Journal of Intelligent & Fuzzy Systems - Volume 36, issue 6

Authors: Sharif, Mohammad | Alesheikh, Ali Asghar | Tashayo, Behnam

Article Type: Research Article

Abstract: Movements of objects take place in different contexts and their trajectories are highly influenced by the contexts. Several studies have been conducted in the last decade on similarity measuring of raw trajectories, but very few have used context information in this process. Because the context information is collected from multifarious sources, it is qualitatively and quantitatively heterogeneous and uncertain. Therefore, the current distance functions are unable to measure the similarities between trajectories by considering the heterogeneous context information. This article presents a new context-aware hybrid fuzzy model, named CaFIRST, to measure the similarity of trajectories by considering not only the …spatial footprints of moving objects but also various types of internal and external context information. CaFIRST is able to handle multi-size trajectories that are contextually enriched by both quantitative (numeric) and qualitative (descriptive) values. The performance of CaFIRST was examined using two real data sets, obtained from pedestrians and cyclists in New York City, USA. The results showed the robustness of CaFIRST for quantifying the commonalities in multivariate trajectories and its sensitivity to small alterations in context information. Furthermore, the effects of internal and external context information on similarity values are shown to be remarkable. Show more

Keywords: Trajectory, similarity measure, context-awareness, multi-objective optimization, hybrid fuzzy inference system (HFIS)

DOI: 10.3233/JIFS-181252

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5383-5395, 2019

Authors: Adaraniwon, Amos Olalekan | Omar, Mohd Bin

Article Type: Research Article

Abstract: This article considers an EOQ model for a delayed deteriorating item in which the demand varies with time and follows a power pattern. Shortages are allowed with partially backlogged and lost sales. We develop a mathematical model for the problem.The proposed model aims at minimizing the total inventory cost which depends on the length of time with positive and negative inventory level. Numerical examples with the effect of various changes in some possible parameters combination of the model are given to illustrate the effectiveness of the model and to gain some managerial decision.

Keywords: Deterioration, delayed, power demand, lost sales, shortages

DOI: 10.3233/JIFS-181284

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5397-5408, 2019

Authors: Nie, Ru-Xin | Wang, Jian-Qiang | Wang, Tie-Li

Article Type: Research Article

Abstract: Preference relations as information representation form are widely used to manage complexity and uncertainty in practical decision-making cases. Intuitionistic trapezoidal fuzzy numbers (ITrFNs) can convey more fuzzy messages than other fuzzy numbers. This paper defines intuitionistic trapezoidal fuzzy preference relations (ITrFPRs) to adequately describe the preferences of decision makers (DMs). To optimize the decision-making selection process, this paper constructs a three-cycle decision-making selection mechanism with ITrFPRs. To build this mechanism, firstly, a possibility degree formula is presented to rank ITrFNs. Secondly, ITrFPRs, consistent ITrFPRs, acceptable consistent ITrFPRs and a new consistency index are defined. Thirdly, a novel consistency transformation method …is built to elevate the consistency of ITrFPRs. Fourthly, considering the relationship between consistency conditions and priority weight, a priority weight derivation method is exploited to derive intuitionistic trapezoidal fuzzy weights. Ultimately, a three cycle selection mechanism integrated with consistency checking, consistency improvement and priority weight derivation procedures is constructed and applied into the case of trip itinerary selection. Sensitive and comparative analyses are carried out to illustrate the effectiveness and applicability of the proposed mechanism. Show more

Keywords: Intuitionistic trapezoidal fuzzy preference relation, consistency, priority weight, decision-making

DOI: 10.3233/JIFS-181306

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5409-5422, 2019

Authors: Peng, Hu | Deng, Changshou | Wu, Zhijian

Article Type: Research Article

Abstract:  As a new and promising swarm intelligence algorithm, brain storm optimization (BSO) has drawn more attention of researches and has been successfully applied to solve the real-world optimization problems. However, too many parameters make the algorithm more complex and greatly limit the convergence performance. Thus, this paper proposed a novel BSO variant, named self-adaptive BSO with p best guided step-size (SPBSO), in which a simple self-adaptive strategy is employed to choose a creating strategy in a random manner rather than depending on several adjustable parameters. In addition, the p best guided step-size and dynamic clustering number are used to accelerate …the convergence speed. The experimental studies have been tested on a set of widely used benchmark functions (including the CEC 2014 problems). Experimental results and comparison with the state-of-the-art BSO variants and some recently proposed PSO and DE algorithms, have proved that the proposed algorithm is competitive. Show more

Keywords: Brain storm optimization, global optimization, self-adaptive strategy, pbest guided step-size

DOI: 10.3233/JIFS-181310

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5423-5434, 2019

Authors: Xie, Zhenping | Jiang, Siwei | Zhou, Jianian

Article Type: Research Article

Abstract:  For non-intrusive power load monitoring problem, the key trouble is that there contains complex multiple types of appliances in a power load environment. In this study, two key suppositions are firstly introduced: (1) the signal characteristics should keep stable for each load appliance with a same running state in continuous times; (2) there is at most one running state change at an enough small monitoring period. Then, we consider that a probabilistic label value for each possible load can be evaluated according to a probabilistic clustering principle. Moreover, a coupled allocation mechanism on mixed probabilistic labels is introduced, in which …an iterative filtering strategy is designed to estimate the optimal state combination of different loads. By performing professional load scenario simulations, the algorithm performance is effectively examined. The corresponding results indicate that better comprehensive performance can be obtained by the proposed method compared to the latest hidden Markov model and fuzzy clustering method. Show more

