Journal of Intelligent & Fuzzy Systems - Volume 34, issue 1

Authors: Sajjad Ali Khan, Muhammad | Abdullah, Saleem | Yousaf Ali, Muhammad | Hussain, Iqtadar | Farooq, Muhammad

Article Type: Research Article

Abstract: For multi-attribute group decision making (MAGDM) problem, there exist inter-dependent or interactive phenomena among criteria or preference of decision makers, therefor it is not suitable for us to aggregate them by conventional aggregation operators based on additive measures. In this paper based on fuzzy measures an interval-valued Pythagorean fuzzy Choquet integral geometric (IVPFCIG) operator is investigated for multiple criteria group decision making. First, some operational laws on interval-valued Pythagorean fuzzy numbers (IVPFNs) are introduced. Then an interval-valued Pythagorean fuzzy Choquet integral geometric (IVPFCIG) operator is proposed. Moreover, some of its properties are given and discussed in detail. Then Choquet integral-based …distance between interval-valued Pythagorean fuzzy numbers is defined. Combining the IVPFCIG operator with Choquet integral-based distance, an extension of TOPSIS method is developed to deal with multi-attribute interval-valued Pythagorean fuzzy group decision making problems. Finally a numerical example is used to illustrate the developed procedures. Show more

Keywords: Choquet integral, interval-valued Pythagorean fuzzy Choquet integral geometric (IVPFCIG) operator, TOPSIS method

DOI: 10.3233/JIFS-171164

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 267-282, 2018

Authors: Ali, Abbas | Ali, Muhammad Irfan | Rehman, Noor

Article Type: Research Article

Abstract: Conflicts and disagreements are associated with issues related to living beings in particular with humans. Certain steps towards resolving these issues help to minimize conflict. Very few researchers paid their attention towards this important topic to develop some techniques which are based on mathematical methods. Rough set theory as a new and powerful mathematical tool to handle uncertainty in decision making problems was used to study conflict analysis and decision making. Afterwards the Pawlak conflict analysis model was established. Subsequently Deja put forward some questions which are not answered by Pawlak conflict analysis model. In the present paper firstly, we …introduce the notions of soft preference relation and soft dominance relation and analyzed the Middle East conflict. Secondly, we answered the questions posed by Deja. Thirdly, two new techniques of reduction of parameters/attributes are introduced and applied to the Middle East conflict. Show more

Keywords: Conflict analysis, prefernce relation, soft preference relation

DOI: 10.3233/JIFS-171172

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 283-293, 2018

Authors: Sahoo, Sankar | Pal, Madhumangal

Article Type: Research Article

Abstract: In this paper, edge irregular intuitionistic fuzzy graphs, edge totally irregular intuitionistic fuzzy graphs, highly edge irregular intuitionistic fuzzy graphs and highly edge totally irregular intuitionistic fuzzy graphs are introduced. Some properties of an edge irregular intuitionistic fuzzy graphs and highly edge irregular intuitionistic fuzzy graphs are discussed. A equivalent condition under which edge irregular intuitionistic fuzzy graphs and edge totally irregular intuitionistic fuzzy graphs is provided. Also, we introduced a strong edge irregular intuitionistic fuzzy graphs, strong edge totally irregular intuitionistic fuzzy graphs, neighbourly edge irregular intuitionistic fuzzy graphs and neighbourly edge totally irregular intuitionistic fuzzy graphs with suitable …illustrations and established many interesting results on them. Finally, edge irregularity and highly edge irregularity on some intuitionistic fuzzy graphs whose crisp graphs a path and a cycle are studied. Show more

Keywords: Intuitionistic fuzzy graphs, edge irregular intuitionistic fuzzy graphs, strong edge totally irregular intuitionistic fuzzy graphs, neighbourly edge irregular intuitionistic fuzzy graphs

DOI: 10.3233/JIFS-171187

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 295-305, 2018

Authors: Petrauskas, Vytautas | Jasinevicius, Raimundas | Kazanavicius, Egidijus | Meskauskas, Zygimantas

Article Type: Research Article

Abstract: This paper proposes and investigates new possibilities applied to enrich SWOT analysis mechanism using elements of artificial intelligence, and, especially, the computing with words paradigm. This approach is novel due to the originality of the encoding of input words that describe the situation under the investigation in a new functional organization of the SWOT engines, and the originality of the method used for decoding and aggregation of numerical outputs into a verbal form. Promising results of the experimental simulation of the prototype of SWOT+CWW tool are delivered as well.

