Journal of Intelligent & Fuzzy Systems - Volume 30, issue 5

Authors: Zhan, Jianming | Zhou, Xiaowu | Xiang, Dajing

Article Type: Research Article

Abstract: A novel congruence relation U  (μ , t ) on an n -ary semigroup S is established. We show that U  (μ , t ) is a congruence relation on an n -ary semigroup S if μ is a fuzzy ideal of S . Based on this idea, we construct the lower and upper approximations in an n -ary semigroup. Furthermore, we introduce the notions of rough ideals and rough prime ideals by means of fuzzy ideals of an n -ary semigroup. In particular, the concepts of rough n -ary semigroups, rough homomorphisms are introduced and some …relative properties are also investigated. Show more

Keywords: Rough set, Upper (lower) approximation, Approximation space, n-ary semigroup, (Prime) ideal, Rough (prime) ideal, Rough homomorphism

DOI: 10.3233/IFS-152072

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2833-2841, 2016

Authors: Praczyk, Tomasz

Article Type: Research Article

Abstract: The paper presents Cooperative Co–Evolutionary Neural Networks (CCENN), that is, a new method for evolving modular artificial neural networks (MANN). In CCENN, individual module–networks evolve in separate populations and to form a complete MANN each population delegates a single module. Modules collaborating within the same artificial neural network (ANN) are not connected and they work like networks in an ensemble–based approach, i.e. output of a complete ANN is determined based on a negotiation process between the module–networks. A module with the greatest negotiation strength is allowed to set one of the outputs of the entire ANN, to fix all the …outputs, the modules negotiate many times. To test performance of CCENN, it was used to evolve neuro–controllers for a team of underwater vehicles whose common goal was to capture other vehicle behaving by a deterministic strategy (predator–prey problem). The experiments were carried out in simulation whereas their results were used to compare CCENN with two other neuro–evolutionary methods designed for building monolithic ANNs. Show more

Keywords: Evolutionary modular neural networks, underwater vehicles, predator–prey problem

DOI: 10.3233/IFS-162095

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2843-2858, 2016

Authors: Qian, Weiyi | Niu, Linlin

Article Type: Research Article

Abstract: In this paper, some new operational laws of intuitionistic multiplicative numbers (IMNs) are defined, which can guarantee the closedness of operation. Based on these operational laws, some aggregation operators are proposed, including intuitionistic multiplicative weighted averaging (IMWA) operator and intuitionistic multiplicative weighted geometric (IMWG) operator. These aggregation operators also have the closedness under presented operational laws. Then, desirable properties of aggregation operators are also expatiated in details. Finally, a group decision making method is presented based on ituitionistic multiplicative preference relation, and the solution process of this decision making method is shown in details through a numerical example.

Keywords: Intuitionistic multiplicative set, operational laws, aggregation operator, group decision making, preference relation

DOI: 10.3233/IFS-151836

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2859-2870, 2016

Authors: Ren, Peijia | Xu, Zeshui | Lei, Qian

Article Type: Research Article

Abstract: There has been a growing interest and activity in the field of interval-valued intuitionistic fuzzy sets (IVIFSs). It is generally useful to express the variations of the membership function and the non-membership function in fuzzy circumstances. However, the IVIFS is a little bit complicated on expressions and calculations. To overcome this limitation, this paper aims to introduce a succinct way to define IVIFS by two intuitionistic fuzzy numbers (IFNs), and thus, a simplified interval-valued intuitionistic fuzzy number (SIVIFN) is proposed. Afterwards, a series of operational laws and aggregation techniques over the SIVIFNs are developed, and their desirable properties are investigated …in detail, which enrich the interval-valued intuitionistic fuzzy set theory. Finally, a numerical example is provided to illustrate the straightforward expressions and calculations of the SIVIFNs. Show more

Keywords: Interval-valued intuitionistic fuzzy set, intuitionistic fuzzy numbers, operational laws, aggregation operators

DOI: 10.3233/IFS-151735

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2871-2882, 2016

Authors: Barchinezhad, Soheila | Eftekhari, Mahdi

Article Type: Research Article

Abstract: Feature selection is the problem of eliminating the features which are irrelevant and/or redundant. It can also be assumed as the problem of selecting a small subset of features which are necessary and sufficient to describe the target concept. In this paper, a new feature selection method based on the concepts of sensitivity and Pearson’s correlation is introduced which is called Sensitivity and Correlation based Feature Selection-SCFS. The sensitivity of one feature is computed via applying the subtractive clustering and is utilized as feature-target relevancy. Pearson’s correlation coefficient is used to determine the redundancy among a subset of selected features. …The introduced measure increases the score of a selected feature subset which has maximum relevancy to the target concept and minimum redundancy among features. The proposed criterion is employed as the fitness function in a genetic algorithm in order to evaluate feature subsets. Some well-known benchmark datasets are utilized for investigating the performance of the proposed method. Also, the results of our method are compared with the other similar feature selection methods. The obtained results show however SCFS is an unsupervised filter; it is well comparable to the other well-known supervised methods in terms of classification accuracy and the number of selected features. Show more

Keywords: Feature selection, correlation, sensitivity, genetic algorithm, fuzzy clustering, filter

DOI: 10.3233/IFS-151736

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2883-2895, 2016

Authors: Yang, Zhixia | Zhou, Zhe | Jiang, Yaolin

Article Type: Research Article

Abstract: In this paper, we propose a least squares support vector machine with parametric margin (Par-LSSVM) for binary classification, which only needs to solve a system of linear equation. Par-LSSVM is able to handle the datasets with heteroscedastic noise. And the closer hyperplane to the test data point gives the class label, and this makes Par-LSSVM capable of dealing with “Cross Planes” datasets. The experimental results on several artificial, benchmark and USPS datasets indicate that our proposed algorithm outperforms Par-ν-SVM for binary classification problem.