Keywords: Noninvasive power load monitoring, coupled allocation, probabilistic clustering, hidden Markov model, fuzzy clustering

DOI: 10.3233/JIFS-181319

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5435-5442, 2019

Authors: Karasan, Ali | Bolturk, Eda | Kahraman, Cengiz

Article Type: Research Article

Abstract: Neutrosphic sets define the uncertainty with three parameters, namely truthiness, indeterminacy and falsity. COmbinative Distance-based ASsessment (CODAS) method computes the Euclidean as the primary measure and Hamming distances as the secondary measure to assess alternatives based on predetermined criteria. In this paper, CODAS method is extended to its interval-valued neutrosophic CODAS version for handling the vagueness and impreciseness in human thoughts. A fuzzy inference system can be used as a decision making process of mapping from a given input to an output using fuzzy logic. The inputs of the used ordinary fuzzy Mamdani type inference system are crisp while the …rules are fuzzy. The applicability of the proposed methodology is illustrated through the assessment of livability index of urban districts. Sensitivity analysis demonstrates the robustness of the decision-making methodology. Show more

Keywords: Livability index, neutrosophic sets, fuzzy inference system, CODAS, decision making

DOI: 10.3233/JIFS-181322

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5443-5455, 2019

Authors: Shvedov, Alexey S.

Article Type: Research Article

Abstract: Linear regression models with fuzzy independent variables and crisp parameters are considered in this paper. The constant term may be fuzzy. It is determined using calculus of variations. Sometimes linear regression models do not satisfy the conditions under which the least squares estimator should be consistent. It is known from econometrics that in some cases instrumental variables can be used to find a consistent estimator for such models. In this paper, an instrumental variables estimator of a linear fuzzy regression model is constructed and consistency of the estimator is established.

Keywords: Fuzzy regression, fuzzy random variables, consistent estimators, instrumental variables

DOI: 10.3233/JIFS-181327

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5457-5462, 2019

Authors: sadeghi, Hossein | Motameni, Homayun | Ebrahimnejad, Ali | Vahidi, Javad

Article Type: Research Article

Abstract: Since data mining plays a key role in a variety of research areas including audio processing, text processing, and machine translation, research efforts in the Persian language has been seriously challenging. Due to difficulties such as clinging letters and absence of vowels in words, research in the Persian language has progressed at a far slower pace than in the English language. In spite of all complexities, it is indispensable to conduct further studies on the Persian morphology. Moreover, one of the widely adopted techniques is statistical, where a major drawback is intensive computational load. For that purpose, this research project …intended to propose a “classified, statistical” method. Compared to the solely statistical method, the new one offers the advantage of 80% reduction in computation load at each stage against previous stages. This in turn enhances the essential computation speed. The results indicated that sequencing and classification of stages in Persian proved more successful by about 13% against the combined fuzzy and classified method. Show more

Keywords: Fuzzy system, classification, morphology, independent functions, dependent functions

DOI: 10.3233/JIFS-181330

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5463-5473, 2019

Authors: Trisal, Sushil Kumar | Kaul, Ajay

Article Type: Research Article

Abstract: Social networks or social media is an online platform for billons of people around the world. This platform makes it easier for the people to have conversations, share information, share videos, instant messaging, create virtual world and more. The most dominant form of interaction on social media is by the text messaging. To detect the emotions from these text messages is not a difficult job for the humans as they are linked with emotions themselves. But to detect the emotions from these text messages by the computer is a difficult job to perform. Various models like fuzzy model, vector space …model, keystroke dynamics, character n-gram models etc have been proposed in the literature for the detection of emotions but every model has its limitations and drawbacks. In this study a novel K-RCC (Reduced Computational Complexity) emotion detection model is proposed which is based on the K Nearest Neighbor (KNN) algorithm. The K-RCC algorithm reduces the computational complexity and incorrect classification rate which is the main drawback of the KNN algorithm. The computational complexity of the KNN algorithm is reduced up to some extent by the K-d Tree algorithm but on the cost of increased incorrect classification rate. The systematic performance analysis of K-RCC is carried out with four Machine learning classification algorithms for the detection of human emotions from tweets collected from social media site twitter. The emotions are classified under six emotional classes such as disgust, fear, joy, sadness, anger, and shame. The K-RCC performs better both in terms of reducing the computational complexity and incorrect classification rate and detection of human emotions. Show more

Keywords: Affective computing, cognitive process, emotions, human behavior, machine learning, social media.

DOI: 10.3233/JIFS-181336

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5475-5497, 2019

Authors: Zeng, Qing-Song | Huang, Xiao-Yu | Xiang, Xian-Hong | He, Junhui

Article Type: Research Article

Abstract: This paper addresses the problem of Face Recognition based on Image Set (FRIS) by kernel learning and proposed an extended kernel discriminant analysis framework for FRIS. By support vector machine learning, an image set from the original input space is mapped into the model space and described with Support Vector Domain Description (SVDD) to handle the underlying non-linearity in data space. In model space, a hyper-sphere encloses most of the mapped data, and the outliers lie outside the hyper-sphere. By exploring an efficient metric for the data domains in model space, we derive a kernel function maps the …data from the model space to a high-dimensional feature space, to which many Euclidean algorithms can be generalized. The proposed method is evaluated on face recognition tasks. Comparisons with several state-of-the-art FRIS methods are performed on ChokePoint and CMU MoBo video database. The proposed methods have demonstrated promising performance. Show more

Keywords: support vector domain description (SVDD), graph embedding, discriminant analysis, kernel method, face recognition

DOI: 10.3233/JIFS-181347

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 6, pp. 5499-5511, 2019