Journal of Intelligent & Fuzzy Systems - Volume 37, issue 3

Authors: Ran, Xiuxia | Hossain, Mahmud

Article Type: Research Article

Abstract: In order to strengthen the training of English writing, this paper proposed a new business English writing training strategy based on some state-of-the-art recommendation algorithm. Firstly, we introduced the development of business English writing briefly, and then we studied how the recommendation algorithm is used to construct the English writing training model for the teachers, which can better assist students in business English writing training and reduce the common mistakes in writing. In this paper, we proposed an optimization and update scheme by the state-of-the-art recommendation algorithms. Furthermore, we designed a useful identification model to evaluate the continuous state of …business English writing. The experimental results show that the coding accuracy of English vocabulary and the efficiency of the model can archive a good performance, which can effectively help students to write. This model deserves further promotion and application. Show more

Keywords: New media environment, writing skills, problem recommendation algorithm, business English

DOI: 10.3233/JIFS-179148

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3445-3452, 2019

Authors: Yin, Xinzhen | Dylan, Baker

Article Type: Research Article

Abstract: At present, most of the comparative education research concentrated in the macro education field such as international education, which has a significantly influenced the future education. Under this circumstances, this paper studied the development choices of comparative education in colleges and universities in the era of big data. Firstly, a new recommendation algorithm is proposed based on the characteristics of education big data. The comparative evaluation of the matching mode of colleges and universities is studied. Subsequently, we designed a new corresponding differential classification teaching mode on the basis of the naive Bayesian algorithm of comparative education in colleges and …universities. At last, we designed a set of experiments to evaluate the proposed classification system. By comparing the development of comparative education platforms in colleges and universities, the optimal utilization combination of colleges and universities in the era of big data is realized to select the best development direction. Show more

Keywords: Big data, colleges and universities, comparative education, development choice

DOI: 10.3233/JIFS-179149

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3453-3460, 2019

Authors: Sang, Zhongqing | Zhang, Rencheng

Article Type: Research Article

Abstract: Focused on the security of switchgear, this paper presented a complete set of an online detection system for the temperature rise of switchgear based on branch definition algorithm. This paper analyzed the characteristics of the temperature rise of the low-voltage circuit breaker terminal, and then proposed a new temperature rise model of the terminal through the thermal network method. In this paper, the influence factors of the temperature rise of the terminal analyzed through the test data, and the temperature rise curve also fitted by using the least squares method. The range of temperature rise time constants for the 100A …low-voltage circuit breaker terminal obtained, and the method of quickly deriving the steady temperature rise of the low-voltage circuit breaker terminal discussed. The simulation results show that the optimization of the algorithm can provide a scientific evaluation method and improved strategy for the on-line detection of temperature rise of complete switchgear. Show more

Keywords: Branch definition algorithm, switch equipment, temperature rise

DOI: 10.3233/JIFS-179150

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3461-3468, 2019

Authors: Ma, Jun | Yu, Hongzhi | Wang, Ding | Pu, Cuocairen | Singh, Amit Kumar

Article Type: Research Article

Abstract: “The preservation of endangered ethnic minority languages” and “application of ethnic minority languages” have become an important research direction and topic for the ethnic minority language researchers. Based on the previous studies, the combined quantitative and qualitative analysis was made to carry out a systematic study on vowels and consonants in the Salar language, especially the strong vowels, weak vowels, voiceless consonants, and voiced consonants, in order to create the “Salar Acoustical Phonetics Parameter Database”. According to the relevant norms, the segmentation, labeling, parameters extraction and database creation were conducted against the collected signals, and the experimental research on the …Salar phonetics was implemented by making a comprehensive statistical analysis of the database. Through the study of Salar phonetics based on the Salar Acoustical Phonetics Parameter Database, it not only provides basic parameters of acoustic physiology for preservation and research of Salar language, but also provides the basic data for the future Salar acoustical corpus construction, speech recognition and speech synthesis, and provides a practical theoretical basis for the acoustical research of the national language project under construction. Show more

Keywords: Salar language, voice acoustic, parameters database

DOI: 10.3233/JIFS-179151

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3469-3476, 2019

Authors: Yang, Ping-Yu | Chou, Li-Chen | Wang, Zhan-Ao

Article Type: Research Article

Abstract: Using Taiwan’s Manpower Utilization Survey from 2012–2014, this paper investigates the impacts that salary variation caused by insufficient information, then evaluates the condition of information holding between the employee and the employer. The results indicate that the ignorance of employee and employer are deeper in the private sector than that in the public sector; the employees and employer ignorance with the white-collar both larger than the blue-collar. Besides, the results demonstrate insignificantly effect in both ignorance estimation in the public sector, which may reflect the labors enter to the public sector mainly through national examination and cause the insignificant estimation.

Keywords: Taiwan, employee relations, information processing

DOI: 10.3233/JIFS-179152

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3477-3487, 2019

Authors: Li, Yingwei | Yang, Yuntong | Ma, Shaoqing | Li, Lei | Wang, Yanjun | Liu, Xingbin | Xie, Ronghua

Article Type: Research Article

Abstract:  The development of Daqing Oilfield in China has entered the middle and late stages of high water cut. At this time, oil-water two-phase flow is ubiquitous, and its flow rate is very difficult to measure accurately. Addressing this issue, the measurement model and simulation model of electromagnetic flow transducer (EFT) with saddle excitation structure is designed in this paper. Then the distribution characteristics of magnetic flux density of different excitation structures are analyzed by finite element simulation. Furthermore, the prediction model between the parameters of different excitation structures and the performance evaluation indexes is established based on RBF neural network. …Through normalization and weight assignment on the output of neural network model, the structure optimization factor is constructed. Then the optimum solution of this factor is gotten, and the optimum parameters of EFT’s excitation structure are obtained. In addition, an EFT with the optimum structure is developed and tested in Daqing oilfield, and the experiment results show that the EFT has high precision, especially in the high viscosity wells. Show more

Keywords: Oil-water two-phase flow, electromagnetic flow transducer, finite element simulation, RBF neural network

DOI: 10.3233/JIFS-179153

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3489-3498, 2019

Authors: Li, Xiaoyun | Fan, Ruiqin | Zhang, Hao Lan | Li, Tongliang | Pang, Chaoyi

Article Type: Research Article

Abstract: Wavelet synopses with maximum error bound is an effective quality-guaranteed compression method that restricts the approximation error of each data does not exceed a given error bound. In this paper, we focus on the study of constructing efficient two-dimensional wavelet synopses with maximum error bound. First, we propose a linear-time two-dimensional F-shift algorithm (TDFS), then present a general parallel framework for two-dimensional data array and generate a parallel two-dimensional F-shift algorithm (PTDFS). We have proven that the size of a synopsis constructed from PTDFS is always no larger than that of the existing methods and can reduce up to 66.7% …at most. The experimental results indicate that the synopsis sizes can be reduced from 40% to 60% in most situations. Moreover, PTDFS can not only improve the quality of reconstruction image, but also reduce the running time. Show more