Keywords: Support vector machine, classification, least squares, parametric margin

DOI: 10.3233/IFS-151743

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2897-2904, 2016

Authors: Zhao, Lin | Bian, Yang | Rong, Jian | Liu, Xiaoming | Shu, Shinan

Article Type: Research Article

Abstract: For the purpose of creating excellent walking environment, increasing the proportion of pedestrians and providing a planning and designing basis for the newly-built and rebuilt sidewalks, this paper proposed a comprehensive multi-factor evaluation method for pedestrian level of service on sidewalks based on the quantification of environmental factors. Firstly, pedestrians’ satisfaction questionnaires survey was conducted with intercept survey method on 87 typical sidewalks covering different regions, road grades, road facility and environmental conditions. The rating scale form of the questionnaires was 10 grades and 4300 valid questionnaires were obtained. Then, the factors of traffic conditions, road facility conditions and environmental …conditions which affected pedestrians’ satisfaction were analyzed in detail. Image recognition and edge detection methods were used to quantify the environmental factors. Combined with Spearman rank correlation method, the 10 significant influencing factors obtained were verified. The more comprehensive and quantified multi-factors evaluation index system for pedestrian level of service on sidewalks could be proposed. Finally, aiming at the characteristics that pedestrian level of service on sidewalks and its influencing factors were multi-type variables, the fuzzy neural network method was used to establish the comprehensive evaluation model for pedestrian level of service on sidewalks. The error result showed that the accuracy of the model in this research was 0.94 which had a significant improvement compared with the existing linear regression models. Show more

Keywords: Edge detection, fuzzy neural network, green looking ratio, pedestrian level of service on sidewalks, quantification on landscape

DOI: 10.3233/IFS-151753

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2905-2913, 2016

Authors: Hua, Mingang | Cai, Yixi | Fei, Juntao

Article Type: Research Article

Abstract: This paper investigates non-fragile exponential state estimation problems for continuous-time fuzzy stochastic neural networks with time-varying delays. The Takagi-Sugeno (T-S) fuzzy model representation is extended to the exponential state estimator design for fuzzy stochastic neural networks with time-varying delays. The neuron activation function and the nonlinear measurement equation are assumed to be satisfy sector-bounded conditions and standard Lipschitz conditions. For these two conditions, delay-dependent sufficient conditions are presented to guarantee the existence of the desired state estimators for fuzzy stochastic neural networks. Finally, two numerical examples are given to demonstrate that the proposed approaches are effective and that the sector-bounded …conditions are weaker than the standard Lipschitz conditions. Show more

Keywords: Non-fragile, state estimation, Takagi-Sugeno, stochastic neural networks, exponential stability

DOI: 10.3233/IFS-151789

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2915-2926, 2016

Authors: Khooban, Mohammad Hassan | Niknam, Taher | Sha-Sadeghi, Mokhtar

Article Type: Research Article

Abstract: In this paper, in order to control a class of nonlinear uncertain power systems, a new simple indirect adaptive general type-II fuzzy sliding mode controller (IDAGT2FSMC) is proposed. For handling dynamic uncertainties, the proposed controller utilizes the advantages of general type-2 fuzzy logic systems (GT2FLS) to approximate unknown nonlinear actions and noisy data. Implementing general type-2 fuzzy systems is computationally costly; therefore, to decrease computational burden, the proposed method uses a recently introduced α -plane representation so that GT2FLS can be seen as a composition of several interval type-2 fuzzy logic systems (IT2FLS) with a corresponding level of α …for each. The globally asymptotic stability of the closed-loop system is mathematically proved. To evaluate the superiority of the proposed controller, performance of the proposed method is compared with those of Indirect Adaptive type-1 Fuzzy Sliding Mode (IDAFSM) controller, Indirect Adaptive Interval Type-II Fuzzy Sliding Mode (IDAT2FSM) controller, conventional Sliding Mode controller (SMC) and PID controller results which are all among the most recent methods applied to the issue in question. Finally, the proposed method is applied to an uncertainly chaotic power system as a case study. Simulation indicates the effectiveness of the proposed controller while facing of dynamic uncertainties and external disturbances. Show more

Keywords: Mathematical modeling, chaotic power systems, general type-II fuzzy, adaptive control, sliding mode control, nonlinear robust control

DOI: 10.3233/IFS-151796

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2927-2937, 2016

Authors: Andishgar, Mohammad Hadi | Fereidunian, Alireza | Lesani, Hamid

Article Type: Research Article

Abstract: Since a power outage can impose damages to the economy, the value of lost load is much more than the cost of electricity not sold. Hence, efforts should be devoted to achieve a highly reliable energy delivery. Although a large number of power system outages occur in power distribution system, the FLISR mechanism is inefficient in many traditional distribution systems. This leads to late awareness of fault and outages, thus remaining the affected parts of the system without electricity for considerably long periods. Hence, first steps to inject intelligence into the smart grid should be started from the distribution system. …In this study, a discrete event system is proposed to model the smart distribution grid operation, specifically to monitor the status of the system, using Petri Nets. Moreover, the proper actions for fault clearance and restoration of the network to the normal state can be obtained using the presented model. The operator is supported by information on fault and the performance of protections. The presented model also helps in reducing the time of fault clearance, thus increasing the system reliability. The proposed model enhances the self-healing ability of smart grid, by reinforcing the healer system, i.e. the FLISR process. Show more

Keywords: FLISR, self-healing, healer reinforcement, Petri Net, smart grid, distribution automation

DOI: 10.3233/IFS-151814

Citation: Journal of Intelligent & Fuzzy Systems, vol. 30, no. 5, pp. 2939-2951, 2016