Editorial

Citation

King, I. and Li, Y. (2008), "Editorial", International Journal of Intelligent Computing and Cybernetics, Vol. 1 No. 4. https://doi.org/10.1108/ijicc.2008.39801daa.001

Editorial

Article Type: Editorial From: International Journal of Intelligent Computing and Cybernetics, Volume 1, Issue 4

About the Guest Editors

Irwin King received the BS from California Institute of Technology, Pasadena, in 1984. He received his MSc and PhD degree in Computer Science from the University of Southern California, Los Angeles, in 1988 and 1993, respectively. He is currently with the Chinese University of Hong Kong. His research interests include web intelligence and social computing, machine learning, and multimedia processing. He has published over 140 refereed journal and conference manuscripts. In addition, he has contributed to over 20 book chapters/edited volumes and has over 30 research and applied grants. His personal homepage is: www.cse.cuhk.edu.hk/ ∼ king, and his contacting E-mail is: king@cse.cuhk.edu.hk

Yangmin Li received his BS and MSc degrees from Jilin University, China, in 1985 and 1988, respectively, and the PhD degree from Tianjin University, China in 1994. He was a Postdoc Research Associate in Purdue University, W. Lafayette, USA, in 1997. He is currently a Full Professor in University of Macau, Macao SAR, China. His research interests include robotics, computational intelligence, and micro/nano technology. He has published over 180 papers in refereed international journals and conferences. His personal homepage is: www.sftw.umac.mo/∼ yangmin, and his contacting E-mail is: ymli@umac.mo

Welcome to this special issue on “Advances in Computational Intelligence”. Computational intelligence is a well-established paradigm, where new theories with a sound applications have been evolving. This special issue features nine papers from the International Workshop on Advanced Computational Intelligence (IWACI 2008). The workshop was held at the University of Macau on June 7-8, 2008 as a post-conference workshop of World Congress on Computational Intelligence (WCCI 2008), which was held at the Hong Kong Convention and Exhibition Centre, Hong Kong, June 1-6, 2008. The workshop received nineteen submissions and each submission was peer-reviewed by at least two experts in the related field. Finally, nine manuscripts were accepted to make a presentation at the workshop. The Program Committee then further invited authors to revise their papers according to feedback at and after the workshop. Eventually nine manuscripts were selected to be in this special issue, which includes six manuscripts from the regular submissions and three manuscripts from the invited speakers.

These nine articles cover three basic areas in computational intelligence in terms of basic foundation, image processing, and applications. The first paper entitled “Recent advances in cluster analysis” authored by Rui Xu and Donald Wunsch II presents a comprehensive and systematic survey and some recent advances in cluster analysis with a special emphasis on complicated data. More specifically, the paper investigates clustering algorithms and analyzes them in terms of scalability, robustness, visualization, cluster shape, etc.

The second paper entitled “A performance gradient perspective on gradient-based policy iteration and a modified value iteration” by Lei Yang, James Dankert, and Jennie Si presents a bottom-up, algorithmic view that complements the gradient-based policy iteration (GBPI)’s top-down approach with modified value iteration to solve partially observable Markov decision process (POMDP) problems. The result of the proposed algorithm is that it is easier to understand and implement in practice. In addition, with the new approach new insight may be developed with performance guarantees.

The third paper entitled “An estimating method for IP Taffic matrix based on generalised inverse matrix” authored by Fengjun Shang presents a novel calculating model based on the generalized inverse matrix. In this model, a generalized inverse matrix is introduced to resolve the traffic matrix equation. An original traffic matrix is estimated according to the prior. The linear programming is introduced to acquire the optimized solutions. Through both theoretical analysis and simulating results, it is shown that the proposed algorithm achieves better performance than the existing representative methods.

The fourth paper entitled “Image piecewise inpainting based on radial basis function” authored by Minfen Shen, Jialiang Chen, and Bin Li presents a novel algorithm for image inpainting, which has been widely used for removing unwanted objects from images or reconstructing damaged photographs. An image piecewise inpainting technique based on radial basis function is used to transform the 2D image inpainting problem into 3D implicit surface reconstruction problem. By RBF resampling, the algorithm can nicely fix the damaged image or remove specific objects. Experimental results show that the proposed algorithms can prevent the edge blur caused by the isotropic character of RBF, and effectively reduce the RBF centers without a loss in accuracy.

The fifth paper entitled “Texture-based image steganalysis by artificial neural networks” by Michael Pratt, Sharath Konda, and Henry Chu demonstrates how image texture could affect steganalytic performance. Based on a texture measure to mask out image areas with high-texture contents, the paper illustrates how the low-texture areas can be used to extract relevant features for detecting the presence of embedded data in images.

The sixth paper entitled “Embedding a social fabric component into cultural algorithms toolkit for an enhanced knowledge-driven engineering optimization” by Robert Reynolds and Mostafa Ali introduces the notion of a social fabric and the influence function in selected complex engineering problems. Different parameter values in the influence function would affect the rate of solution. This is interesting since the proposed approach shows a better convergence to optimal values in complex engineering problems with numerous constraints.

The seventh paper entitled “Automotive engine idle speed control optimization using least squares support vector machine and genetic algorithm” authored by P.K. Wong, L.M. Tam, K. Li and H.C. Wong presents a novel electronic control unit setup optimization for engine idle speed control. Least squares support vector machines is proposed to build up an engine idle speed model based on dyno test data, and then genetic algorithm is applied to obtain optimal settings automatically subject to various user-defined constraints. The study shows that the predicted results using the estimated model from LS-SVM are good agreement with the actual test results.

The eighth paper entitled “A neural network approach to control performance assessment” authored by Yunfeng Zhou and Feng Wan proposes a neural network approach to control performance assessment. The performance index is based on the minimum variance control benchmark, a radial basis function network is used as the pre-whitening filter to estimate the white noise sequence, and a stable filtering and correlation analysis method is adopted to calculate the performance index by estimating innovations sequence using the RBFN pre-whitening filter. This scheme is compared with auto-regressive model, auto-regressive moving average model and Laguerre model methods. The simulation results show the merits and potentials of the proposed RBFN approach.

The last paper entitled “Minimizing joint-torques of a flexible redundant manipulators based on vibration suppression” authored by Zhihui Gao, Chao Yun, and Yushu Bian studies the vibration control of a flexible redundant manipulator using mode theory. The active damping control is used to damp out its flexural vibration, and the corresponding control strategy is presented. The self-motion which meets the need of suppressing vibration is analyzed, and it is found that a flexible redundant manipulator still has the second optimization capability on the basis of its vibration being reduced. Then a method is proposed for minimizing joint-torques of a flexible redundant manipulator based on vibration suppression by using this second optimization capability. The results of some numerical simulations verify the effectiveness of this proposed method.

The guest editors would like to thank the authors and the reviewers for their contributions to this special issue. Moreover, we are grateful for the International Journal of Intelligent Computing and Cybernetics (IJICC) for the opportunity to publish and the journal editors for their insightful feedback to this special issue, their support and guidance in the publication. As guest editors, we hope that the selected papers in this special issue will stimulate further progress in the computational intelligence direction. We gladly believe that the best is yet to come.

Irwin KingDepartment of Computer Science & Engineering, The Chinese University of Hong Kong

Yangmin LiHong KongDepartment of Electromechanical Engineering, University of Macau, Macao