Keywords: Wavelet synopses, parallel, error bound, data compression

DOI: 10.3233/JIFS-179154

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3499-3511, 2019

Authors: Libo, Zhou | Tian, Huang | Chunyun, Guan | Elhoseny, Mohamed

Article Type: Research Article

Abstract: A fundamental problem facing deep neural networks is that they require a large amount of data to keep the system efficient in complex applications. Promising results of this problem are made possible by using techniques such as data enhancement or transfer learning in large data sets. However, when the application provides limited or unbalanced data, the problem persists. In addition, the number of false positives generated by deep model training has a significant negative impact on system performance. This study aims to solve the problem of false positives and class imbalances by implementing an improved filter library framework for Cole …pest identification. The system consists of three main units: First, the primary diagnostic unit (boundary box generator) generates a bounding box containing the location of the infected area and class. Then, the promising box belonging to each category is used as an input to the secondary diagnostic unit (CNN filter bank) for verification. In the second unit, the misclassified samples are filtered by training for each category of independent CNN classifiers. The result of the CNN filter bank is to determine if a target belongs to the category because it is detected (true) or no (false), otherwise. Finally, an integrated unit combines the information of the autonomous unit and the secondary unit in the future while maintaining a true positive sample and eliminating false positives of misclassification in the first unit. By this implementation, the recognition rate of this method is about 96%, which is 13% higher than our previous work in the complex task of Cole disease and pest identification. In addition, our system is able to handle false positives generated by bounding box generators and class imbalances that occur on data sets with limited data. Show more

Keywords: Plant diseases, detection, deep neural networks, filter banks, false positives

DOI: 10.3233/JIFS-179155

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3513-3524, 2019

Authors: Liu, Zimei | Xie, Yi | Zhang, Hao

Article Type: Research Article

Abstract:  Stampede accidents with serious injuries occur from time to time on escalators. Field observation was conducted on four typical passenger behaviors during taking escalators, namely, walking behavior, subgroup behavior, overtaking behavior and waiting behavior. The effect of behavior characteristics on passenger safety was analyzed according to the observation data. Several scenarios were simulated to quantitatively study the impact of passenger behaviors on crowd stampede risk under different situations. The results show that: (1) the presence of subgroup behavior and overtaking behavior increases the crowd stampede risk by increasing the crowd density and the degree of congestion on the connection plane; …(2) the walking behavior reduces the crowd density; (3) the “walk left, stand right” rule decreases the evacuation efficiency; (4) waiting behavior of passengers on the connection plane significantly increases the crowd stampede risk. Management measures were proposed to promote the passenger safety and reduce the stampede injury on escalators. Show more

Keywords: Passenger safety, crowd stampede risk, passenger behavior, escalator, simulation

DOI: 10.3233/JIFS-179156

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3525-3533, 2019

Authors: Heda, Zhang

Article Type: Research Article

Abstract: Machinery and equipment are widely used in modern large-scale production, while industrial large-scale production and the progress of science and technology make machinery and equipment more complex and large-scale. Traditional mechanical diagnosis technology cannot meet the actual diagnosis requirements. The residual life of the whole equipment is predicted. This is of great significance for improving the efficiency of equipment, enhancing reliability, reducing maintenance costs and prolonging service life. The advantages of artificial intelligence in solving the problems of remote control, fault diagnosis and non-linearity point out the direction of the development of mechanical fault diagnosis technology. The research shows that …the fault prediction and maintenance process based on the operating state of the device is summarized into three steps: data acquisition, data processing and equipment remaining life prediction. The comprehensive detection algorithm is used for diagnosis, and the diagnosis method is comprehensively analyzed. The research shows that after optimizing the network parameters through human intelligence, the network convergence speed is obviously accelerated, which can be used as a performance-based pattern recognition system for fault diagnosis of mechanical equipment. Show more

Keywords: Artificial intelligence, machinery and equipment, fault diagnosis

DOI: 10.3233/JIFS-179157

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3535-3544, 2019

Authors: Zhang, Guanhong | Brown, Peter | Li, Guobin

Article Type: Research Article

Abstract: With the maturity of virtualization technology, cloud computing has brought us new computing and service models. Adopting a resource pool solution based on cloud computing architecture, the virtualized resources can be uniformly managed and deployed to achieve the purpose of automated and intelligent management of information systems. However, because cloud servers have some features that are different from ordinary hosts, existing intrusion detection technologies cannot be directly applied to cloud computing. This paper focuses on the real-time dispatching of people. The main innovation of this paper is to apply BP neural network technology to the real-time dispatching of intelligent people, …establish the time prediction model of intelligent dispatching of people based on BP neural network, and design the intelligent dispatching algorithm of people based on BP neural network, and use examples to analyze the opposition to verify the feasibility of the algorithm. The results show that the algorithm improves the classification accuracy of neural networks and shortens the training time of samples. It improves the efficiency of intelligent dispatch detection, the accuracy of results and the efficiency of explicit algorithm. Show more

Keywords: Intelligent Scheduling, BP neural network, Cloud Computing, Real-time

DOI: 10.3233/JIFS-179158

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3545-3554, 2019

Authors: Sun, Bo | Wei, Ming | Yang, Chungfeng | Ceder, A.

Article Type: Research Article

Abstract:  This paper presents a fuzzy optimization model for demand-responsive feeder transit services (DRT) that can transport an uncertain number of passengers from demand points to the rail station. The proposed model features fuzzy triangular number variables used to describe the changes in travel demand. Moreover, some practical factors such as boarding time windows and expected ride time are comprehensively considered in the model. The problem is formulated as a mixed-integer fuzzy expectation model to minimize the total travel distance for all routes, and its deterministic linear programming model is then obtained based on the credibility theory. Because the proposed model …is an extension of the NP-hard problem, this study involves the design of a collaborative ant colony optimization (ACO), which redefines the construct rules, pheromones, heuristic information, and selection strategies of solutions to address the limitations of traditional ACO such as the premature convergence. When ACO applied to a case study in Nanjing City, China, sensitivity analyses are performed to investigate the impact of the number of vehicles on results of the scheduling, compared with the traditional model. Finally, the proposed ACO is compared with ACO, standard ACO, particle swarm optimization (PSO), and genetic algorithm (GA) to prove its validity. Show more

Keywords: DRT transit system, fuzzy travel demand, ACO

DOI: 10.3233/JIFS-179159

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3555-3563, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3565-3565, 2019

Authors: Nayak, Byamakesh | Choudhury, Tanmoy Roy | Misra, Banishree | Mohapatra, Alivarani

Article Type: Research Article

Abstract: In this paper, component values of analog active filters are selected based on the manufacturer’s values of E series. The selection is based on optimization algorithms and here one is nature-inspired meta-heuristic optimization algorithm, called Whale Optimization Algorithm (WOA), and another one is the physics-based method called Sine Cosine Algorithm (SCA), are used for active filter design. The capability of optimization of the above algorithms is evaluated by considering the two active filters of a 4th order Butterworth and State variable filter. The performances of each algorithm are analyzed by applying to above two different filter structures, where the component …values are determined by making compatible with different E series manufacturer. Show more

