionistic fuzzy sets, but also fulfills the axiom for traditional distance. However, several questionable results arise in Xu (2017). Thus, the purpose of this paper is threefold. First, his proof is improved. Second, his criticism for two previously published distance measures are amended. Third, it is shown that in his numerical examples, there are several poorly-founded discussions. The refinement will help readers understand Xu (2017) and then apply his new distance measure to …pattern recognition problems and medical diagnosis problems. Show more

Keywords: Distance measure, similarity measure, intuitionistic fuzzy sets

DOI: 10.3233/JIFS-181003

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 657-667, 2019

Authors: Li, Yongkun | Shen, Shiping

Article Type: Research Article

Abstract: In this paper, a class of quaternion-valued BAM neural networks with time-varying delays on time scales is proposed. Based on inequality analysis techniques on time scales, a fixed point theorem and the theory of calculus on time scales, the existence and global exponential stability of almost automorphic solutions for this class of neural networks is established. The obtained results are completely new and supplement to the known results. Finally, a numerical example is given to illustrate the feasibility of our results.

Keywords: BAM neural networks, Almost automorphic solution, Quaternion, Global exponential stability, Time scales

DOI: 10.3233/JIFS-181118

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 669-685, 2019

Authors: Khan, Muhammad Adnan | Umair, Muhammad | Saleem, Muhammad Aamer | Ali, Muhammad Nadeem | Abbas, Sagheer

Article Type: Research Article

Abstract: In modern communication, MIMO technology appeared to be one of the important technologies. System capacity and service quality are enhanced by using this technology. The mission of both channel and data estimation based on the principle of maximum likelihood is achieved by means of continuous and discrete TOMPSO algorithm over Rayleigh Fading Channel. The algorithm has three levels. At the first stage, channel and data populations are prepared. The continuous TOMPSO is using to estimate channel parameters at the second stage. Once the channel is estimated, it is used at stage 3 along with discrete TOMPSO to estimate transmitted symbols. …It is observed that due to included total opposite based learning of swarmand velocity factor the TOMPSO gives a fast convergence rate and attractive results in terms of MMSE and MMCE. Show more

Keywords: MIMO, TOMPSO, BER, MMSE, MMCE

DOI: 10.3233/JIFS-181127

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 687-692, 2019

Authors: Li, Xiao-Yang | Xiong, Yun | Duan, Chun-Yan | Liu, Hu-Chen

Article Type: Research Article

Abstract: Failure mode and effect analysis (FMEA) is a powerful reliability management tool for identifying and eliminating known and potential failures in systems, designs, processes, or services to improve their safety and reliability. At present, FMEA has been widely used in various industries. However, the traditional risk priority number (RPN) method has been criticized for many defects. For example, it ignores the relative importance of the risk factors severity (S), occurrence (O), and detection (D), and it is difficult for experts to evaluate the risk of failure modes using precise values from 1 to 10. In this study, we develop a …new FMEA model that combines interval type-2 fuzzy sets (IT2FSs) and fuzzy Petri nets (FPNs) to overcome the drawbacks and improve the effectiveness of the traditional FMEA. The rationality and accuracy of the proposed FMEA are illustrated by an example of aerospace electronics manufacturing project. The results show that the new risk assessment model can produce more reliable and reasonable risk ranking results of failure modes in the practical application. Show more

Keywords: Failure mode and effect analysis (FMEA), interval type-2 fuzzy set (IT2FS), fuzzy petri net (FPN), fuzzy reasoning

DOI: 10.3233/JIFS-181133

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 693-709, 2019

Authors: Huu, Quynh Nguyen | Viet, Dung Cu | Thuy, Quynh Dao Thi | Quoc, Tao Ngo | Van, Canh Phuong

