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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Kaur, Jagdeep | Kumar, Amit
Article Type: Research Article
Abstract: There are very few methods in literature to deal with fully fuzzy linear fractional programming (FFLFP) problems. In this paper, it is pointed out that in the existing methods (Journal of Applied Mathematics and Computing, 27 (2008), 227-242; Yugoslav Journal of Operations Research, 22 (2012), 41-50) for solving FFLFP problems, an inappropriate ranking property is used which may lead to the erroneous results. To resolve the flaw of the existing methods, a new method is proposed for solving FFLFP problems, and is illustrated with the help of a numerical problem.
Keywords: Fuzzy linear fractional programming, fuzzy optimal solution, fuzzy numbers
DOI: 10.3233/JIFS-151993
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 1983-1990, 2017
Authors: Paul, Susmita | Jana, Debaldev | Mondal, Sankar Prasad | Bhattacharya, Paritosh
Article Type: Research Article
Abstract: Interrelationship between species plays an important role to structure the ecosystem and also controls the dynamics of other species in that ecosystem. Mutualism is the way in which two organisms of different species exist in a relationship where each individual benefits from the activity of the other. In general, in our ecosystem, harvesting is a very frequently used process to exploit biological resources for the welfare of our social and economic purposes. In this article a two species mutualistic harvesting model with imprecise biological parameters has been developed. Due to lack of precise numerical information of the biological parameters such …as population growth and cooperation rate, we consider the parameters of the proposed model with imprecise data as the form of interval in nature. After formulation of this imprecise model we discuss the existence of various equilibrium points and their stability. Then we investigate the effect of MSY policy in this mutualistic system, where the model’s population follow logistic law of growth. We,then try to find the existence of bionomic equilibrium in the said imprecise environment. We also try to carry out the equilibrium solution of the control problem which is derived and solved the optimal harvesting policy. All the analytical findings are illustrated through computer simulation which is followed by discussions and conclusions in an elegant way. Show more
Keywords: Mutualism, harvesting, imprecise parameter, local stability, optimal control, Pontryagin’s maximum principle, MSY
DOI: 10.3233/JIFS-161186
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 1991-2005, 2017
Authors: Thompson, Temitope | Sowunmi, Olaperi | Misra, Sanjay | Fernandez-Sanz, Luis | Crawford, Broderick | Soto, Ricardo
Article Type: Research Article
Abstract: Over 93 million people get ill with sexually transmitted diseases in sub-Saharan Africa. However, research has shown that people with sexually transmitted diseases find it difficult to share their problem with a physician due to societal discrimination in Africa. Due to this problem, we have implemented a medical expert system for diagnosing sexually transmitted diseases (ESSTD) that maintains the anonymity of the individuals. The patients diagnose themselves by answering questions provided by the system. This paper presents the design and development of the system. Forward chaining rules were used to implement the knowledge base and the system is easily accessible …on mobile platforms. The Java Expert System Shell was used for its inference engine and the system was validated by domain experts. It is useful because it helps to maintain anonymity for patients with STD. Show more
Keywords: Artificial intelligence, rule-based expert systems, knowledge base, decision trees, sexually transmitted diseases
DOI: 10.3233/JIFS-161242
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2007-2017, 2017
Authors: Oh, Ju-Mok | Kim, Yong Chan
Article Type: Research Article
Abstract: In this paper, we introduce the notions of L -fuzzy topogenous orders, L -fuzzy topology, L -interior operators and L -closure operators in complete residuated lattices. Moreover, we investigate the relations among L -fuzzy topogenous orders, L -interior operators and L -closure operators. We show that there is a Galois correspondence between the category of separated L -fuzzy interior (resp. closure) spaces and that of separated L -fuzzy topogenous (resp. cotopogenous) spaces.
Keywords: Complete residuated lattice, L-fuzzy topogenous orders, L-interior operators, L-closure operators, L-fuzzy topologies, Galois correspondence
DOI: 10.3233/JIFS-161267
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2019-2032, 2017
Authors: Wang, Xiaomin | Liu, Ying | Li, Piyu | Liu, Jianbo
Article Type: Research Article
Abstract: In this paper, new concepts such as multi-granularity soft rough sets and multi-granularity soft relative attribute reduction are introduced. Basic properties of multi-granularity soft rough approximations are presented and illustrated by examples. A multi-granularity soft decision system is constructed based on multi-granularity soft rough sets. Furthermore, an algorithm for multi-attribute decision-making problems is proposed. Finally, the validity of this method is proved by the application of the component retrieval problem.
