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International Journal of Information Technology Vol. 11 No. 6 2005 (Special Issue) Guest Editorial Special Issue on Neural Networks & Fuzzy Systems Welcome to the special issue of IJIT on Neural Networks & Fuzzy Systems! In recent years, intelligent computing techniques, such as neural network and fuzzy logic approaches, have long been applied in many fields with many important theoretical solutions and successful applications. We have witnessed a fast growing interest in neural networks & fuzzy system. The special issue addresses this important area and its related topics. The 2005 International Conference on Intelligent Computing hosted a track on Neural Networks & Fuzzy System. We have selected 15 papers from the track. This special issue tries to archive a collection of current advances of neural networks & fuzzy systems in theory and applications, addressing various aspects of neural network and fuzzy system applications. While acknowledging its limited coverage, this special issue offers a range of interesting contributions. Let us scan through the contributions of this special issue. More than half of them are related to neural network and fuzzy system applications, focusing on such issues as control, prediction, pattern recognition, and decision making. The rest of the papers cover various aspects, such as identification, spatial query, and image processing. Yong-gui Kao, Cun-chen Gao and Wei-dong Sun investigate the problem of quadratic stabilization of linear uncertain systems with multiple time-varying delays in state and input. Carlos Heránndez-Espinosa, Joaquín Torres-Sospedra and Mercedes Fernández Redondo investigate in ensemble of neural networks. They provide 9 new methods in network integration and they trained ensembles of 3,9,20 and 40 networks with 20 different methods including the new ones. Fuqing Zhao, Qiuyu Zhang, Dongmei Yu, Yahong Yang have designed, developed, and implemented a production activity scheduling system using the multi-layered perceptron neural networks. Yongjian Yang, Xiaohui Yang and Wei Zhang investigate fuzzy spatial position inference aspects. They proposed a new way to use fuzzy reasoning to solve the fuzzy location problem in applying GIS. Zhiyuan Xue, Chuandong Li, Rong Zhang investigate the estimate of parameter-deviation degree for delayed neural networks, they presented a simple delayed neural network with parameter deviation and analyzed its robust stability. Michael J. Watts and Susan P. Worner investigate two neural network methods for predicting the risk of insect pest species establishment in regions where they are not normally found. Han Zhao, Kang Jiang and Wen-Gang Cao present a partner selection algorithm based on genetic algorithms and fussy decision-making. Qingjiu Xu, Jinyong Yu, Wenjin Gu and Daquan Tang investigate fuzzy sliding-mode controller aspects. In this paper, a novel adaptive fuzzy neural networks controller is designed for some BTT missile integrated with sliding-mode control. Jun Wang and Hong Peng use B-spline wavelet as membership function, proposed a fuzzy wavelet network for approximating nonlinear function. Compared with the other methods, the proposed method has the advantages of the approximation accuracy and good generalization performance. Jin Cheng, Jianqiang Yi, Dongbin Zhao studied a RBF neural network-based model reference adaptive control approach for ship steering systems. Shichun Yuan and Chen Guo presented an adaptive control for a class of linear systems with matching uncertainties. Zong-yi Xing, Yong Zhong, Li-min Jia et al investigate interpretable fuzzy classification aspects, they propose an approach to construct interpretable and precise fuzzy classification system based on fuzzy clustering and genetic algorithm. Yunan Hu and Bin Zuo investigate the extremum seeking control, a method combining an annealing recurrent neural network with extremum seeking control is proposed. Xiaoli Li, Zhenlong Du, Tong Wang and Dongmei Yu investigate audio feature selection aspects, rough set theory is firstly applied to stream data processing. J.G. Shi, X.G. Gao, Z. Liu and C.H. Zhang investigate Hierarchy Discrete Dynamic Bayesian Network and its inference algorithm to solve the problem of modeling a complicated system. We are very pleased to offer this great selection of papers. We hope you all find this issue informative and helpful in keeping yourselves up-to-date. ACKNOWLEDMENT The guest editors would like to thank all the authors for their contributions and all reviewers for their time and effort, as their contribution was crucial to the successful realization of this special issue. Ping GUO Guest Editor Rong-Fang BIE Guest Editor Fu-Sheng YU Guest Editor Beijing Normal University Ping GUO |