Keywords: Active filter design, E series, sine cosine algorithm, whale optimization algorithm, 4th order butterworth filter, state variable filter

DOI: 10.3233/JIFS-171965

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3567-3579, 2019

Authors: Shi, Lukui | Du, Weifang | Li, Zhanru

Article Type: Research Article

Abstract: A two stage recognition method combined multiple kind of features was proposed to overcome the limitation of single kind of feature in the lung sound recognition. The method combines the improved Welch power spectrum, Mel cepstrum coefficients and the linear prediction cepstral coefficients based on the wavelet decomposition. In the first stage, pneumonia samples and asthma samples are firstly taken as the abnormal category. Then a two-class classifier based on random forests is trained to identify the normal samples and the abnormal samples. In the second stage, a classifier based on random forests is trained to recognize pneumonia and asthma …from the samples classified as the abnormal samples in the first stage. To further improve the accuracy, a multi granularity cycle segmentation method of lung sounds was presented, which is based on the short time zero crossing rate. It can better segment lung sounds. Experimental results showed that the proposed method greatly improved the recognition accuracy, especially for improving the accuracy of pneumonia and asthma. Show more

Keywords: Lung sound, random forest, Welch power spectrum, Mel cepstrum coefficient, linear prediction cepstral coefficient

DOI: 10.3233/JIFS-181339

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3581-3592, 2019

Authors: Wang, Guijun | Gao, Tong | Sun, Gang

Article Type: Research Article

Abstract: Fuzzy similarity degree is a measurement of the similarity between fuzzy sets through local information, it plays an important role in the design of fuzzy system and controller. This article first proposes a new computational formula for membership functions of a consequent fuzzy set based on fuzzy similarity degree, and an analytic representation of the Mamdani fuzzy system is obtained through the Gauss fuzzification, product inference engine and center average defuzzification. Next, a specific Mamdani fuzzy system constructed by Gauss fuzzifier or singleton fuzzification be expressed through a given fuzzy similarity degree in practice. Finally, the output algorithm of the …proposed fuzzy system is given by the space positioning method. The result shows that the Mamdani fuzzy system constructed by fuzzy similarity degree and Gauss fuzzification is superior to that based on singleton fuzzification in terms of approximation capability. Show more

Keywords: Fuzzy system, fuzzy similarity degree, Gauss fuzzification, singleton fuzzification, output algorithm

DOI: 10.3233/JIFS-181599

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3593-3603, 2019

Authors: Imran, Muhammad | Siddiqui, Muhammad Kamran | Baig, Abdul Qudair | Khalid, Waqas | Shaker, Hani

Article Type: Research Article

Abstract: Graph theory is a fundamental and energetic tool for designing and modeling a graph/network. There are certain topological indices based on degree, distance and eccentricity, etc. The topological indices essentially relate certain physio-concoction properties and bio-activity to the corresponding synthetic and atomic structure. In this paper, our aim is to figure out degree-based topological indices mainly atom-bond connectivity (ABC ), geometric-arithmetic (GA ), ABC 4 and GA 5 indices for cellular neural network (CNN) and give closed results of these indices for cellular neural network. Moreover, we also compute general Randi c ´ …index R α of CNN for α = { 1 , - 1 , 1 2 , - 1 2 } only and give analytical closed form results. A 3D graph analysis for comparison of indices is also given. Show more

Keywords: Molecular descriptor, cellular neural network, atom bond connectivity index, geometric arithmetic index, general Randić index

DOI: 10.3233/JIFS-181813

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3605-3614, 2019

Authors: Liu, Peide | Shen, Mengjiao

Article Type: Research Article

Abstract: As the extension of intuitionistic fuzzy numbers (IFNs), linguistic intuitionistic fuzzy numbers (LIFNs) are proposed. LIFNs are expressed by linguistic variables and take the membership degree (MD) and non-membership degree (NMD) into consideration. The MD and NMD of LIFNs can easier describe complex and fuzzy information in multiple attribute decision-making (MADM) problems. The TODIM method based on prospect theory can reflect the psychological factors of the decision makers (DMs). However, existing TODIM methods neither handle the decision-making problems under linguistic intuitionistic environment nor consider interrelations among multiple attributes. Based on these problems, in this paper, combining the fuzzy measure with …the TODIM method, an extended Choquet-TODIM method is proposed to process the MADM problems. The extended Choquet-TODIM method considers the interrelationship of multiple attributes and the bounded rationality of DMs. Firstly, the relative theories of LIFNs, the classical TODIM method and λ -fuzzy measures are briefly reviewed. Secondly, the TODIM method is extended to linguistic intuitionistic fuzzy environment and C-TODIM method of LIFNs is proposed. Then λ -fuzzy measure is extended to the classical TODIM method and a model of determining fuzzy measures is proposed. The proposed method gives the new solution to calculate the fuzzy measures and address the MADM problems with interrelationship among different attributes. Lastly, two numerical examples are used to compare with two existing methods and explain the effectiveness and superiority of this method. Show more

Keywords: Linguistic intuitionistic fuzzy numbers, TODIM method, fuzzy measures, multiple attribute decision making

DOI: 10.3233/JIFS-182554

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3615-3627, 2019

Authors: Shao, Ming-Wen | Wu, Wei-Zhi | Wang, Chang-Zhong

Article Type: Research Article

Abstract: There are mainly two classes of approaches in the studies of Formal Concept Analysis (FCA), i.e. the constructive and axiomatic approaches. In axiomatic approach, operators are interpreted by using operations in mathematical systems instead of operations in a formal context. Seeking for minimal axioms to characterize the concept generation operators is an important issue in the research of the axiomatic approach. In this paper, axiomatic characterizations of set-theoretic operators are investigated. We construct an adjoint generalized (dual) concept systems in which the pair of classical concept generation operators are represented by one set-theoretic operator, and the other operator can be …obtained from the former. Compared with the previous methods, the proposed generalized (dual) concept systems have fewer axioms and is easy to verify. Some properties of adjoint generalized (dual) concept systems are examined. Show more

Keywords: Concept lattice, galois connection, generalized concept system, set-theoretic operator

