Titlebook: Soft Computing in Industrial Applications; Recent and Emerging Ashraf Saad,Keshav Dahal,Rajkumar Roy Conference proceedings 2007 Springer-

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Object Recognition Using Particle Swarm Optimization on Fourier Descriptorsormations, presence of noise, and occlusion have been included as the part of the study. For simplicity, instead of objects, outlines of the objects have been used for the whole process of the recognition. Fourier Descriptors have been used as features of the objects. From the analysis and results u

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dura-mater

Differential Evolution for the Registration of Remotely Sensed Imagessting by means of a set of bidimensional remotely sensed images on two problems, i.e. mosaicking and changes in time. Registration is carried out by finding the most suitable affine transformation in terms of maximization of the mutual information between the first image and the transformation of th

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Geodesic Distance Based Fuzzy Clustering of problems simultaneously, it partitions the datasets into cluster of objects that are similar to each other and describes the clusters by cluster prototypes to provide some information about the distribution of the data. In most of the cases these cluster prototypes describe the clusters as simpl

Ibd810

Stability Analysis of the Simplest Takagi-Sugeno Fuzzy Control System Using Popov Criterionn with graphical interpretation, a sufficient condition in the frequency domain is proposed to guarantee the globally asymptotical stability of the simplest T-S fuzzy control system. Since this sufficient condition is presented in the frequency do-main, it is of great significance in designing the s

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Identification of an Experimental Process by B-Spline Neural Network Using Improved Differential Evog the learning procedure. To overcome the problems encountered by the conventional learning methods, differential evolution (DE) ( an evolutionary computation methodology ( can provide a stochastic search to adjust the control points of a BSNN are proposed. DE incorporates an efficient way of self-a

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B-Spline Neural Network Using an Artificial Immune Network Applied to Identification of a Ball-and-The learning procedure. When using feed-forward BSNNs, the quality of approximation depends on the control points (knots) placement of spline functions. This paper describes the application of an artificial immune network inspired optimization method ( the opt-aiNet ( to provide a stochastic search t

Infelicity

cortex

Application of a GA/Bayesian Filter-Wrapper Feature Selection Method to Classification of Clinical Darge set of features that were extracted from the speech of clinically depressed patients and control subjects, with the goal of finding a small set of highly discriminating features. Here, we report improved results that were obtained by applying a technique that constructs clusters of correlated f