Keywords: Computing with words (CWW), SWOT analysis, fuzzy logic, membership functions, verbal information, verbal encoding and decoding, fuzzy reasoning

DOI: 10.3233/JIFS-171280

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 307-320, 2018

Authors: Fan, Rui | Wei, Lixin | Li, Xin | Hu, Ziyu

Article Type: Research Article

Abstract: Multi-objective particle swarm optimization (MOPSO) algorithms are shown to have enormous potential in solving multi-objective optimization problems (MOPs). However, most MOPSO is difficult to balance the exploration and exploitation, which may cause some problems to find true Pareto fronts when tackling some complex MOPs. A multi-objective decomposition particle swarm optimization based on completion-checking (C-DMOPSO) is improved in this paper. The updating mode of velocity is changed dynamically according to the algorithm’s evolutionary process, which balances the exploration and exploitation effectively. In addition, simulated binary crossover and opposition-based learning are adopted to improve the diversity, and the archive set strategy is …added to store the optimal solutions. Furthermore, polynomial mutation is performed in archive. The effectiveness of the proposed algorithm is tested by nineteen standard functions, including ZDT, DTLZ and UF, and the experimental results show that C-DMOPSO performs better on most of test problems. Show more

Keywords: Multi-objective optimization, evolutionary algorithms, decomposition, particle swarm optimization

DOI: 10.3233/JIFS-171291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 321-333, 2018

Authors: Liu, Naiqi | Chen, Yanju | Liu, Yankui

Article Type: Research Article

Abstract: Portfolio optimization is concerned with the optimal allocation of limited capital to the available financial assets to achieve a reasonable tradeoff between risk and profit. The main contribution of this paper is to introduce a new risk measure, conditional value-at-risk (CVaR) of fuzzy variable, to build a class of credibilistic mean-CVaR portfolio optimization model. In the proposed credibilistic portfolio optimization model, the CVaR is used as a measure tool to assess market risk resulted from the financial asset price fluctuations. The computational formulas for common triangular, trapezoidal and normal fuzzy variables are established. Under mild assumptions on the uncertain returns, …the proposed credibilistic portfolio optimization model can be turned into its equivalent deterministic mixed-integer parametric programming models, which can be solved by the CPLEX software. The computational results from our numerical experiments demonstrate the efficiency of the proposed CVaR modeling approach as a risk management tool. Show more

Keywords: Portfolio optimization, risk management, financial asset, conditional value-at-risk, credibilistic optimization

