Journal of Intelligent & Fuzzy Systems - Volume 36, issue 4

Authors: Ooi, Boon Pin | Abdul Rahim, Norasmadi | Zakaria, Ammar | Masnan, Maz Jamilah | Abdul Shukor, Shazmin Aniza

Article Type: Research Article

Abstract: Under certain situations, researchers were forced to work with small sample-sized (SSS) data. With very limited sample size, SSS data have the tendency to undertrain a machine learning algorithm and rendered it ineffective. Some extreme cases in SSS problems will have to deal with large feature-to-instance ratio, where the high number of features compared to small number of instances will overfit the classification algorithm. This paper intends to solve small sample-sized classification problems through hybrid of random subspace method and random linear oracle ensemble by utilizing binary feature subspace splitting and oracle selection scheme. Experimental results on artificial data indicate …the proposed algorithm can outperform single decision tree and linear discriminant classifiers in small sample-sized data, but its performance is identical to k-nearest neighbor classifier due to both shared similar selection approach. Results from real-world medical data indicate the proposed method has better classification performance than its corresponding single base classifier especially in the case of decision tree. Show more

Keywords: Ensemble method, classification, small sample, Euclidian’s distance

DOI: 10.3233/JIFS-18504

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3225-3234, 2019

Authors: Zhang, Qibin | Wang, Peng | Chen, Zonghai

Article Type: Research Article

Abstract: This paper presents a novel qualitative scan matching approach based on the point cluster representation of laser scans for the coordination of mobile robots in indoor environments. According to the geometric characteristics of the scanned environment, a hierarchical clustering method is proposed to split the points in a laser scan into stable clusters, with which the point distribution in the scan can be approximated by a collection of probability distributions instead of the discrete data points. Based on the proposed compact and continuous description of captured sensor data, the pairwise constraints between clusters are exploited as heuristic information for efficient …data association between consecutive scans. In order to find the relative transformation between two frames, a qualitative estimate of the rotation with the maximum support and a closed-form solution for the translation are derived. Experiments in a variety of scenarios demonstrate the effectiveness of the proposed approach for robot pose estimation in indoor environments. Show more

Keywords: Mobile robots, pose estimation, laser scan matching, clustering, association

DOI: 10.3233/JIFS-18020

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3235-3247, 2019

Authors: He, Chunmei | Liu, Yaqi | Yao, Tong | Xu, Fanhua | Hu, Yanyun | Zheng, Jinhua

Article Type: Research Article

Abstract: The regular fuzzy neural network (RFNN) is a kind of fuzzy neural network by fuzzifying the feed-forward neural network. The RFNN can directly deal with the language information and it has the merits of fuzzy system and neural network. It is presented a fast learning algorithm based on the extreme learning machine (ELM) for the RFNN in this paper. The RFNN referred here is a three-layer feed-forward fuzzy neural network and the connected weights in the RFNN are all fuzzy numbers. A simulation example is given to approximately realize the fuzzy if-then rules by the RFNN. The results show that …the RFNN trained by the proposed algorithm has good performance and approximation ability. Show more

Keywords: Regular fuzzy neural network, learning algorithm, extreme learning machine

DOI: 10.3233/JIFS-18046

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3263-3269, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3271-3271, 2019

Authors: Wang, Yanhui | Cui, Yiru | Li, Man | Wang, Shujun

Article Type: Research Article

Abstract:  Due to the mechanical, electrical and information tripling coupling relationships among the components of mechatronics system, it is not reasonable enough to evaluate the criticality of components only in the view of physical structure or function. Our work makes two contributions. Firstly, the concept of the key components of mechatronics system is defined, and three identification measures of components have been proposed from system structure, function and the impact of single fault components on the whole system respectively. The structural importance is calculated based on the improved importance evaluation matrix; the functional importance is calculated using IPR algorithm; and the …failure relevance importance is calculated based on cascading failure process. Secondly, a fuzzy clustering method for key component identification of mechatronics system is proposed, which calculates the comprehensive importance according to the characteristic of clustering center and the membership degree of the component. Taking a component network of China Railway CRHX EMU vehicle bogie system as an example, a list of ordered comprehensive importance of components is given by combining attribute characteristics of clustering centers with the degree of membership of each component, and the results show that the accuracy of the identification is 83.3%. Show more

Keywords: Comprehensive importance of components, key components identification, fuzzy clustering method, mechatronics system