DOI: 10.3233/JIFS-182612

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3629-3638, 2019

Authors: Qu, Guohua | Li, Tianjiao | Qu, Weihua | Xu, Ling | Ma, Xiaolong

Article Type: Research Article

Abstract: Interval-value dual hesitant fuzzy set, first proposed by Ju et al. (Interval-valued dual hesitant fuzzy aggregation operators and their applications to multiple attribute decision making, 1203–1218, 2014). Multiple attribute decision making with dual hesitant fuzzy information is a new research topic since dual hesitant fuzzy set was firstly proposed, it has been widely studied in the fuzzy decision making literature. As a new generalization of fuzzy sets, interval-value dual hesitant fuzzy set (IVDHF) This article develops a multi-attribute decision making method considering the regret value theory and group satisfaction for the interval-value dual hesitant fuzzy element and incomplete weight information. …Considering that decision makers have different level of the degree of evaluation, firstly, based on the score function and the accuracy function of the interval-valued hesitant fuzzy element, the deviation function of the interval-valued hesitant fuzzy set is defined. On this basis, a new group satisfaction is proposed. And then, for the situation where the information of attribute weight is incompletely known and completely unknown, some optimization models of attribute weight are established by using the new group satisfaction degree, and then the attribute weight can be determined. Finally, a real example of investment alternative evaluation is carried out to validate the implementation of the proposed approach. Show more

Keywords: Interval-valued dual hesitant fuzzy set, group satisfaction degree, regret theory, stochastic multiple attribute decision making

DOI: 10.3233/JIFS-182634

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3639-3653, 2019

Authors: Chen, Jin | Meng, Sun | Zhou, Wei

Article Type: Research Article

Abstract: In today’s society, many decision-making problems cannot be merely solved based on quantitative data. Even though some issues are able to be addressed by quantitative data, researchers may face the difficulty of obtaining accurate and sufficient numbers. Some qualitative evaluations given by experts or decision makers are usually linguistic expressions. Therefore, fuzzy linguistic research has been broadly studied to address the above issues. This research has also been attracting increasing attention from researchers and decision makers in the world. It is believed that analyzing the status quo and emerging trends in this research area is of great necessity, especially for …the beginners who are interested in fuzzy linguistic research. To do so, this paper provides the mapping knowledge domain of fuzzy linguistic research based on 648 papers on Web of Science from 1975 to 2018 by using CiteSpace which is an effective tool for scientometric studies. The visualization analyses of cited reference clusters, collaborations networks, author co-citation networks, burst detection and time zone view are presented in this study to show the research streams and the papers that made significant theoretical contributions. Also, the active counties, institutions, journals and authors in this research area are analyzed in detail. Besides, the specific hot spots and emerging trends can be known. There are two contributions in this study. Firstly, we give a comprehensive investigation about the status quo and emerging trends of fuzzy linguistic research in the recent 43 years. Secondly, we make the development of fuzzy linguistic research easier and direct to learn for beginners. Show more

Keywords: Fuzzy logic, linguistics, decision making, CiteSpace, scientometric

DOI: 10.3233/JIFS-182737

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3655-3669, 2019

Authors: Riaz, Muhammad | Hashmi, Masooma Raza

Article Type: Research Article

Abstract: In multi-attribute group decision-making (MAGDM) problems, there exist some multi-polarity for the attributes and criteria. Sometimes in real life situations, we deal with the both membership and non-membership grades for the attributes in the presence of multi-polarity. For this purpose, we change verbally stated information into mathematical language with the help of uncertain linguistic variables to deal with the ambiguities and uncertainties. In that case, we construct some extensions from the existing hybrid structures of fuzzy set to handle these types of problems. That’s why from the prevailing concepts of cubic set and m-polar fuzzy set, we innovate the concept …of cubic m-polar fuzzy set (CMPFS). We investigate its numerous operations with the help of examples. With the enthusiasm of CMPFS, we establish certain aggregation operators based on cubic m-polar fuzzy numbers (CMPFNs) namely Cubic m-polar fuzzy weighted averaging (CMPFWA), Cubic m-polar fuzzy ordered weighted averaging (CMPFOWA) and Cubic m-polar fuzzy hybrid averaging (CMPFHA) operators corresponding to R -order and P -order, simultaneously. Using the score function and accuracy function a relation is proposed, through which we can compare the CMPFNs. This manuscript presents a novel approach for treating ambiguities based on the application of land selection using linguistic variables in CMPF decision theory. An algorithm based on MAGDM is intended for a given agricultural project, which will produce results according to the proposed operators one by one. Furthermore, a comparative analysis is listed to demonstrate the difference, advantages, validity, simplicity, flexibility and superiority to the proposed operators. Show more

Keywords: Cubic m-polar fuzzy set (CMPFS), membership degrees, Cubic m-polar fuzzy weighted averaging (CMPFWA) operator, Cubic m-polar fuzzy ordered weighted averaging (CMPFOWA) operator and Cubic m-polar fuzzy hybrid averaging (CMPFHA) operator, MAGDM for agricultural purpose

DOI: 10.3233/JIFS-182809

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3671-3691, 2019

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

Article Type: Research Article

Abstract: Software Release Planning (SRP) is to find, for a software, a subset of the requirements with the highest value while respecting the budget. The value of a requirement however may, to various degrees, depend on selecting or ignoring other requirements. However, existing SRP models ignore either Value-Related Dependencies altogether or the strengths of those dependencies even if they consider them. This paper presents an Integer Programming model for software release planning, which considers the variances of strengths of positive and negative value-related dependencies among software requirements. To capture the imprecision associated with strengths of value-related dependencies we …have made use of algebraic structure of fuzzy graphs. We have further, contributed a scalable technique for automated identification of value-related dependencies based on user preferences for software requirements. The validity of the work is verified through simulations. Show more

Keywords: Fuzzy Graphs, Integer Programming, Value-Related Dependencies, Release Planning

DOI: 10.3233/JIFS-182810

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3693-3707, 2019

Authors: Chen, Yingyue | Chen, Yumin | Yin, Aimin

Article Type: Research Article

Abstract: Feature extraction for blind image steganalysis produces much features or high dimensional data, which bring about time consuming and even a low detection percentage. As being one of the most important phases of preprocessing, feature selection can reduce these extracted features, and improve the performance of steganalysis. Firstly, we introduce the Neighborhood Rough Sets (NRS) to the field of blind image steganalysis. Then, some concepts of feature significance and feature reduct are presented based on NRS. Furthermore, we propose a Feature Selection approach by NRS for blind image steganalysis (FSNRS). The FSNRS has the ability to delete redundant features, meanwhile …maintaining the classification accuracy of a steganalysis system. The FSNRS is a filter feature selection technique for blind image steganalysis, which filtrates extracted features depending on a positive region preserving in NRS. The compact feature subset with a shortest feature dimension for blind image steganalysis is selected. Moreover, some experiments for blind steganalysis using SVM and KNN classifiers on selected feature subset are carried out. The experimental results show that our proposed approach can obtain compact features for blind image steganalysis and the performances of classifiers on those selected features are improved. Since the FSNRS is used with an adjustable neighborhood parameter, as a result, the classification performance of selected features is better than that of original whole features in most cases. Show more

Keywords: Image steganalysis, blind steganalysis, feature selection, neighborhood rough sets, rough sets