Keywords: Soft rough set, multi-granularity soft rough set, multi-granularity soft decision system, multi-granularity soft relative attribute reduction, decision rule
DOI: 10.3233/JIFS-161498
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2033-2045, 2017
Authors: Ding, Shuchen | Huang, Xianlin | Ban, Xiaojun | Lu, Hongqian | Zhang, Hongyang
Article Type: Research Article
Abstract: Underactuated mechanical systems have their own difficulties within the control criterion. As a particular and complex underactuated mechanical system, underactuated truss-like robotic finger(UTRF) is studied by establishing its dynamic model. The control problems include high nonlinearity, model inaccuracy and uncertainties. Type-2 fuzzy logic control method is supposed to be a proper way to solve these problems, because fuzzy logic control itself does not depend on an accurate model of the controlled object, and type-2 fuzzy logic control is able to handle uncertainties. Based on a brief introduction on type-2 fuzzy logic systems, an interval type-2 fuzzy logic controller is designed …for UTRF to accomplish the goal of stabilization in its equilibrium point. As an extension of the type-1 fuzzy, the performances of the proposed controller are compared with the type-1 one case to show the advantages of the type-2 fuzzy. Simulation results show that the designed interval type-2 fuzzy logic controller is correct and effective and has better performances than that of type-1 fuzzy control. Show more
Keywords: Underactuated robot, nonlinear system, fuzzy logic system, type-2 fuzzy logic control
DOI: 10.3233/JIFS-161538
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2047-2057, 2017
Authors: Wang, Youwei | Feng, Lizhou | Li, Yang
Article Type: Research Article
Abstract: In text classification field, many classifiers cannot deal with the features with large dimensions, thus it is very important to filter the redundant information from the original feature space efficiently and achieve the features with best qualities. On this basis, a new two-step based feature selection method is proposed in this paper. Firstly, some definitions (word semantic correlation, set semantic correlation, semantic correlative and semantic correlative set) are introduced, and the algorithm of generating the semantic correlative sets is given. Secondly, the process of the two-step based feature selection method is described: in the first step, a feature subset is …obtained by using an optimal feature selection method, and a set of semantic correlative sets is generated by using the selected feature subset; in the second step, the redundant information of the selected features is filtered by using the generated semantic correlative sets. Finally, in order to avoid local optimum when searching the best threshold, the conception of memory recall position is introduced and an improved memory recall mechanism based fruit fly optimization algorithm is proposed. In the experiments, two typical classifiers: support vector machine and naïve bayes are used on four datasets: Reuters50, SMSSPAS, WebKB and 20-Newsgroups, and the 10-cross validation is carried out when the measurements of F1 and receiver operating curve are used. Experimental results show that the proposed method achieves higher accuracy than several representative traditional feature selection methods and runs faster than typical mutual information based feature selection methods, illustrating its effectiveness on achieving the best features in text classification filed. Show more
Keywords: Feature selection, redundant information, feature space, fruit fly optimization algorithm, support vector machine, receiver operating curve
DOI: 10.3233/JIFS-161541
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2059-2073, 2017
Authors: Ahmadizar, Fardin | Rabanimotlagh, Ahmad | Arkat, Jamal
Article Type: Research Article
Abstract: The group shop scheduling (GSS) problem is a general formulation that includes the job shop and the open shop scheduling problems. This paper is the first dealing with a GSS problem with random release and processing times and fuzzy due dates. While release and processing times are assumed to be random variables with known distributions, as in many real-world situations, job due dates are considered to be fuzzy tolerating a certain amount of delay. The objective is to maximize the expected total degree of satisfaction with respect to the fuzzy due dates. The problem is formulated as a stochastic disjunctive …program and then two solution approaches are developed for it, both of which act within an ant colony optimization (ACO) framework. In the first approach, to estimate the performance of a constructed schedule, each random variable is replaced by its expectation, whereas in the other approach following a simulation optimization procedure, a discrete event simulation model is employed to estimate the performance of a schedule. The proposed approaches are then compared through computational experiments. Show more
Keywords: Group shop scheduling, random release times, random processing times, fuzzy due dates, ant colony optimization, simulation
DOI: 10.3233/JIFS-16164
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2075-2084, 2017
Authors: Zeng, Zhen
Article Type: Research Article
Abstract: The enterprise technological innovation is a creative process. The uncertainty risk mainly includes the environment, technology, market, and risk management. At the same time, the process of enterprise technological innovation is a dynamic process. In the initial stage of the technical innovation, the enterprise must evaluate and select the innovation project and also consider the social and economic benefits and the development of technology with the combination of their own development strategies; at the end select the most suitable for the development of innovative investment projects. In this paper, we study on the multiple attribute decision making problems with fuzzy …number intuitionistic fuzzy information. Firstly, we analyze several operations on the fuzzy number intuitionistic fuzzy sets. Firstly, we develop the induced fuzzy number intuitionistic fuzzy Hamacher correlated average (IFNIFHCA) operator. Then, we use the IFNIFHCA operator to solve multiple attribute decision making with the fuzzy number intuitionistic fuzzy information. Finally, an illustrative example for evaluating the technological innovation capability in high-tech enterprises is given to verify the developed approach. Show more
Keywords: Comprehensive evaluation, fuzzy number intuitionistic fuzzy sets, Hamacher aggregation operators, induced fuzzy number intuitionistic fuzzy Hamacher correlated average (IFNIFHCA) operator, technological innovation capability, high-tech enterprises
DOI: 10.3233/JIFS-161812
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2085-2094, 2017
Authors: Agarwal, Shikha | Ranjan, Prabhat
Article Type: Research Article
Abstract: Dimensionality reduction of high dimensional data still perceives challenges and hence, it is pertinent to introduce new methods or revamp existing methods. In this study, a new ternary particle swarm optimization (TPSO) algorithm has been proposed, in which particle is a string of “trit”, which is the smallest unit of information. Ternary string is made up of (0, 1 and #). 0, 1 and # are representatives of rejection, acceptance and intermediate (uncertain) states respectively. Since trit is the smallest unit of information therefore, # trit brings the characteristics of quantum theory in the search. This provides the better exploration …of feature leading to global optimum solution. This method belongs to wrapper category of feature selection method since it has k nearest neighbor classifier as performance evaluator. The TPSO has been applied in two phases. The second phase is included in the system in a top down information processing fashion, in which big system of information is broken down to have insight into the hidden important information. In first phase TPSO is applied multiple times on each data set. In second phase optimum features are retrieved by applying LBUB, EXP_SEARCH and VOTE_MERGE methods. Experimental results on bench marking datasets show that the proposed methods are promising to handle feature selection in high dimensional space. Show more
Keywords: Particle swarm optimization, feature selection, dimensionality reduction, gene expression data, classification
DOI: 10.3233/JIFS-161956
Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2095-2107, 2017
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