DOI: 10.3233/JIFS-171359

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3273-3287, 2019

Authors: Yu, Jianhang | Li, Yingqin | Chen, Minghao | Zhang, Biao | Xu, Weihua

Article Type: Research Article

Abstract:  The decision-theoretic rough set, as a special case of probabilistic rough set, mainly adopts Bayesian decision procedure to achieve the thresholds from a given loss function. It provides a novel semantic interpretation for rough regions by utilizing three-way decision approach and has been widely applied in decision making. However, there is a limitation of classical decision-theoretic rough set that it lacks of ability to deal with hybrid data. Where the condition attributes are composed of multiple types, for instance, real-valued, set-valued, interval-valued, fuzzy-valued, intuitionistic fuzzy-valued attribute and so on. These complex data constitute a knowledge representation system named lattice-valued decision …information system. In this talk, we develop a decision-theoretic rough set model in a lattice-valued decision information system to study these hybrid data. Then, some essential properties of this model are addressed and decision rules are investigated. Furthermore, we design two heuristic attribute reduction algorithms based on rough entropy and positive region preservation, respectively. Finally, a series of examples based on medical diagnosis are conducted to interpret decision rules and demonstrate these algorithms. Show more

Keywords: Attribute reduction, decision-theoretic rough set, lattice-valued decision information system, positive region preservation, rough entropy

DOI: 10.3233/JIFS-172111

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3289-3301, 2019

Authors: Le, Tien-Loc

Article Type: Research Article

Abstract:  This paper aims to design a self-evolving function-link type-2 fuzzy neural network for application in controlling antilock braking systems. In this control scheme, the self-evolving algorithm is applied to autonomously construct the control network without an initial rule-base. The function-link is designed to give the interval type-2 fuzzy neural network has more freedom in adjusting the parameters. Based on the steepest descent gradient method and the Lyapunov theory, the adaptive laws for the proposed system are derived, and the control system stability is guaranteed. Further, to rapidly achieve the desired control performance, an online particle swarm optimization algorithm is used …to optimize the learning rates for the parameter adaptive laws. The performance of the control system is assessed via multiple simulation results of the antilock braking system response under various road conditions. Show more

Keywords: Type-2 fuzzy logic system, particle swarm optimization, self-evolving learning algorithm, antilock braking systems

DOI: 10.3233/JIFS-181014

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3303-3315, 2019

Authors: Wang, Duojin | Yu, Hongliu | Wu, Jing | Meng, Qingyun | Lin, Qinglian

Article Type: Research Article

Abstract: Improvement in hand function is one of the major goals of stroke rehabilitation. This paper introduces a newly developed hand rehabilitation device with a user-centered design concept, which integrates fuzzy based quality function deployment (Fuzzy-QFD), morphological analysis method and fuzzy based analytic hierarchy process (Fuzzy-AHP). The design focuses on extension of some certain technical attributes of products to obtain a higher level of user satisfaction. Results of functional test showed that the hand affected due to a stroke could complete the training task successfully by controlling electromyography signals from an unaffected hand. Moreover, for poststroke patients the passive training …by voice control is also a suitable alternative. Depending on the actual situation of patients the voice commands could be given by themselves or by therapists. The operation and test results of function showed that the product meet patients’ requirements and has practical significance. The proposed user-centered method also can be applied to the development of similar products. Show more

Keywords: Exoskeleton, hand rehabilitation, fuzzy-QFD, fuzzy-AHP, morphological analysis

DOI: 10.3233/JIFS-181025

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3317-3331, 2019

Authors: Mao, Hua

Article Type: Research Article

Abstract: For a formal context, we define an equivalence relation on the set of attributes. Through this equivalence relation, we define the lower and upper approximation operators relative to the family of semiconcepts of the formal context. We study on the two operators with the further properties that are interesting and valuable in the theory of rough set. In addition, we research on the lattice properties of all of semiconcepts in a formal context. Using this lattice, we set up two operators, and find their approximation properties in the theory of rough set. The two ways for giving approximations generalize the …idea of Pawlak rough set approximations from one universal set to two non-related universal sets. We provide examples to exam the correct of the two approximation ways in this paper. Show more

Keywords: Semiconcept, approximation, equivalence relation, lattice, rough set

DOI: 10.3233/JIFS-18104

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3333-3343, 2019

Authors: Jesi, P. Maria | Raj, A. Albert

Article Type: Research Article

Abstract:  Wireless mobile ad hoc networks (MANETs) have emerged as a key technology for next-generation wireless networking. Due to its advantages over other wireless networks, MANETs are undergoing rapid progress and inspiring numerous applications. However, many technical issues are still facing the deployment of this technology, and one of the most challenging aspects is the Bandwidth conserving Technology. To achieve this aspect this paper proposed a method for maintaining infrastructure of the network and mobility of nodes. This can be achieved by employing clustering to improve the stability of nodes by utilizing weight-based clustering algorithm. However, the mobility of the node …is maintained by utilizing distributed scheduling works based on a priority based Distributed Scheduling to reduce interference so as to improve the throughput. Show more

Keywords: Wireless mobile ad hoc networks, mobility of nodes, scheduling, weight-based clustering

DOI: 10.3233/JIFS-181067

Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 4, pp. 3345-3356, 2019