DOI: 10.3233/JIFS-171298

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 335-347, 2018

Authors: Li, Chengdong | Ding, Zixiang | Qian, Dianwei | Lv, Yisheng

Article Type: Research Article

Abstract: In many data-driven modeling, prediction or identification applications to unknown systems, linguistic (fuzzy) results described by fuzzy sets are more preferable than the crisp results described by numbers owing to the uncertainties and/or noises existed in the observed data. On the other hand, fuzzy neural network (FNN) provides a powerful tool for providing accurate crisp results, but does not have the ability to achieve linguistic outputs due to its crisp weights. This study extends the crisp weights of FNN to fuzzy ones to obtain linguistic outputs. And, a data-driven design method is proposed to construct this kind of fuzzily weighted …FNN (FW-FNN). The proposed data-driven method includes four steps. Firstly, a fully connected FNN is generated. Then, the SVD-QR method based pruning strategy is presented to realize the structure reduction of the initial FW-FNN. Thirdly, the centers of the Gaussian fuzzy weights in the structure reduced FW-FNN are learned by the least square method. Fourthly, the multi-objective algorithm is utilized to optimize the widths of the Gaussian fuzzy weights to achieve the maximum of the average membership grades of the output fuzzy sets and the minimum of the coverage intervals of the linguistic outputs. To evaluate the proposed FW-FNN and the data-driven method, applications to the nonlinear dynamic system identification, the chaotic time series prediction and the traffic flow prediction are given. Simulation results demonstrate that the linguistic outputs can effectively capture the uncertainties and/or noises in the observed data. It provides us a very useful tool for system modeling, prediction and identification especially when uncertainties and/or noises should be taken into account. Show more

Keywords: Data-driven method, fuzzy neural network, multi-objective optimization, structure reduction

DOI: 10.3233/JIFS-171348

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 349-360, 2018

Authors: Konwar, Nabanita | Debnath, Pradip

Article Type: Research Article

Abstract: In this paper we provide three new type of contractive conditions and establish fixed point theorems related to them in the setting of an intuitionistic fuzzy n -Banach space. Our results improve and generalize several classical results existing in literature. Several examples have been provided in support of non-triviality of our results.

Keywords: Intuitionistic fuzzy n-Banach space, contractive mapping, fixed point

DOI: 10.3233/JIFS-171372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 361-372, 2018

Authors: Łuczak, Maciej

Article Type: Research Article

Abstract: Data normalization is one of the most common processing methods applied to raw data before its subsequent use in data mining algorithms, classification, or clustering methods. Many procedures, particularly those that use any statistical analysis, require that data be normalized in one way or another. In the case of time series a standard method of processing raw data is z-normalization of each time series instance in the data set. For multivariate (multidimensional) time series we z-normalize each dimension (variable) individually. Although normalization brings a lot of advantages, it is easy to find examples of data sets where normalization destroys information …contained in the raw data. In this paper we demonstrate, that for multivariate time series (MTS) both raw and normalized components give some information about the data and the best way of mining it is a combination of them. We focus here on multidimensional time series and their classification using the nearest neighbor method with the dynamic time warping (DTW) distance measure. We construct a parametric distance measure that is a combination of DTW on raw and z-normalized time series data. It turns out that the combined distance measure carries more information about the data than the two distance components separately. By determining an individual parameter for each data set it is possible to obtain a lower classification error than the errors of both component distance measures. We perform experiments on real data sets from many fields of science and technology. The advantage of the combined approach is confirmed by graphical and statistical comparisons. Show more

Keywords: Multivariate time series classification, dynamic time warping, parametric distance measure, combining raw and normalized data

DOI: 10.3233/JIFS-171393

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 373-380, 2018

Authors: Wang, Jian-Qiang | Zhang, Xu | Zhang, Hong-Yu

Article Type: Research Article

Abstract: With the popularity of online hotels booking, increasing attention has been paid to hotel recommendation methods. To provide personalized hotel recommendation for different types of consumers, a new hotel recommendation approach is proposed based on consumers’ online reviews using interval neutrosophic linguistic numbers (INLNs). Meanwhile, this paper puts forward a distance formula of the interval neutrosophic linguistic numbers and the interval neutrosophic linguistic numbers power average (INLNPA) operator, making a further extension on the basis of the INLNs. Moreover, we develop a novel integration model utilizing the INLNPA operator that takes into consideration the relevance of the similar groups. And …we apply the proposed approach to the hotel recommendation. In the case study, we have extracted 1902 online reviews of 10 hotels from TripAdvisor.com to verify the reliability of the proposed approach. The main conclusion of this paper is that the reliability of the hotel ordering can be improved by using the proposed approach. Show more

Keywords: Hotel recommendation, online reviews, interval neutrosophic linguistic numbers, TripAdvisor.com

DOI: 10.3233/JIFS-171421

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 381-394, 2018