Article Type: Research Article

Abstract: Over the years, many content-based image retrieval (CBIR) methods, which use SVM-based relevant feedback, are proposed to improve the performance of image retrieval systems. However, the performance of these methods is low due to the following limitations: (1) ignore the unlabeled samples; (2) only exploit the global Euclidean structure and (3) not taking advantage of the various useful aspects of the object. In order to solve the first problem, we propose a graph-based semisupervised learning (GSEL), which can add positive samples and construct balanced sets. With the second problem, we propose a manifold learning for dimensional reduction (MAL), which exploits …the geometric properties of the manifold data. With the third problem, we propose a combination of classifiers by aspect (CCA), which exploits the various useful aspects of the object. Experimental results reported in the Corel Photo Gallery (with 31,695 images), which demonstrate the accuracy of our proposed method in improving the performance of the content-based image retrieval system. Show more

Keywords: Content-based image retrieval (CBIR), relevance feedback, support vector machines (SVM), Graph-based Semisupervised learning and manifold learning

DOI: 10.3233/JIFS-181237

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 711-722, 2019

Authors: Hu, Linmin | Cao, Xuerui | Li, Zhenzhen

Article Type: Research Article

Abstract: The objective of this paper is to establish some reliability models for redundant systems based on the assumption that the conversion switches are imperfect and distribution parameters are uncertain variables. Some new concepts of random uncertain distributions associated with random uncertain variables are proposed, which are applied to redundant series-parallel systems, including cold redundant system and warm redundant system. In each type of redundant system, we consider two methods to describe the switch lifetimes: random uncertain 0-1 switch lifetime and random uncertain geometric switch lifetime. The reliability and the mean time to failure of these systems are analyzed. Some numerical …examples are presented to demonstrate the proposed reliability models and perform a comparison for the system models with uncertain parameters and constant parameters. Show more

Keywords: Redundant system, Imperfect switch, Uncertain variable, Reliability, MTTF

DOI: 10.3233/JIFS-181260

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 723-735, 2019

Authors: Birjandi, A. | Mousavi, S. Meysam | Hajirezaie, M. | Vahdani, B.

Article Type: Research Article

Abstract: Multiple routes of networks in fuzzy environments are essential issues in the project scheduling problems (PSPs) with resource constraints, fuzzy RCPSP-MR. Route assignment to flexible work package defined in a project activity network indicates more complexities in front of canonical PSP. Also, in the last few decades, considering uncertainties’ concepts in project schedules have been essential and attracted the attention of researchers and project managers. Therefore, in this article, a new weighted mathematical model is presented under uncertainty conditions, and a new hybrid fuzzy approach is provided via two fuzzy primary methods. Then, a new four-part non-distinct (FPND) approach is …proposed based on PSO, binary particle swarm optimization (BPSO) and genetic algorithm (GA) to minimize project end cost. In this approach as the first part and to generate high-quality primary routes for flexible work package, six different rules are investigated, and the appropriate route is chosen. In the second part, initial solutions are generated via PSO. Then, in the third part, initial solutions are improved based on GA. Finally, in the last part, assigned routes are improved with binary PSO. To appraise the effectiveness of the presented approach, influential parameters are tuned by Taguchi method. Finally, to evaluate the performance of FPND, 70 numerical examples are designed in different dimensions, and results are compared with other well-known algorithms. Show more

Keywords: RCPSP-MR, fuzzy sets theory, multi-route work package, four-part non-distinct (FPND) approach, distribution rules, Taguchi method

