Journal of Intelligent & Fuzzy Systems - Volume 36, issue 3

Authors: Ju, Hongmei | Hou, Qiuling | Jing, Ling

Article Type: Research Article

Abstract: By using fuzzy set theory (FS), interval-valued fuzzy set theory (IVFS) and nonparallel support vector machine theory (NPSVM), the fuzzy nonparallel support vector machine (F-NPSVM) and interval-valued fuzzy nonparallel support vector machine (IVF-NPSVM) are constructed. Both F-NPSVM and IVF-NPSVM consider the membership degree of the training points in their models and the difference is the method to determine them. Then the solutions to them are derived. The experiments on both artificial data set and benchmark data sets show that most of the classification results by using the F-NPSVM and IVF-NPSVM are more accurate than NPSVM, support vector machine (SVM), interval-valued …fuzzy support vector machine (IVF-SVM), generalized eigenvalue proximal support vector machine (GEPSVM) and twin support vector machine (TWSVM). Finally, Friedman test is used to verify that there is a significant difference between the two new models and the previous ones. Show more

Keywords: Classification, fuzzy, interval-valued fuzzy, nonparallel support vector machine

DOI: 10.3233/JIFS-18702

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2677-2690, 2019

Authors: Rajeswari, A.M. | Deisy, C.

Article Type: Research Article

Abstract: Education is a collective intelligence system where a group of persons ranging from students to management thinks and work together to achieve institutions’ goals. The primary goal of every institution is to accomplish excellent end-semester examination results. A good result is achieved through proper training given by the educators and in response to the performance of students in the examination. Training is cost accounting, whereas students’ performance is unpredictable. Outlier analysis in the education system has been stipulated in recent decades to predict the students’ uncertain behavior in learning activities which are utilized to alert the education systems. Fuzzy Logic …System can handle such uncertainties in learning activities. The major issues that affect the accuracy of fuzzy based outlier detection methods are fixing appropriate membership function and validating the fuzzy rules before extracting outliers. To remedy these issues the proposed Fuzzy Temporal Outlier Detection (FTOD) method detects outliers from mid-semester examination results using fuzzy logic based associative classifier with optimal membership functions. The resultant outliers distinguish the slow learners from spurious-slow learners with high accuracy than the existing FARIM and modified-FARIM algorithms. Thus, educators can provide cost-effective training to enrich the slow learners’ cognition to score high in end-semester examinations. Show more

Keywords: Education system, outlier detection, fuzzy association rules, optimal membership function, associative classification, lift measure

DOI: 10.3233/JIFS-18748

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2691-2704, 2019

Authors: Wang, Kai | Shi, Fu-Gui

Article Type: Research Article

Abstract: In this paper we give a natural method of constructing a bi-stratified [0, 1]-convexity by a [0, 1]-valued interval operator, where the concept of bi-stratified [0, 1]-convexities is firstly introduced. And its convex hull operators can be characterized by [0, 1]-valued interval operators. Finally, we discuss the relationship between bi-stratified [0, 1]-convexities and [0, 1]-valued interval operators from a categorical aspect.

Keywords: [0, 1]-valued interval operator, fuzzy convexity, bi-stratified fuzzy convexity, convex hull operator

DOI: 10.3233/JIFS-18891

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2705-2713, 2019

Authors: Rizvi, Naela | Ramesh, Dharavath

Article Type: Research Article

Abstract: Cloud computing relates to the storage and accessing of data as a service from Internet for any organizational infrastructure at-any-time. The delivery of some of the services related to computing such as servers, networking, storage, software, etc., is made possible with the use of cloud computing. Companies offer these services in terms of cloud service providers (CSPs) who charge for the services they provide to the users. When a request is made to use the services, the service provider allocates a feasible number of virtual machines (VMs). Determining optimum amount of resources required at runtime to satisfy the user’s …request is not a trivial task. Therefore, in cloud ecosystem the cardinal issue is the management of resource allocation to an application in order to abide by the service level agreements (SLAs). The fundamental objective of cloud service management is to design a self-adjustable auto-scalar to respond to elastic workload and optimizing the allocation of resources with reduced cost. The notable issue is how and at what time resources are to be allocated/de-allocated in order to follow agreed SLAs. In this paper, we propose a resource provisioning framework based on the integrated concepts of autonomic computing with Fuzzy Q Learning and Chebyshev’s Inequality principle. The concept of auto-scaling mechanism is commonly implemented in four phases of proposed autonomic MAPE loop framework: Monitoring, Analysis, Planning and Execution. The proposed framework follows the control MAPE loop structure with the inclusion of Chebyshev’s inequality for prediction in the analysis phase and fuzzy Q-learning in planning phase, where human intervention in the form of fuzzy rules ensures efficacious provisioning of VMs. A comparative analysis has been performed with a different combination of (i) LRM in the analysis phase with FBQ-LA in planning phase, ii) Chebyshev’s Inequality in the analysis phase with FBQ-LA in planning phase, and iii) Chebyshev’s Inequality in the analysis phase with Q-Learning in planning phase. Experimental results prove that the proposed autonomic model based on Chebyshev’s inequality and FBQ-LA outperforms the existing model in terms of improved VM provisioning, minimized costs as well as reduction in response time. Show more

Keywords: Resource provisioning, autonomic computing, MAPE loop, fuzzy Q-learning, Q-learning

DOI: 10.3233/JIFS-18828

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2715-2728, 2019

Authors: Karaaslan, Faruk

Article Type: Research Article

Abstract: In this study, hesitant fuzzy graph (HFG) structure and some concepts related to HFGs such as homomorphism, isomorphism, weak isomorphism and co-weak isomorphism are introduced. Also, operations of Cartesian product, direct product, lexicographical product and strong product between two HFGs are defined, and examples are given related these operations. Finally, a decision making algorithm and an application of HFGs in decision making are given.

