Journal of Intelligent & Fuzzy Systems - Volume 33, issue 4

Authors: Keshavarz, Hamidreza | Abadeh, Mohammad Saniee

Article Type: Research Article

Abstract: Sentiment analysis deals with classifying the opinions in text. Twitter is the most popular microblogging platform in social media, with hundreds of millions of tweets posted every day. A considerable number of tweets contain opinions. The goal of this paper is to classify the polarity of the tweets into positive and negative classes using dynamic sentiment lexicons based on frequencies of words in positive and negative classes. We extract five meta-level features incorporating the generated sentiment lexicons and classify the text based on them. We also incorporate some previously known lexicon-based and corpus-based features. The proposed method is assessed on …six datasets, and outperforms previous papers on accuracy on four datasets, and on f-measure on three datasets. This method generates sentiment lexicons dynamically. The changes of meanings of words can be captured by the generated lexicons. Our research produces very promising results in sentiment analysis in terms of accuracy and f-measure. The accuracy of our method on four datasets and the f-measure of our method on three datasets are higher than 85%. Show more

Keywords: Sentiment analysis, opinion mining, sentiment lexicons, twitter

DOI: 10.3233/JIFS-16562

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2223-2234, 2017

Authors: Zhai, Hao | Zhang, Jianguo

Article Type: Research Article

Abstract: In recent advances for fuzzy dynamic modeling problem, two-stage equivalent value (EV) programming as an alternative optimization technology has been put forward to make the problem tractable in fuzzy decision-making systems. The main purpose of this paper is to provide a new methodology for computing fuzzy EV programming problem with a finite number of second-stage realizations, which is analytic and systematic rather than approximate strategy. Firstly, we provide two EV definitions in the sense of Lebesgue-Stieltjes (L-S) integral, where two L-S measures are characterized by different nondecreasing functions. Meanwhile, several properties of EV operator are presented to facilitate us to …model with this operator. Secondly, for two-stage fuzzy EV programming problem, the second-stage feasibility set and fuzzy elementary feasibility set are defined. Moreover, we demonstrate the convexity of the second-stage feasibility set and recourse function, and establish the supporting hyperplane of the recourse function. Then, a new plane decomposition algorithm is developed to solve two-stage fuzzy EV programming problem, which adds iteratively feasibility and optimality cuts to the relaxed formulation of its first-stage programming problem. Finally, an illustrative example shows the solution details, and demonstrates the applicability of this proposed method. Show more

Keywords: Equivalent value, Lebesgue-Stieltjes integral, plane decomposition algorithm, supporting hyperplane, two-stage fuzzy programming

DOI: 10.3233/JIFS-17084

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2235-2247, 2017

Authors: Rao, Peddi Phani Bushan

Article Type: Research Article

Abstract: This paper presents a new method on ranking fuzzy numbers by identifying the degree to which one fuzzy number dominates the other through a total dominance function, developed by using a few number of α - cuts that fall within the centroid range of the referential triangular fuzzy number and involving optimistic perspective of the decision maker. This method is very useful in ranking large quantity fuzzy numbers and fuzzy numbers whose membership functions are not known in prior.

Keywords: Fuzzy numbers, centroids, alpha cut, index of optimism

DOI: 10.3233/JIFS-171119

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2249-2258, 2017

Authors: Sisodia, Dilip Singh

Article Type: Research Article

Abstract: Relational Medoid based fuzzy relational clustering (FRC) algorithms perform better than center based FRC. However, in medoid based FRC the selection of medoid is solely random and sometimes lead to inconsistent results. In this paper, a subtractive medoids selection based fuzzy relational clustering (SMS-FRC) method is proposed. In SMS-FRC algorithm inherent geometry and density of pairwise dissimilarity values are preferred over random initial values of medoids. The SMS-FRC is applied to identify clusters of user sessions from server log data, based on their browsing behavior. The concept of augmented sessions is used to derive the page relevance based intuitive augmented …dissimilarity matrix. The experiments are performed on a publicly available log data from NASA web server. The generated clusters are evaluated using various fuzzy cluster validity measures, and results are compared with relational fuzzy c-medoids (RFCMdd) clustering algorithm. The results suggest the quality of fuzzy clusters discovered using SMS-FRC clustering is better than that of those obtained with the relational fuzzy c-medoids algorithm. Show more

Keywords: Relational fuzzy clustering, subtractive clustering, fuzzy validity measures, intuitive augmented similarity, user sessions, a user profile

DOI: 10.3233/JIFS-17122

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2259-2268, 2017

Authors: Song, Zongyun | Xiao, Xinli | Niu, Dongxiao

Article Type: Research Article

Abstract: Under the current situation, distributed power generation becomes key solutions to the problems of environmental pollution and resources shortage that the electricity industry is facing. Rational power generation programming schemes will reduce energy consumption, and optimize energy structure on the premise of meeting the increasing requirements for electric energy. The multi-objective programming model was established to optimize economical and technical objectives of distributed generation system (DGS) containing waste incineration generation (WIG) and hybrid energy storage equipment (HESE), and then memorized-firefly algorithm (M-FA) is introduced to determine the model and installed capacity of various power generation units in distributed generation system. …The case study demonstrated that the proposed programming model can obtain rational solutions with taking various objectives and constraints into consideration, and the M-FA shows the abilities of global search and better convergence in solving power generation programming problems, which will provide theoretic and practical references for the multi-objective programming problems of distributed generation system. Show more