DOI: 10.3233/JIFS-181293

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 737-751, 2019

Authors: Sadi-Nezhad, Soheil | Bonnar, Stephen | Andrews, Doug

Article Type: Research Article

Abstract: The concern for the relationship between demographic changes and asset markets has increased from beginning of 2000. Many researchers analyze the relationship between demographic changes and asset prices through regression models. Most of these studies apply linguistic terms for each different phase of the life cycle (e.g. late working-aged, elderly, adult, and middle-aged) and then define a specific behaviour for each of these cohorts. Although these terms are vague, all the researchers define them as a crisp set with crisp partitions. Additionally, fuzzy regression methods have attracted growing interest from researchers in various scientific, engineering, and humanities area due to …the ambiguity in real data. The motivation of this research is that it is rational to consider and apply fuzzy sets to interpret these linguistic terms instead of the crisp partitions. In this study, we propose and apply a new approach in order to calculate the fuzzy frequency for the linguistic term, which can be useful in any other demographic study. Moreover, new fuzzy regression models are developed. These regression models, that are able to consider both fuzzy and crisp regression coefficients are developed based on applying a fuzzy distance concept in which the distance between two triangular fuzzy numbers (TFNs) or between a TFN and a crisp number is a TFN. Multi-objective optimization helps us to find the results without any compromise. The models are solved using the mathematical programming solver LINGO-16 to derive the fuzzy regression coefficients. We apply these models in a numerical example also in a real case study (fuzzy input, crisp output) in which an investigation on the relationship between fuzzy demographic dynamics and monetary aggregates is made. Show more

Keywords: Fuzzy sets, fuzzy demographic changes, fuzzy regression, fuzzy distance, Marshallian K

DOI: 10.3233/JIFS-181297

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 753-769, 2019

Authors: Gopalakrishnan, Nivetha | Krishnan, Venkatalakshmi

Article Type: Research Article

Abstract: Managing and Mining mobile sensor data has become a topic of advanced research in several fields of computer science, such as the distributed systems, the database systems, and data mining. The main objective of the sensor based applications is to make the real-time decision which has been proved to be very challenging due to the high resource-constrained computing and the enormous volume of sensor data generated by Wireless Sensor Networks (WSNs). This challenge motivates the sensor research community to explore new data mining techniques to extract information from large continuous raw data streams obtained from WSNs. Existing traditional data mining …methods are not directly suited to WSNs due to the aggressive nature of sensor data and the presence of anomalies or outliers in WSNs. This work provides an overview of how traditional outlier detection method algorithms are revised and implemented in the application of Human Activity Recognition (HAR). Based on the limitations of the existing technique, a hybrid outlier detection method is proposed. Show more

Keywords: Classification, data mining, human activity, outlier detection, sensor data

DOI: 10.3233/JIFS-181315

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 771-782, 2019

Authors: Elsanabary, Walaa | Gamal, Mona | Abou El-Fetouh, Ahmed | Elkhameesy, Nashaat

Article Type: Research Article

Abstract:  In the presence of high competition market, planning the infrastructures of Telecommunication Access Network (TAN) is one of the most important tasks facing telecommunication companies especially after the trend of using optical fiber cables. This infrastructure is controlled by a list of barriers which affect selecting the locations of the most widely used technology Multi Services Access Nodes (MSAN). Therefore, the importance of determining the appropriate location of MSANs is appeared. This paper presents the capabilities of the Artificial Bee Colony (ABC) to find the fuzzy classifications rules for the telecommunication MSANs locations based on a set of MSAN’s planning …barriers. This system starts by preparing the training data set using the benefits of Geographic Information System (GIS) for generating digital maps. The system helps in analyzing spatial data of existing TAN and the barriers which affect planning TAN. Afterwards, the system fuzzifies the MSAN’s planning barriers using Particle Swarm Optimization and Total Entropy as fitness function (PSO-TE). Then, the ABC capabilities, correlation function and confidence rate as a fitness function and the mamdani inference system are utilized to find the appropriate telecommunication fuzzy rules with respect of training data. The system ends by evaluating the generated telecommunication fuzzy rules for MSAN locations via comparing the result of proposed model with a number of classification algorithms found in literature based on the test data set. The total classification accuracy of the TFRML-ABC model is 97.8%. Hence, the proposed TFRML-ABC model is concluded to be efficient in classifying the MSAN’s features taking into consideration the misclassification rates. Show more

Keywords: Artificial bee colony (ABC), correlation, Min-Max mamdani inference system, particle swarm optimization-total entropy (PSO-TE), telecommunication access network (TAN), geographic information system (GIS), multi services access node (MSAN)