DOI: 10.3233/JIFS-182836

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3709-3720, 2019

Authors: Rahman, Khaista | Abdullah, Saleem | Ghani, Fazal

Article Type: Research Article

Abstract: The concept of interval-valued Pythagorean fuzzy (IVPF) sets is capable of handling imprecise and ambiguous information and managing complex uncertainty in real-world applications. The focus of our this paper is to introduce some generalized operators, such as the generalized interval-valued Pythagorean fuzzy Einstein weighted averaging (abbreviated as GIVPFEWA) operator, the generalized interval-valued Pythagorean fuzzy Einstein ordered weighted averaging (abbreviated as GIVPFEOWA) operator, and the generalized interval-valued Pythagorean fuzzy Einstein hybrid averaging (abbreviated as GIVPFEHA) operator along with their some general properties, such as idempotency, commutativity, monotonicity and boundedness. Furthermore, the method for multiple attribute group decision making problems based on …these operators was developed, and the operational processes were illustrated in detail. The main advantage of using the proposed methods and operators is that these operators and methods give a more complete view of the problem to the decision makers. These methods provide more general, more accurate and precise results as compared to the existing methods. Therefore these methods play a vital role in real world problems. Finally the proposed operators have been applied to decision-making problems to show the validity, practicality and effectiveness of the new approach. A systematic comparison between the existing work and the proposed work also has been given. Show more

Keywords: GIVPFEWA operator, GIVPFEOWA operator, GIVPFEHA operator, Group decision-making

DOI: 10.3233/JIFS-182951

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3721-3742, 2019

Authors: Rashmanlou, Hossein | Pal, Madhumangal | Raut, Sreenanda | Mofidnakhaei, F. | Sarkar, Biswajit

Article Type: Research Article

Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. The intuitionistic fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they have many applications in networks. The main purpose of this paper is to introduce some connectivity concepts in the intuitionistic fuzzy graphs. Analogous to fuzzy cutvertices and fuzzy bridges in fuzzy graphs, intuitionistic fuzzy cutvertices and intuitionistic fuzzy bridges are introduced and characterized. We also proposed the concept of gain and loss for …paths and pairs of vertices. Finally, we give an application of intuitionistic fuzzy digraphs. Show more

Keywords: Intuitionistic fuzzy digraph, gain, loss, intuitionistic fuzzy cutvertices, intuitionistic fuzzy bridge

DOI: 10.3233/JIFS-182961

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3743-3749, 2019

Authors: Wang, Lan | Pang, Bin

Article Type: Research Article

Abstract: In this paper, we mainly focus on the relationship between (L , M )-fuzzy closure systems and (L , M )-fuzzy convex structures as well as the relationship between (L , M )-fuzzy closure systems and (L , M )-fuzzy cotopologies. Firstly, we show that there is an adjunction between the category LMFC of (L , M )-fuzzy convex spaces and the category LMFS of (L , M )-fuzzy closure spaces, and there is also an adjunction between the category LMFT of (L , M )-fuzzy cotopological spaces and LMFS . In particular, the categories LMFC …and LMFT are both coreflective subcategories of LMFS . Secondly, we prove that there is an adjunction between the category ELFC of extensional L -fuzzy convex spaces and the category LFC of L -fuzzy convex spaces, and there is also an adjunction between the category ELFT of extensional L -fuzzy cotopological spaces and the category LFT of (L , M )-fuzzy cotopological spaces. Specially, ELFC is a coreflective subcategory of LFC and ELFT is a coreflective subcategory of LFT . Show more

Keywords: (L, M)-fuzzy closure system, (L, M)-fuzzy convex structure, (L, M)-fuzzy cotopology, coreflective subcategory

DOI: 10.3233/JIFS-182963

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3751-3761, 2019

Authors: Tremante, Panayotis | Yen, Kang | Brea, Ebert

Article Type: Research Article

Abstract: The fuzzy control uses qualitative knowledge with linguistics descriptions about the operation of any process. Furthermore, Fuzzy Controller (FC) has several parameters which can be adjusted to change the performance. If this adjust is done through a “trial and error” procedure, then it will be very time-consuming and difficult to reach a good performance. Frequently, the tuning of the Membership Functions (MFs) have the most influence to improve the performance of a FC. Therefore, in this study we tune the MFs of a FC using optimization by Direct Search (DS) method, specifically the pattern search. In this sense, our goal …is to improve the performance of the system to satisfy certain conditions and propose optimization method to tune the MFs. The methodology of the optimization is simulation-based. The Objective Function (OF) is the squared error between the set point and the output of the system. The evaluation of the OF and the implementation of the fuzzy control system were performed by simulations. An explanation of the algorithmic method based on the pattern search algorithm is shown. The method proposed in this paper is illustrated with examples for the non-linear systems. The results are compared and discussed with other controllers. Show more

Keywords: Fuzzy control, membership functions, optimization, pattern search

DOI: 10.3233/JIFS-190003

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3763-3776, 2019

Authors: Luqman, Anam | Akram, Muhammad | Davvaz, Bijan

Article Type: Research Article

Abstract: A q -rung orthopair fuzzy model is a powerful framework for illustrating uncertainty and vagueness. This model is more practical, flexible and appropriate as compared to fuzzy, intuitionistic fuzzy and Pythagorean fuzzy models. Directed hypergraphs are utilized to execute higher-order relationships in communications and social webbing. In this research study, we design a new framework for manipulating q -rung orthopair fuzzy data by means of combinative theory of q -rung orthopair fuzzy sets and directed hypergraphs. We introduce certain new concepts, including q -rung orthopair fuzzy directed hypergraphs, dual directed hypergraphs, line graphs and coloring of q -rung orthopair fuzzy …directed hypergraphs. Further, we implement some interesting concepts of q -rung orthopair fuzzy directed hypergraphs to real life problems. Show more

Keywords: q-Rung orthopair fuzzy directed hypergraphs, dual directed hypergraphs, coloring of q-rung orthopair fuzzy directed hypergraphs, algorithms

DOI: 10.3233/JIFS-190054

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3777-3794, 2019

Authors: Sornam, Madasamy | Vanitha, Venkateswaran

Article Type: Research Article

Abstract: The standard backpropagation algorithm has already proven its effectiveness in most of the potential problems, but the major limitation is entrapment of local minima and slow convergence rate. To address these issues, a modified backpropagation algorithm has been proposed by adding a third term called inertia, the physical component used to accelerate the network towards the convergence without getting stuck into local minima. The Chebyshev polynomial form is a convenient method for expanding a function in a linear independent term. Inertia has been expanded using Chebyshev polynomial which is used as a third term in weight updation. The performance of …the proposed algorithm outperforms the standard backpropagation algorithm (SBP) and the backpropagation algorithm with momentum (SBPM). The proposed algorithm was tested with the standard benchmark problems such as XOR problem, parity checking problem and dataset from UCI machine learning repository such as iris flower classification, wheat classification, breast cancer detection and wine classification. Experimental results show that the addition of the third parameter called inertia in the backpropagation algorithm gave better performance and faster convergence rate compared to the SBP and SBPM. Show more

Keywords: Back propagation, chebyshev polynomial, feed forward neural network, inertia, momentum

DOI: 10.3233/JIFS-190063

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3795-3804, 2019

Authors: El-Saady, Kamal | Temraz, Ayat A.

