Journal of Intelligent & Fuzzy Systems - Volume 31, issue 3

Authors: Mandal, Kanika | Basu, Kajla

Article Type: Research Article

Abstract: Minimum spanning tree finds its huge application in network designing, approximation algorithms for NP-hard problems, clustering problems and many more. Many research works have been done to find minimum spanning tree due to its various applications. But, till date very few research works are available in finding minimum spanning tree in neutrosophic environment. This paper contributes significantly by defining the weight of each network edge using single valued neutrosophic set (SVNS) and introduce a new approach using similarity measure to find minimum spanning tree in neutrosophic environment. Use of SVNS makes the problem realistic as it can describe the uncertainty, …indeterminacy and hesitancy of the real world in a better way. We introduce two new and simple similarity measures to overcome some disadvantages of existing Jaccard, Dice and Cosine similarity measures of SVNSs for ranking the alternatives. Further from the similarity measures we have developed two formulas for the entropy measure proving a fundamental relation between similarity measure and entropy measure. The new entropy measures define the uncertainty more explicitly in comparison to other entropy measure existing in the literature which has been established using an example. Show more

Keywords: Similarity measure, entropy measure, decision making, minimum spanning tree

DOI: 10.3233/JIFS-152082

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1721-1730, 2016

Authors: Pacini, Elina | Mateos, Cristian | Garino, Carlos García | Careglio, Claudio | Mirasso, Aníbal

Article Type: Research Article

Abstract: Computational Mechanics (CM) concerns the use of computational methods to study phenomena under the principles of mechanics. A representative CM application is parameter sweep experiments (PSEs), which involves the execution of many CPU-intensive jobs and thus computing environments such as Clouds must be used. We focus on federated Clouds, where PSEs are processed via virtual machines (VM) that are lauched in hosts belonging to different datacenters, minimizing both the makespan and flowtime. Scheduling is performed at three levels: a) broker, where datacenters are selected based on their network latencies via three policies, b) infrastructure, where two bio-inspired schedulers based on …Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) for VM-host mapping in a datacenter are implemented, and c)VM, where jobs are assigned into the preallocated VMs based on job priorities. Simulated experiments performed with job data from two real PSEs show that our scheduling approach allows for a more agile job handling while reducing PSE makespan and flowtime. Show more

Keywords: Cloud computing, computational mechanics, scheduling, ant colony optimization, particle swarm optimization

DOI: 10.3233/JIFS-152094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1731-1743, 2016

Authors: Hong-Li, Zhang | Yu-Yi, Zhai | Shu-Lin, Liu | Dong, Li | Bo, Wang | Kun-Ju, Shi | Er-Pin, Zhou

Article Type: Research Article

Abstract: An accurate and efficient intelligent fault diagnosis method plays a key role in reducing the production arrest of forthcoming faults in modern industrial machines, increasing the safety of plant operations and optimizing manufacturing costs. Recently, a new approach for hierarchical clustering based on data field, was put forward and obtained good effect. Thus, inspired by the principle, a new efficient and intelligent fault diagnosis method called Mass Optimizing Group Identification Classification Algorithm (MOGICA) has been proposed in this article. In this classifier, the classification rate and size of used objects population have some fluctuation with the change of only parameter …δ . Thus, with the purpose of making data field distribution more reasonable and increasing the classification accuracy, Entropy is introduced to determine the parameter δ . The performance of the method has been tested through two kinds of experiments. In the first experiment, four benchmark data sets were used to evaluate the performance of this algorithm. In the second experiment, the algorithm was used to diagnose the faults of ball bearing. Compared with other classification techniques in the two experiments, our method is more competitive. Show more

Keywords: Data field, MOGICA, quadratic programming, classification, fault diagnosis

DOI: 10.3233/JIFS-152168

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1745-1757, 2016

Authors: Usman, Muhammad | Usman, M. | Asghar, Sohail

Article Type: Research Article

Abstract: Data mining and machine learning methods have been utilized successfully in the past for identifying and forecasting meaningful patterns from data repositories of diverse application domains. However, the high number of dimensions and instances present in large datasets pose great technical challenges to these existing methods of classification and prediction. The presence of noisy data and missing values makes it even tougher to achieve accurate prediction outcomes. A number of hybrid methodologies constituting dimensionality reduction, feature selection and noise removal methods have been proposed in the literature. However, majority of these techniques force the analysts to compromise on accuracy of …classification and prediction results. Therefore, there is a strong need of a methodology that not only scales well with the sheer size and volume of data but also provides near to accurate classification and prediction results by effectively handling the noise in data variables. This paper proposes a fuzzy-based methodology which ranks the dimensions in order of importance and exploits Fuzzy Nearest Neighbor (FNN) approaches for accurate classification and prediction. An experimental evaluation on real world datasets, taken from UCI machine learning repository, shows that the proposed approach outperforms the existing classification and prediction methods by employing only a subset of important features to achieve high prediction accuracy rates at multiple levels of data abstraction. Show more

Keywords: Classification, fuzzy nearest neighbor, prediction, large datasets, feature selection, pattern recognition

DOI: 10.3233/JIFS-152176

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1759-1768, 2016

Authors: Xiong, Zhongmin | Zhu, Jiguang | Yuan, Hongchun | He, Shijun | Wei, Huiwen