Keywords: Hesitant fuzzy set, hesitant fuzzy graph, product operations, homomorphism, isomorphism, decision making

DOI: 10.3233/JIFS-18865

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2729-2741, 2019

Authors: Liu, Yue | Cai, Fei | Ren, Pengfei | Gu, Zhizhou

Article Type: Research Article

Abstract: To address the problem that the existing time-aware methods always recommend out-of-fashion items to users, this paper proposes a novel method named Item Life Cycle based Collaborative Filtering (ItemLC-CF), taking both user’s preference and item’s popularity into consideration. This method presents a life cycle function to simulate the variation of item’s popularity and integrates such variation with CF to learn the relative preference for items by reranking the candidate set of CF according to item’s vitality. Given that it is extremely complicated to construct a life cycle function for each item, items are clustered into different categories via their popularities …instead of original product categories. Meanwhile, a SVM ensemble classifier based on AdaBoost is employed to find an appropriate category for new arrival items. Evaluation on MovieLens-1M dataset demonstrates that the proposed method can improve the performance of recommendation list, in turn providing more reasonable and popular recommendation lists for users. Show more

Keywords: Collaborative filtering, item life cycle, recommender system, interest shift

DOI: 10.3233/JIFS-18783

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2743-2755, 2019

Authors: Khalil, Ahmed Mostafa | Li, Sheng-Gang | You, Fei | Ma, Sheng-Quan

Article Type: Research Article

Abstract:  The aim of this paper is to correct the assertions (3) and (4) of Proposition 3.6 proposed by Alkhazaleh [Journal of Intelligent and Fuzzy Systems 32 (2017) 4311-4318]. Every notions involved are extend to the arbitrary set case in a clear, rigorous, and non-burdensome manner. A counterexample is given to illustrate the flaw of the assertions. Then we introduce two new notions describing ‘subset’ of n -valued refined neutrosophic soft sets (n -VRNSs for short) and ‘equal’ of n -VRNSs, and give some examples and related propositions. Finally, we use these results to remedy the flaw of the assertions, and …to improve the work of Alkhazaleh. Show more

Keywords: Neutrosophic set, soft set, neutrosophic soft set, n-valued refined neutrosophic soft set

DOI: 10.3233/JIFS-18647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2757-2763, 2019

Authors: Bi, Lvqing | Dai, Songsong | Hu, Bo | Li, Sizhao

Article Type: Research Article

Abstract: A complex fuzzy set, characterized by complex-valued membership functions, is a generalization of a fuzzy set. In this paper, we present complex fuzzy arithmetic aggregation (CFAA) operators, complex fuzzy weighted arithmetic aggregation (CFWAA) operators. Based on the partial ordering of complex fuzzy values, we develop complex fuzzy ordered weighted arithmetic aggregation (CFOWAA) operators. Highly pertinent to complex fuzzy operations is the concept of rotational. This concept has been developed for complex fuzzy aggregation operators. We show that CFAA, CFWAA and CFOWAA operators possess the property of rotational invariance. Moreover, based on the relationship between Pythagorean membership grades and complex …numbers, these operators are studied under Pythagorean fuzzy values. Show more

Keywords: Complex fuzzy sets, complex fuzzy arithmetic aggregation (CFAA) operators, complex fuzzy ordered weight arithmetic aggregation (CFOWAA) operators, complex fuzzy ordered weight arithmetic aggregation (CFOWAA) operators, pythagorean fuzzy sets

DOI: 10.3233/JIFS-18568

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2765-2771, 2019

Authors: Wang, Gang | Qin, Feng | Li, Wen-Huang

Article Type: Research Article

Abstract: The conditional distributivity, also called restricted distributivity, is crucial for many different areas such as utility theory and integral theory. This is the because it weakens distributivity on the domain. This paper is focused on and fully characterizes the conditional distributivity for a uni-nullnorm with continuous and Archimedean underlying t-norms and t-conorm over a continuous t-conorm or a uninorm from U min  ∪ U max with continuous underlying operators.

Keywords: Fuzzy connectives, functional equations, conditional distributivity, uni-nullnorms, uninorm

DOI: 10.3233/JIFS-181702

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2773-2785, 2019

Authors: Wang, Zhen | Jin, LeSheng | Yager, Ronald R. | Mesiar, Radko | Kalina, Martin | Špirková, Jana | Borkotokey, Surajit

Article Type: Research Article

Abstract: We study the Yager OWS aggregation and the Irregular normalized Yager OWA aggregation under infinite environment. Two evaluation problems are proposed to motivate their applications. Few distinguishing properties are discussed. We show that such aggregations use the same type of weights, infinite weights (sequence), to embody the involved preferences. Their respective applications in the fields of Scientometrics and Gradual Confidence Aggregation are proposed and analyzed.

Keywords: Aggregation function, Decision making, evaluation, Infinite Ordered Weighted Sum, OWA operators

DOI: 10.3233/JIFS-181291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 3, pp. 2787-2792, 2019