Article Type: Research Article

Abstract: In this paper we consider the category M -FQMod of M -fuzzy (left) Q -modules over a given quantale Q . We introduce and investigate the notion of M -fuzzy Q -submodule of a left Q -module. Also, the notions of M -fuzzy module nuclei and conuclei on a left Q -module are defined, and the elementary properties of both are studied. The relationships between such notions and M -fuzzy Q -submodule are discussed. Finally, the relationship between the category of M -fuzzy Q -modules and the category of (L , M )-quasi-fuzzy topological spaces is discussed.

Keywords: Quantale, semi quantale, left Q-module, module nucleus and module conucleus, 06A06, 54A10, 54A40

DOI: 10.3233/JIFS-190073

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3805-3814, 2019

Authors: Sulaiman, Muhammad | Samiullah, Ismat | Hamdi, A. | Hussain, Zubair

Article Type: Research Article

Abstract: In this paper, we have used a novel initialization strategy to improve Whale optimization algorithm (WOA), which is named as The Improved Whale Optimization Algorithm (IWOA). To evaluate the capability of the algorithm in terms of efficiency and performance, we have implemented it to solve thermal economic multi-objective optimization problems of Plate Fin Heat Exchanger (PFHE). We have investigated the design problem with a single-objective as well as multi-objectives. In single-objective we have minimized the total cost and maximized the effectiveness of PFHE. In multi-objective, we have combined the total cost and effectiveness, with the help of design weights and …a penalty parameter. The sensitivity of IWOA is checked towards the change in population sizes and the target prey numbers. The algorithm was stable in calculating the best values but was variative in number of functions evaluations. The performance of IWOA is compared with Genetic Algorithm (GA), Elitist-Jaya Algorithm (EJA), and modified-TLBO (Teaching Learning Based Optimization). Which show that IWOA has significantly improved the results. The suggested algorithm has less parameters to be set by designers. It converges to the required results quickly and is easy to implement. Similarly, all the experiments suggested that IWOA is applicable to design problems with complex objectives and highly non-linear constraints. Show more

Keywords: Design Engineering Problems, Whale Optimization Algorithm (WOA), Plate Fin Heat Exchanger (PFHE), Constrained Optimization

DOI: 10.3233/JIFS-190081

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3815-3828, 2019

Authors: Zhang, Nian | Yuan, Yin | Fu, Deqiang | Wei, Guiwu

Article Type: Research Article

Abstract: Dual hesitant fuzzy linguistic set consists of linguistic terms, membership hesitancy degrees and non-membership hesitancy degrees, which is widely applied to describe the quantitative and qualitative information in the decision-making problem. In this article, some new power aggregation operators of dual hesitant fuzzy linguistic set on the Archimedean t-conorms and t-norms functions are introduced. Then, the properties of those new operators are studied and the relationships between novel operators and existing ones are discussed. Furthermore, an approach to resolve group decision making problem is described. Finally, an example is used to illustrate the developed approach.

Keywords: Dual hesitant fuzzy linguistic set, power-geometric operator, Archimedean t-conorm and t-norm, group decision making

DOI: 10.3233/JIFS-190098

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3829-3847, 2019

Authors: Tao, Hong-Yu | Zhao, Mei-Ling | Ye, Jun

Article Type: Research Article

Abstract: A neutrosophic cubic set (NCS) can depict single-valued and interval neutrosophic information simultaneously in real life. Then, the NCS concept cannot describe neutrosophic cubic information regarding the assessment problems of two-dimensional universal sets (TDUSs), while a Q-neutrosophic set (Q-NS) can depict neutrosophic information in TDUSs but not describe neutrosophic cubic information in TDUSs. Motivated by the Q-NS and NCS concepts, we need to extend the Q-NS concept to Q-NCS for indicating neutrosophic cubic information in TDUSs. Therefore, this study first proposes a Q-NCS concept, which indicates its truth, falsity, and indeterminacy values independently in TDUSs, and then the basic operations …of Q-neutrosophic cubic elements (Q-NCEs) and some weighted aggregation operators of Q-NCEs, such as a Q-NCE weighted arithmetic averaging (Q-NCEWAA) operator and a Q-NCE weighted geometric averaging (Q-NCEWGA) operator. Next, Q-neutrosophic cubic multi-attribute decision-making (MADM) methods regarding the proposed Q-NCEWAA and Q-NCEWGA operators are proposed under TDUSs and Q-NCS setting. Eventually, an illustrative example shows the applicability of the proposed MADM methods in TDUSs and Q-NCS setting. Show more

Keywords: Q-neutrosophic cubic set, two-dimensional universal sets, Q-neutrosophic cubic element weighted geometric averaging (Q-NCEWAA) operator, Q-neutrosophic cubic element weighted geometric averaging (Q-NCEWGA) operator, decision making

DOI: 10.3233/JIFS-190116

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3849-3864, 2019

Authors: Mohammed, Shehu Shagari | Azam, Akbar

Article Type: Research Article

Abstract:  In this paper, the notion of soft set-valued mappings and E -soft fixed points are introduced. These ideas are used to establish some analogues of classical fixed point theorems in the literature. Some Examples are given to support the hypotheses of the theorems. A few graphical and tabular illustrations are also provided so as to visualize the novel concepts pictorially. Moreover, as an application of one of the presented results, an existence condition for a solution of nonlinear discrete-type delay differential equation is provided.

Keywords: soft set, soft set-valued mapping, E-soft fixed point, delay differential equation 2010 Mathematics Subject Classification: 46S40, 47H10, 54H25.

DOI: 10.3233/JIFS-190126

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3865-3877, 2019

Authors: Liu, Ming | Zhao, Hua | Xu, Zeshui | Ma, Rufei

Article Type: Research Article

Abstract: Interval-valued intuitionistic multiplicative set (IVIMS) has received more and more attention in solving practical problems. The intentions of the decision makers (DMs) can be reflected more objectively by the interval-valued intuitionistic multiplicative numbers (IVIMN), because we use intervals instead of crisp numbers, the unsymmetrical scale instead of the symmetrical scale to show the DMs’ preferences. But we also find the existing problems in the application processes. The representation of the IVIMNs is so complicated that it increases our workload and wastes time. To alleviate this, we use two intuitionistic multiplicative numbers (IMNs) to simplify the IVIMN. Then the simplified IVIMN …(SIVIMN) and the corresponding simplified IVIMS (SIVIMS) are discussed in this paper. On this basis, we propose the operation laws and prove some properties of them. Then the aggregation operators for the simplified interval-valued intuitionistic multiplicative (SIVIM) information are developed, which is used to propose the SIVIM decision making method. At the end of the paper, we use an example to prove the feasibility of the SIVIMNs and verify their advantages. Show more

Keywords: Simplified interval-valued intuitionistic multiplicative number, aggregation operator, simplified interval-valued intuitionistic multiplicative decision matrix