Keywords: Distributed generation system, multi-objective programming, waste incineration generation, hybrid energy storage equipment, memorized-firefly algorithm

DOI: 10.3233/JIFS-17168

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2269-2279, 2017

Authors: Fan, ChangXing | Ye, Jun

Article Type: Research Article

Abstract: This paper introduces a Refined-Interval Neutrosophic Set (R-INS) as an extension of a Refined-Single Valued Neutrosophic Set (R-SVNS) and puts forward the decision-making models based on the Cosine Measures of R-SVNSs and Refined-Interval Neutrosophic Sets (R-INSs). By the cosine measure between every alternative and the ideal alternative, all the alternatives can be ranked with the measure values, and the best one of all alternatives can be selected. The proposed methods for multiple attribute decision making (MADM) are more clear (more refined) and the refined evaluation results are credible, so the proposed decision-making models are very suitable for handling with the …decision-making problems with refined neutrosophic information. Show more

Keywords: Refined-single valued neutrosophic set, refined-interval neutrosophic sets, cosine measure, decision making, multiple attribute

DOI: 10.3233/JIFS-17270

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2281-2289, 2017

Authors: Qin, Keyun | Yang, Jilin | Liu, Zhicai

Article Type: Research Article

Abstract: As the theoretical foundation of fuzzy control, fuzzy reasoning has been extensively studied. This paper is devoted to the discussion of the similarity property of similarity-based fuzzy reasoning method, triple I fuzzy reasoning method and fuzzy similarity inference method. The similarity degrees between the inferred conclusions of these fuzzy reasoning methods and the consequent part of fuzzy inference rules are analyzed and evaluated. Based on these similarity degrees, the monotonicity, the reversibility and the approximation property of these fuzzy reasoning methods are examined.

Keywords: Fuzzy set, similarity measure, similarity-based fuzzy reasoning method, triple I method, left-continuous t-norm

DOI: 10.3233/JIFS-17333

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2291-2303, 2017

Authors: Elhoseny, Mohamed | Shehab, Abdulaziz | Yuan, Xiaohui

Article Type: Research Article

Abstract: Robots have recently gained a great attention due to their potential to work in dynamic and complex environments with obstacles, which make searching for an optimum path on-the-fly an open challenge. To address this problem, this paper proposes a Genetic Algorithm (GA) based path planning method to work in a dynamic environment called GADPP. The proposed method uses Bezier Curve to refine the final path according to the control points identified by our GADPP. To update the path during its movement, the robot receives a signal from a Base Station (BS) based on the alerts that are periodically triggered by …sensors. Compared to the state-of-the-art methods, GADPP improves the performance of robot based applications in terms of the path length, the smoothness of the path, and the required time to get the optimum path. The improvement ratio regarding the path length is between 6% and 48%. While the path smoothness is improved in the range of 8% and 52%. In addition, GADPP reduces the required time to get the optimum path by 6% up to 47%. Show more

Keywords: Robot path planning, Bezier Curve, Genetic Algorithm, Wireless Sensor Network

DOI: 10.3233/JIFS-17348

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2305-2316, 2017

Authors: Li, Zhiming | Sheng, Yuhong | Teng, Zhidong | Miao, Hui

Article Type: Research Article

Abstract: This paper extends the classical susceptible-infected-susceptible (SIS) epidemic model from a deterministic framework to an uncertain one and formulates it as an uncertain differential equation (UDE) for SIS epidemic model. The solutions of UDE SIS model and the corresponding α-paths are obtained. Under some conditions, these α-paths have the convergence properties. Further, a general uncertain SIS model is introduced. It’s solutions and α-paths are given. An algorithm is provided to solve α-paths and uncertain distributions of the UDE SIS model, including some examples.

Keywords: Liu process, uncertain differential equation, contour process, SIS epidemic model, α-path

DOI: 10.3233/JIFS-17354

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2317-2327, 2017

Authors: Abed, Saad Adnan | Rais, Helmi Md

Article Type: Research Article

Abstract: Graph domination is one of the NP-Complete problems that cannot be solved exactly in polynomial time. Hence, we propose a stochastic approach to tackle the minimum dominating set problem (MDS). The main aim of MDS is to find the minimum number of nodes that covers all other nodes in a graph. Thus, we present the problem in binary sequence to activate a node to be a dominator by setting it to the value of 1, or deactivate it by assigning its value to 0. In this paper, the stochastic search represented by hybrid swarm intelligence algorithm to find the smallest …set of nodes that dominate the graph. This method uses population-based approach called bat algorithm (BA) which explore a wide area of the search space, thus it is capable in the diversification procedure. However, population-based algorithms are not good in exploiting the search space in comparison to single-solution based methods, therefore we included simulated annealing (SA) algorithm to balance between exploitation and exploration in order to reach a best possible solution. Our proposed method was experimented on benchmark datasets, which yielded results comparable to the state-of-the-art MDS methods. It can be concluded that the proposed method is an effective solution for MDS problem. Show more

Keywords: Minimum dominating set, meta-heuristics, hybrid methods, bat algorithm, simulate annealing

DOI: 10.3233/JIFS-17398

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 4, pp. 2329-2339, 2017