DOI: 10.3233/JIFS-181324

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 783-795, 2019

Authors: Chen, Ke | Luo, Yuedong

Article Type: Research Article

Abstract: This paper proposed a concept based on q-rung orthopair fuzzy sets (q-ROFSs) and linguistic term sets called q-rung orthopair linguistc sets (q-ROLSs). This study also investigates a novel multi-criteria decision-making (MCDM) approach in which the arguments take the form of q-ROLSs, we extend Muirhead mean (MM) aggregation operators under q-rung orthopair linguistic environment. Firstly, certain operational laws of q-ROLSs are investigated. Secondly, the q-rung orthopair linguistic Muirhead mean, the q-rung orthopair linguistic weighted Muirhead mean and the q-rung orthopair linguistic weighted geometric Muirhead mean operators are presented. Special cases of the q-rung orthopair linguistic Muirhead mean operators and their properties …are analysed. With these foundations as basis, an approach is developed to be applied to MCDM problems based on the proposed operators. Finally, a practical example is developed to illustrate this method and comparative analysis demonstrate the superiorities of the aggregation operators. Show more

Keywords: Multi-criteria decision making, q-rung orthopair linguistic sets, muirhead mean, aggregation operator

DOI: 10.3233/JIFS-181366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 797-809, 2019

Authors: Kalpana, B. | Anusheela, N.

Article Type: Research Article

Abstract: This paper develops a latest mathematical model to derive the membership function of fuzzy retrial queue with single server queue model FM 1 , FM 2 /FM 1 , FM 2 /1 with priority and unequal service rates. The vital aim of this paper is to combine the parametric non linear programming technique and Yager’s ranking method. Using α - cut approach and Zadeh’s principle the fuzzy queues are changed into crisp queues in this paper. The membership function of the system characteristics is derived for different values of α . The numerical example is given to check the …validity of the model. Show more

Keywords: Fuzzy sets, membership function, nonlinear programming, priority, retrial queue

DOI: 10.3233/JIFS-181433

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 811-820, 2019

Authors: Salarpour, H. | Ghodrati Amiri, G. | Meysam Mousavi, S.

Article Type: Research Article

Abstract:  Housing market industry is the main factor of economic growth for each country to enhance the gross domestic product. In this respect, countries should implement the best strategy among the candidate strategies in each period to control the housing market for growing the economy and avoiding the impact of a sustainability crisis. Meanwhile, identifying the assessment criteria and recognizing the relative importance of them by regarding their interdependencies coherence could assist decision makers to apply and define the best strategy in each period. Also, in real complex cases, evaluating the criteria based on exact values in which the information is …incomplete or decision makers faced with qualitative criteria are impossible. To address the issue, dynamic interval-valued hesitant fuzzy set (DIVHFS) theory is an appropriate tool that allows experts to define some membership degrees under a set for different periods to suitably cover the dynamic uncertainty. However, this paper proposes a new dynamic hesitant fuzzy hierarchical group decision approach regarding a last aggregation concept for computing the criteria weights regarding the global and local weights by keeping away from the data loss. Thereby, the local weights of criteria are calculated by developing dynamic interval-valued hesitant fuzzy correlation and standard deviation method. Also, the global weight of each criterion is determined based on decision making trial and evaluation laboratory (DEMATEL) methodology regarding the interdependencies coherence of each criterion. In the process of proposed approach, the weight of each decision maker is specified based on manipulated dynamic interval-valued hesitant fuzzy compensatory degree technique to increase the reliability of obtained results. Finally, a real case study for specifying the relative importance of each sustainable criterion in housing market strategy selection problem is prepared to indicate the feasibility and performance of proposed dynamic hesitant fuzzy hierarchical group decision approach. Show more

Keywords: Dynamic interval-valued hesitant fuzzy sets, sustainable development, housing market management, criteria assessment, DEMATEL