Article Type: Research Article

Abstract: Active rules have been employed for enhance self-reaction functionality, but how to detect their confluence property during an indeterminable rule process is intractable. If two rules without priority have been triggered at the same time, then anyone can be firstly chosen to execute at random and two different executive sequences will be arisen. An active rule set is confluence if and only if the same final database state appears no matter which executive sequence has been chosen to execute. The existing methods based on Rule Commutativity are no more effective to detect the confluence case if a rule set …has exclusive rules and has no user-defined priority as they do not designed for rules without priority and they do not consider whether two different executive sequences for rules can be satisfied by the same database state. To address these problems, this work proposes the concepts of Exclusive Rule and Confluence Requirement with exclusive rules based on the conditional formula of an executive sequence. Then, a new algorithm for confluence detection is provided. The examples and theoretical analysis clearly show that the proposed method achieves much better detection performance when exclusive rules appear. Show more

Keywords: Active rule, rule analysis, confluence, exclusive rule, algorithm

DOI: 10.3233/JIFS-152202

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1769-1778, 2016

Authors: Du, Longbo | Gao, Jing

Article Type: Research Article

Abstract: In recent years, China’s real estate investment behavior with the market economy has been developing steadily and has become increasingly frequent. Real estate investment is a long construction period, huge investment, influence factors and complex activity, and the real estate enterprise is faced with increasingly fierce competition. How the scheme selection of more scientific, reasonable, comprehensive evaluation analysis of the investment plan, select the optimal scheme, is the key to win investment, is also the most critical problem facing investors. In this paper, we study on the multiple attribute decision making for real estate investment with hesitant fuzzy information. Inspired …by the dependent aggregation, we propose the dependent hesitant fuzzy Hamacher weighted average (DHFHWA) operator, where the weights rely on the aggregated hesitant fuzzy arguments and can lower the influence of unfair hesitant fuzzy arguments on the aggregated results by allocating low weights to the “false” and “biased” ones and then utilize them to design this approach for multiple attribute decision making with hesitant fuzzy information. In the end, an example of real estate investment is proposed to testify our method. Show more

Keywords: Multiple attribute decision making, hesitant fuzzy information, dependent hesitant fuzzy Hamacher weighted average (DHFHWA) operator, real estate investment

DOI: 10.3233/JIFS-152291

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1779-1785, 2016

Authors: Kim, Yong Chan

Article Type: Research Article

Abstract: In this paper, we investigate categories of fuzzy preorders, approximating operators and Alexandrov topologies in complete residuated lattices. In fact, categories of fuzzy preorders, approximating operators and Alexandrov topologies are isomorphic. We give their examples.

Keywords: Complete residuated lattices, fuzzy preorders, (upper, lower, join-meet) approximation operators, Alexandrov topologies

DOI: 10.3233/JIFS-152398

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1787-1793, 2016

Authors: Silva Farias, Antonio Diego | de Araújo Lopes, Luiz Ranyer | Bedregal, Benjamín | Santiago, Regivan H.N.

Article Type: Research Article

Abstract: There are several variations of fuzzy Turing machines in the literature, many of them require a t-norm in order to establish their accepted language. This paper generalize the concept of non-deterministic fuzzy Turing machine - NTFM, replacing the t-norm operator for several aggregation functions. We establish the languages accepted by these machines, called fuzzy recursively enumerable languages or simply LFRE and show, among other results, which classes of LFRE are closed under unions and intersections.

Keywords: Turing machines, fuzzy turing machines, fuzzy languages, aggregation functions

DOI: 10.3233/JIFS-152489

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1795-1806, 2016

Authors: Arun, N.K. | Mohan, B.M.

Article Type: Research Article

Abstract: This paper presents mathematical models of the simplest fuzzy PID controller of Mamdani type. This controller is called the “simplest” as it employs minimum number of fuzzy sets (two on each input variable and four on output variable) while satisfying the control rule base that contains four rules relating all six input fuzzy sets to all four output fuzzy sets. L - type, Γ - type and Π - type membership functions are considered in fuzzification process of input and output variables. Controller modeling is done via algebraic product AND operator-maximum OR operator-Larsen product inference method-Centre of Sums (CoS) …defuzzification process combination. The new model obtained in this manner turns out to be nonlinear, and its properties are studied. Since digital controllers are implemented on the digital processors, the computational and memory requirements of the fuzzy controller and conventional (nonfuzzy) controller are compared. Stability analysis of closed loop systems containing the fuzzy controller models is done using the small gain theorem. Show more

Keywords: Mathematical model, fuzzy control, PID controller, Mamdani type controller, center of sums defuzzification

DOI: 10.3233/JIFS-152626

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1807-1818, 2016

Authors: Hao, Xiaoying | Niu, Meixia | Wang, Yuan | Wang, Zhudeng

Article Type: Research Article

Abstract: In this paper, we further investigate the constructions of implications and left (right) semi-uninorms on a complete lattice. We firstly give out the formulas for calculating the upper and lower approximation conjunctive left (right) semi-uninorms of a binary operation. Then, we derive the formulas for calculating the upper and lower approximation NP implications of a binary operation. Finally, we show that the right (left) residuum of the upper approximation conjunctive right (left) infinitely ∨-distributive left (right) semi-uninorm of a right (left) infinitely ∨-distributive binary operation is the lower approximation right infinitely ∧-distributive NP implication of the right (left) residuum of …the binary operation. Show more

Keywords: Fuzzy connective, implication, left (right) semi-uninorm, upper (lower) approximation, neutrality principle (NP)

DOI: 10.3233/JIFS-15531

Citation: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 3, pp. 1819-1829, 2016