Over the last few decades, several computational intelligence paradigms have been established and recently, hybridization of computational intelligence techniques are becoming popular due to their capabilities in handling many real-world complex problems, involving imprecision, uncertainty, vagueness, and high dimensionality. The objectives of the international meetings fused under the umbrella of the Hybrid Intelligent Systems (HIS) conference series are to increase the awareness of the research community of the broad spectrum of hybrid techniques, to bring together computational intelligence researchers from around the world to present their cutting-edge results, to discuss the current trends in HIS research, to develop a collective vision of future opportunities, to establish international collaborative opportunities, and as a result to advance the state of the art of the field. The Seventh International Conference on Hybrid Intelligent Systems (HIS’07) was successfully organized during 17–19 September 2007 in Kaiserslautern, Germany, and gathered individual researchers from over 15 countries. HIS’07 was technically co-sponsored by IEEE Systems Man and Cybernetics Society, Deutsches Forschungsinstitut Für Künstliche Intelligenz (DFKI), Fraunhofer Institut Technound Wirtschaftsmathematik (ITWM), the German Chapter of IEEE Computational Intelligence Society, the Arbeitskreis Bildanalyse und Mustererkennung Kaiserslautern (BAMEK), The World Federation on Soft Computing (WFSC), and Phytec Messtechnik GmbH. The HIS’07 program committee represented 23 countries on five continents. All submitted papers were reviewed by at least three independent referees and, in some uncertain cases the number of referees was up to four. Based on the referee’s reports, the HIS’07 Program Committee selected 52 papers for oral presentation and 13 papers for poster presentation and the proceedings were published by IEEE Computer Society, USA. This special issue composing of five papers is focused on various hybrid computational intelligence approaches and its applications. Papers were selected on the
[1]
Thomas M. Breuel,et al.
A Branch and Bound Algorithm for Finding the Modes in Kernel Density Estimates
,
2009,
Int. J. Comput. Intell. Appl..
[2]
Kurt Geihs,et al.
Combining Genetic Programming and Model-Driven Development
,
2009,
Int. J. Comput. Intell. Appl..
[3]
André Carlos Ponce de Leon Ferreira de Carvalho,et al.
Evaluation Functions for the Evolutionary Design of Multiclass Support Vector Machines
,
2009,
Int. J. Comput. Intell. Appl..
[4]
Andreas König,et al.
Fully Evolved Kernel Method Employing SVM Assessment for Feature Computation from Multisensor Signals
,
2009,
Int. J. Comput. Intell. Appl..