DOI: 10.3233/JIFS-181482

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 821-833, 2019

Authors: Jing, Shibo | Yang, Junyu | Yang, Liming | Zhang, Min

Article Type: Research Article

Abstract:  Applying semi-supervised learning to extreme learning machine (ELM), we propose a semi-supervised extreme learning machine classification framework (SSELM) with arbitrary norm (q -norm, q=0,1 and 2). However, the SSELM involves nonconvex and nonsmooth problem. In this work, two types of optimization methods are developed to solve the proposed SSELM. The first one is an exact solution approach that reformulates SSELM as mixed integer programming. The second is an approximation approach that approximates the SSELM framework by DC (difference of convex functions) programming. Several formulations for SSELM are presented with different norm. Furthermore, the proposed methods are applied in a practical …medical dataset using near-infrared spectral technology. Experimental results in different spectral regions show that incorporating unlabeled samples in training improves the generalization compared with the supervised ELM when insufficient training information is available. Moreover, the proposed methods achieve equivalent performance in benchmark data sets compared to the supervised ELM algorithms and other semi-supervised methods. These results show the feasibility and effectiveness of the proposed algorithms. Show more

Keywords: Extreme learning machine, semi-supervised classification, mixed integer programming, DC programming, arbitrary norm

DOI: 10.3233/JIFS-181501

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 835-845, 2019

Authors: Rohani, Arash | Joorabian, Mahmood | Abasi, Mahyar | Zand, Mohammad

Article Type: Research Article

Abstract: This paper deals with a control design based on amplitude adaptive notch filter (AANF) for a four-leg distributed static compensator (DSTATCOM) in a three-phase four-wire distribution grid to overcome current-related problems of power quality. Extracted reference currents of DSTATCOM are obtained using AANF because of its simple structure, exact measuring of frequency and amplitude, suitable estimation of the desired signal, and capability of tracking the changes of the input signal amplitude. To improve the dynamic performance of DSTATCOM, two fuzzy logic controllers are utilized to regulate DC link voltage and the voltage of point of common coupling (PCC). Furthermore, an …adaptive hysteresis band current controller is applied for generating the gate pulses of IGBT switches. The proposed control scheme is robust to power system oscillations, especially when the main voltage suffers from disturbances and unbalancing. Different surveys are performed to study the efficacy of the proposed method, and results are verified through the simulation results in MATLAB/Simulink environment. Show more

Keywords: DSTATCOM, power quality, amplitude adaptive notch filter, fuzzy logic controller, adaptive hysteresis band current controller

DOI: 10.3233/JIFS-181521

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 847-865, 2019

Authors: Oztaysi, Basar | Cevik Onar, Sezi | Seker, Sukran | Kahraman, Cengiz

Article Type: Research Article

Abstract: Water treatment technology (WTT) selection is an excessively important problem since dramatic increases in health problems originated from drinking waters occur day by day. WTTs have high initial investments and operating and maintenance costs with different lives and capacities. Besides, their selection depends on the output quality of the water, capacity, land structure, and environmental issues. Therefore, WTT selection problem is a multi-criteria problem, which requires linguistic evaluations rather than exact numerical evaluations. In this paper, we propose a multi-expert and multi-criteria hesitant Pythagorean fuzzy decision analysis to select best fit WTT for clarification process in water treatment. Aggregation …operators and pairwise comparisons for hesitant Pythagorean fuzzy sets (HPFSs) are applied in the analysis. Comparative analyses are additionally realized to show the validity of the proposed approach and the robustness of the givendecisions. Show more

Keywords: Water treatment, hesitant fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, analytic hierarchy process (AHP)

DOI: 10.3233/JIFS-181538

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 867-884, 2019

Authors: Singh, Akanksha | Kumar, Amit | Appadoo, S.S.