DOI: 10.3233/JIFS-190127

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3879-3895, 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. 37, no. 3, pp. 3897-3923, 2019

Authors: Asif, Muhammad | Shah, Tariq

Article Type: Research Article

Abstract: Accelerated adventures in computer Science and technology has made digital technology, a need of the day. Academicians, researchers, and technologists are anxious to share their secret data through the communication channel along with its security. The security of data, transmission rate, and error correction capability are the fundamental questions against the data transmission through any algebraic code dependent communication channel. Though, data security is always questioned due to the synchronized encoding and decoding algorithms. In this paper, a novel approach is developed to ensure the data security issues occurred due to synchronized encoding-decoding of a BCH code and for data …transmission, a computational technique is designed by which data can be encoded and transmitted by using Field-Linear BCH code or a Ring-Linear BCH code of the same dimension, designed distance and code length. Although the Ring-Linear BCH code is preferable for encoding, on the other hand decoding of data is adept by Field-Linear BCH code. Accordingly, a computational technique of Barlekamp Massey Algorithm is utilized for the purpose. This scheme provides a quick code selection of the desired level of transmission rate and error correction capability during the communication. Thus, it also addresses the dimension issue of primitive BCH code. In addition, for the data security perspective we utilize a BCH code in round key addition and mixed column matrix steps in AES algorithm and then put on this modified AES algorithm to image encryption. The image encryption quality permits to incorporate this alteration in AES. Show more

Keywords: Primitive BCH-code, Galois ring, Galois field, generator polynomial, AES algorithm

DOI: 10.3233/JIFS-190137

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3925-3939, 2019

Authors: Fathalian, M. | Borzooei, R.A. | Hamidi, M.

Article Type: Research Article

Abstract: In this paper, by considering the concept of hesitancy fuzzy magic labeling of a graph, we show that whether any simple graph is hesitancy fuzzy magic labelizing. For this we prove that, any finite path graph, cyclic graph, star graph and by using them, any complete graph and so any connected graph has hesitancy fuzzy magic labelizing. Finally, we give some applications for hesitancy fuzzy magic labeling graphs in plumbing system and traffic flow.

Keywords: Cyclic graph, star graph, connected graph, fuzzy graph, hesitancy fuzzy magic labeling graph

DOI: 10.3233/JIFS-190148

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3941-3955, 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. 37, no. 3, pp. 3957-3968, 2019

Authors: Catak, Ferhat Ozgur | Mustacoglu, Ahmet Fatih

Article Type: Research Article

Abstract: Today, many companies are faced with the huge network traffics mainly consisting of the various type of network attacks due to the increased usage of the botnet, fuzzier, shellcode or network related vulnerabilities. These types of attacks are having a negative impact on the organization because they block the day-to-day operations. By using the classification models, the attacks could be identified and separated earlier. The Distributed Denial of Service Attacks (DDoS) primarily focus on preventing or reducing the availability of a service to innocent users. In this research, we focused primarily on the classification of network traffics based on the …deep learning methods and technologies for network flow models. In order to increase the classification performance of a model that is based on the deep neural networks has been used. The model used in this research for the classification of network traffics evaluated and the related metrics showing the classification performance have been depicted in the figures and tables. As the results indicate, the proposed model can perform well enough for detecting DDoS attacks through deep learning technologies. Show more

Keywords: cyber security, ddos, deep learning, autoencoder

DOI: 10.3233/JIFS-190159

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3969-3979, 2019

Authors: Leninfred, A. | Dhanya, D. | Kavitha, S. | Ashwini, M.

Article Type: Research Article

Abstract: Cloud computing is used for processing resources that are conveyed as an administration over a network and a prototype to enable beneficial on-interest network access to a general loch of configurable reckoning resources which are rapidly provisioned and discharged. While adopting cloud computing, major challenges like resource provisioning, resource allocation and security are arising. Only prevailing resource provisioning algorithm are depending upon single tier application utilizing meta-heuristic methodology. Here, we presented a multi-tier application for provisioning dynamic resources utilizing meta-heuristic methodology like Ant Colony Optimization algorithm (ACO), Simulated Annealing (SA) algorithm and hybrid algorithm which fuses ACO and SA and …also an improved cost based scheduling is used to schedule jobs within the cloud with reduced cost. Implementation outcomes displays the efficiency of provisioning resources using ACO-SA algorithm in multitier application of hybrid cloud is greater than other resource provisioning algorithms in cloud computing. Show more

Keywords: Hybrid cloud, cloud computing, resource provisioning, meta-heuristic technique, hybrid ACO-SA, improved cost based scheduling

DOI: 10.3233/JIFS-190160

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3981-3990, 2019

Authors: Liu, Xiaoyong | Yun, Zhonghua | Yang, Hang | Zhang, Qiang

Article Type: Research Article

Abstract: In this paper, a novel method for fault detection based on an adaptive interval regression model characterized by the upper regression model (URM) and lower regression model (LRM) has been proposed. Applying the proposed method, a confidence band for the measured data, derived in the normal operating conditions of a system, is constructed.The method combines the superiorities of model sparse representation and computational efficiency of linear programming support vector regression (LP-SVR) with some ideas from L 1 -norm on approximation errors. First, the upper and lower L 1 -norms with respect to upper bound approximation error are considered, and the …both norms subject to respective constraints are integrated into LP-SVR to form new upper and lower optimization problems, respectively. Following that, optimization problem corresponding to URM and LRM are solved by linear programming and interval regression model is thus constructed to judge whether the fault occurs or not. The proposed method returns an interval output as opposed to a point output. Finally, the efficacy of this method is demonstrated by applying it on the benchmark Tennessee Eastman problem, and has been compared with conventional techniques such as principal component analysis (PCA), dynamic-PCA (DPCA) and One-Class Support Vector Machine(1-class SVM). It is shown that the proposed method is superior to those approaches in terms of performance measure of detection latency. Show more

Keywords: Fault detection, LP-SVR, L1-Norm minimization, linear programming, interval regression model

DOI: 10.3233/JIFS-190176

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 3991-4001, 2019

Authors: Too, Edna C. | Li, Yujian | Kwao, Pius | Njuki, Sam | Mosomi, Mugendi E. | Kibet, Julius

Article Type: Research Article

Abstract:  Deep learning is a field of Artificial Intelligence that has recently drawn a lot of attention with the desire to build up a quick, automatic and accurate system for image identification and classification. Deep learning serves as a fundamental part of modern computer vision solutions. However, as the architectures become deep and powerful new challenges in the process of training emerge. This includes the computational cost associated with training deep and large networks. In this work, the focus is on pruning and evaluation of state-of-the-art deep convolutional neural network for image-based plant disease and plants species classification. Pruning filters allow …the reduction of parameters by removing unimportant filters and its feature maps. In this paper, the performance of pruned networks is evaluated across three datasets. It is observed that pruned DenseNet with Self-Normalization Neural Network (SNN) approach learns 2x faster compared to the initial DenseNet architecture. Additionally, pruning filters allow the reduction of the number of parameters and FLOPs by approximately 14% and 25% respectively. The aim is to create a fast and efficient model for the purpose of identification of plant diseases. Fast methods are desired for early identifications of diseases before damages occur. The proposed method achieves a satisfactory accuracy performance on PlantVillage, LeafSnap and Swedish-leaf dataset using held-out dataset. Our best pruned model gives an accuracy of 99.24%, 86.64%, and 97.5% on PlantVillage, LeafSnap, and Swedish-leaf datasets respectively. Show more

