Titlebook: Intelligent Computing; International Confer De-Shuang Huang,Kang Li,George William Irwin Conference proceedings 2006 Springer-Verlag Berlin

white-matter

思考而得

Meta-Learning Evolutionary Artificial Neural Networks Using Cellular Configurations: Experimental WoEANN framework, which used the direct encoding methods, and with the conventional design of ANNs. We demonstrated how effective is the proposed MLEANN-CA framework to obtain a design of feed-forward neural network that is smaller, faster and with better generalization performance.

Dedication

A Neural Network with Finite-Time Convergence for a Class of Variational Inequalitiesnetworks, the new model is suitable to parallel implementation with lower complexity, and can be applied to solve some nonmonotone problems. The validity and transient behavior of the proposed neural network are demonstrated by numerical examples.

linguistics

Chaotic Neural Network with Initial Value Reassigned and Its Applicationet the increasing convergence rate and the decreasing searching time. The controlled numerical experiments with the Travel Salesman Problems (TSP) show that the proposed method has better global searching ability.

macular-edema

Chaotic Synchronization of Hindmarsh-Rose Neural Networks Using Special Feedback Functionse of networks with three neurons. It is shown that with increasing of the number of the coupled neurons, the coupling strength satisfying stability equation of synchronization decreases in the case of all-to-all coupling. Besides, the influences of noise to synchronization of two coupling neurons are given.

四海为家的人

Improving the Intelligent Prediction Model for Macro-economyparameters of the membership functions. The experimental results of the system indicates that the method is efficient and robust, producing high-precision results. This method could be extended to other application areas.

occult

Comparative Study on Input-Expansion-Based Improved General Regression Neural Network and Levenberg-ern space and thus leads to the samples data more easily separable. The classification results for both Iris data and remote sensing data show that general regression neural network is superior to Levenberg-Marquardt BP network (LMBPN) and moreover input-expansion method may efficiently enhance classification accuracy for neural network models.

付出

Fast Kernel Classifier Construction Using Orthogonal Forward Selection to Minimise Leave-One-Out Mison rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.

jumble

Patrimony

Improving the Combination Module with a Neural Network, we have performed a comparison among 6 classical combination methods and the two versions of . in order to get the best method. The results show that the methods based on . are better than classical combination methods.