Article Type: Research Article

Abstract: Abdel-Basset et al. (Neural Computing and Applications, 2018, https://doi.org/10.1007/s00521-018-3404-6) proposed methods for solving different types of neutrosophic linear programming problems (NLPPs) (NLPPs in which some/all the parameters are represented as trapezoidal neutrosophic numbers (TrNNs)). Abdel-Basset et al. also pointed out that as a trapezoidal fuzzy number is a special case of trapezoidal neutrosophic number. Therefore, the fuzzy linear programming problems which can be solved by the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315; Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395; Kumar et al., 2011, Appl Math Model, 35 : 817-823; Satti et al., Int J Decis Sci, 7 : 312-33) …can also be solved by thier proposed method. In addition to that, to show the advantages of their proposed method over the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315; Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395; Kumar et al., 2011, Appl Math Model, 35 : 817-823; Satti et al., Int J Decis Sci, 7 : 312-33), Abdel-Basset et al. solved the same fuzzy linear programming problems by their proposed method as well as the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315; Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395; Kumar et al., 2011, Appl Math Model, 35 : 817-823; Satti et al., Int J Decis Sci, 7 : 312-33) and shown that the results, obtained on applying by their proposed method are better than the results, obtained on applying the existing methods (Ganesan and Veermani, Ann Oper Res, 2006, 143 : 305-315; Ebrahimnejad and Tavana, Appl Math Model, 2014, 38 : 4388-4395; Kumar et al., 2011, Appl Math Model, 35 : 817-823; Satti et al., Int J Decis Sci, 7 : 312-33). After a deep study of Abdel-Basset et al. ’s method, it is observed that Abdel-Basset et al. have considered several mathematical incorrect assumptions in their proposed method and hence, it is scientifically incorrect to use Abdel-Basset et al. ’s method in its present form. The aim of this paper is to make the researchers aware about the mathematical incorrect assumptions, considered by Abdel-Basset et al. in their proposed method, as well as to suggest the required modifications in Abdel-Basset et al. ’s method. Show more

Keywords: Trapezoidal neutrosophic number (TrNNs), linear programming, neutrosophic set, ranking function

DOI: 10.3233/JIFS-181541

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 885-895, 2019

Authors: Mishra, Akansha | Kumar, Amit | Khan, Meraj Ali

Article Type: Research Article

Abstract: Bharti and Singh (International Journal of Fuzzy Systems 20 (2018), 1511-1522) proposed a method for solving a special type of interval-valued intuitionistic fuzzy transportation problems (IVIF-TPs) (transportation problems (TPs) in which the quantity of the product to be supplied is represented as a real number, whereas, all the other parameters are represented as interval-valued triangular intuitionistic fuzzy numbers (IVTIFNs)). In this note, an interval-valued intuitionistic fuzzy transportation problem (IVIF-TP) is solved by Bharti and Singh’s method and shown that more than one IVTIFNs, representing the optimal interval-valued intuitionistic fuzzy (IVIF) transportation cost is obtained, which is mathematically …incorrect as the obtained distinct IVTIFNs has different physical meanings. Also, it is pointed out that to resolve this flaw of Bharti and Singh’s method may be considered as a challenging open research problem. Show more

Keywords: Interval-valued intuitionistic fuzzy numbers, IVTIFNs, transportation problem

DOI: 10.3233/JIFS-181547

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 897-900, 2019

Authors: Dong, Yuanxiang | Hou, Chenjing

Article Type: Research Article

Abstract: Soft set theory, proposed by Molodtsov, has been regarded as a generic mathematical tool for dealing with uncertainties. However, classical soft sets are not appropriate to deal with incomplete and inconsistent information. In this paper, we introduce the concept of paraconsistent soft sets combining paraconsistent logic and soft sets. The complement, “And”, restricted intersection, relaxed intersection, restricted cross and relaxed cross operations are defined on paraconsistent soft sets. In order to deal with incomplete and inconsistent information in decision making simultaneously, we also define paraconsistent soft decision system, choice value, decision value, the selected set and the eliminated set, and …bring up the decision algorithm. Finally, an investment decision problem with incomplete and inconsistent information is analyzed by paraconsistent soft sets. The result shows that paraconsistent soft sets with more adequate parameterization can solve decision making problems with incomplete and inconsistent information more effectively than classical soft sets. Show more

Keywords: Soft sets, paraconsistent logic, incomplete information, inconsistent information, decision making

DOI: 10.3233/JIFS-181553

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 901-912, 2019