Preface of the Special Issue on Hybrid Intelligent Systems using Soft Computing Techniques

The special issue on hybrid intelligent systems using soft computing techniques comprises seven contributions, which are representative of the state of the art in this area. The papers describe different contributions to the area of hybrid intelligent systems with application on control, pattern recognition, time series prediction, and automation. In the papers, optimal combinations of intelligent techniques are applied to solve, in an efficient and accurate manner, problems in particular areas of application. The first paper, " Optimization of the Fuzzy C-Means Algorithm using Evolutionary Methods " , by Oscar Castillo et al., proposes a novel approach to the optimization of the Fuzzy C-Means algorithm by evolutionary or bio-inspired methods, this in order to automatically find the optimal number of clusters and the weight exponent. The optimization methods used for the realization of this paper were genetic algorithms and particle swarm optimization. The results obtained by both methods are presented, and a comparison between both methods to observe if one method is better than the other. The second paper, " Artificial Neural Image Processing Applications: A Survey " , by Juan Ramirez-Quintana et al., provides a review of neural networks applied in image processing. Artificial Neural Networks (ANNs) have been useful for decades to the development of Image Processing algorithms applied to several different fields, such as science, engineering, industry, security and medicine. This close relationship between ANNs and Image Processing has motivated a study of 160 papers that propose and deal with said algorithms. The information contained in these papers is analyzed, commented and then classified according to its contribution and applications. Then, some important aspects of recent visual cortex-based ANN models are described to finally discuss about the conclusions reached throughout the process. The third paper, " Automatic Handling of Expert Knowledge Using Artificial Immune Systems Applied to Combinatorial Optimization Problems " , by Francisco Javier Díaz Delgadillo et al., provides methods to reduce computing time of combinatorial optimization problems that can be applied to any population based algorithm such as: genetic algorithms, artificial immune systems, ant colony optimization, etc. To demonstrate the usefulness of the proposed methodology an Artificial Immune System was used since we used concepts derived from this paradigm. The proposed methodology was applied to solve the Traveling Salesman Problem (TSP) and it is introduced the concept of vaccination to reduce cities in the TSP. It is able to work practically with any optimization population …