Keywords: Deep learning, convolutional neural network, pruning, image-based disease classification

DOI: 10.3233/JIFS-190184

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4003-4019, 2019

Authors: Yang, Jie | Yu, Shujuan | Zhang, Yun

Article Type: Research Article

Abstract: The increase of depth is essential for the success of Deep Neural Networks while also leads to the difficulty of training. In light of this, the authors propose a novel multi-layer LSTM model called Highway-DC via introducing Highway Networks (Highway) to Densely Connected Bi-LSTM (DC-Bi-LSTM) which representation of each layer concatenates the output of itself and all preceding layers. Highway is applied to control the volume of input or output of each layer in DC-Bi-LSTM to the next. However, results reveal that Highway-DC shows no improvement over DC-Bi-LSTM, thus an extended version of Highway named Highway II is proposed via …eliminating the multiplicative connections between transform gate and the output in Highway thus preserve the learning of each layer. And the Highway II-based model is named Highway II-DC. Evaluated on 7 benchmark datasets of text classification with compare to DC-Bi-LSTM and other state-of-the-art approaches, results indicate that Highway II-DC shows promising performance for achieving state-of-the-art on 3 datasets and surpassing DC-Bi-LSTM on 6 datasets with faster speed to converge. Besides, it can still enjoy the gain of increased layers with depth up to 30, while DC-Bi-LSTM gets saturated early at a depth of 15. Show more

Keywords: Deep neural networks, Bi-LSTM, text classification, highway

DOI: 10.3233/JIFS-190191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4021-4032, 2019

Authors: Rubio, José de Jesús | Cruz, David Ricardo | Elias, Israel | Ochoa, Genaro | Balcazar, Ricardo | Aguilar, Arturo

Article Type: Research Article

Abstract: Recently, the Adaptive-Network-Based Fuzzy Inference System (ANFIS) is applied in many areas of knowledge, and there are multiple optimization algorithms for its learning. This work shows the design of a novel optimization algorithm for an ANFIS system that learns and classifies the behavior of brain signals between normal and abnormal. For this goal, different types of optimization algorithms for the learning of an ANFIS system are evaluated, such as the backpropagation, the mini-lots, and the Adam algorithm (adaptive moment estimation). As a result, utilizing the ANFIS with Adam and mini-lots provides the most accurate, fastest, and with least computational …costs results. Show more

Keywords: Adam algorithm, ANFIS system, mini-lots, classification of brain signals

DOI: 10.3233/JIFS-190207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4033-4041, 2019

Authors: Xia, Yaowei | Qin, Jiejie

Article Type: Research Article

Abstract: In this paper, a new optimization methodology to assess the designs of the various renewable generation systems of electrical energy is used. This methodology utilizes Whale Optimization Algorithm (WOA) to minimize the cost of the electrical energy generated. The methodology permits to examine and to combine different sources of energy as to touch base at an optimal configuration of the hybrid system. This system is capable of providing energy to the predefined site in an achievable way as indicated by certain specialized and financial criteria. The system incorporates wind generation, photovoltaic generation and batteries for energy storage. The recreation results …have been acquired with the help of MATLAB programming. Moreover, the outcomes of the proposed methodology have been compared with Particle Swarm Optimization (PSO) Algorithm for validation. The recreation results demonstrated the predominance of the proposed methodology. Show more

Keywords: Hybrid renewable energy system, whale optimization algorithm, optimization, photovoltaic, wind, off-grid

DOI: 10.3233/JIFS-190213

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4043-4053, 2019

Authors: Mantas, C.J.

Article Type: Research Article

Abstract: First-order recurrent neural networks can be trained to recognize strings of a regular language. Finite state automata can be extracted from these neural networks. Normally, a search process in the output domain of the neurons is necessary for carrying out this extraction procedure. On the other hand, studies about fuzzy rules extraction from feedforward multilayered neural networks can be considered to define new techniques that transform first-order recurrent neural networks into finite state automata. With these new techniques, a fuzzy description of the action of each neuron can be obtained. From these descriptions, the transition function of the automaton can …be directly found and, in this way, the search process is not necessary. A technique with this approach is presented in this paper. Besides, the used method to extract fuzzy rules from a neuron has the advantage that the inputs of the fuzzy system coincide with the inputs of the neuron. Thus, the fuzzy system is more intuitive. Once the transition function is obtained, the automaton structure can be found with the analysis of the transitions for every state and input from the initial state. Finally, several examples are presented to illustrate the method. Show more

Keywords: First-order recurrent neural networks, regular grammars, fuzzy rules, finite state automata

DOI: 10.3233/JIFS-190215

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4055-4070, 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. 37, no. 3, pp. 4071-4084, 2019

Authors: Sree Priya, S. | Sivarani, T.S.

Article Type: Research Article

Abstract: This paper proposes an optimal control of Induction Motor (IM) drives using a new optimization technique. The optimization technique is the joined execution of both the Improved Moth flame Optimization (IMFO) algorithm and Radial Basis Function Neural Network (RBFNN). The main objective of the proposed strategy is to enhance the control performance of the IM while reducing the Total Harmonic Distortion (THD), eliminating the oscillation period of the stator current, torque, and speed. Here, the IMFO technique is optimized the gain parameters of the PI controller based on the IM speed variation and generates the reference quadrature axis current. By …using the RBFNN, the reference three-phase current for accurate control pulses of the voltage source inverter (VSI) is predicted. The RBFNN is trained by the input motor actual quadrature axis current and the reference quadrature axis current with the corresponding target reference three-phase current. Furthermore, the proposed method control signals are connected with random pulse width modulation (RPWM) scheme and appropriate pulses are generated and applied to the inverter. With the proposed strategy, the control pulses of VSI are optimized and the proposed system offers a reliable solution. The proposed methodology is implemented in MATLAB/Simulink working platform. The performance of the IM drive is assessed by utilizing the comparative analysis with the existing techniques. The result obtained using the proposed optimization strategy showed that; it can provide the optimal control of IM drive. Also, the proposed strategy is effective in minimize the acoustic noise, torque ripple, eliminate the oscillation period with less computation, and reduces the complexity of the algorithm. Show more

Keywords: Induction motor (IM), IMFO, RBFNN, total harmonic distortion (THD), random pulse width modulation (RPWM)

DOI: 10.3233/JIFS-190244

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 3, pp. 4085-4102, 2019