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Human make behavior by perception, modeling believable perception for a virtual agent is a meaningful topic in computer games. A model of adaptive perception of a virtual agent with emotion is proposed based on Q-learning method; the formulas of emotion value are presented. A demo system is realized on PC; an agent with the model can dynamically control the range of the perception according to virtual...
Children like cartoon games, a cartoon game for children should support more knowledge. Leaning nonverbal emotion interaction is a very important social skill for a child, how to animate nonverbal emotion interaction in a cartoon game is an interesting subject. Emotion cognitive structure of a virtual character is presented, emotion expression method is also proposed, a virtual character can express...
The characteristics of data stream are infinite data and quick stream speed. Clustering modeling is an important method which link to the effect of clustering technology. A nice modeling method impacts on the performance of data stream mining system. In this paper put forward a model which named Compound Gaussian Mixture Model (CGMM) and the clustering algorithm of CGMM which combines classical GMM...
Feature selection is a very important part for datamining, machinery learning and pattern recognition. Distance plays a vital role in Support Vector Machines (SVM) theory. Relief-F algorithm solves feature redundancy well but doesn't guarantee the maximum distance. To overcome this problem, a feature subset selection algorithm is proposed which takes SVM average distance as estimation rule and sequential...
The amount of music information available on the Web is rapidly increasing. There is a pressing need for music information extraction. To extract useful information from natural language text, we must recognize music named entities first. This paper introduces a hybrid method to identify the Chinese named entities in music domain. Recently, machine learning approaches are frequently used to solve...
A hybrid artificial neural network (ANN) Lagrangian relaxation approach to combinatorial optimization problems in power systems, in particular to unit commitment is presented in this paper. Until now, the Lagrangian relaxation method has been studied as it appeared to be the most practical method for obtaining an approximate solution to unit commitment. Based on the use of supervised learning neural-net...
This paper proposes a new intelligent built-in test (BIT) fault diagnosis system based on wavelet analysis and neural networks. The aim of this investigation is to improve the fault diagnosis capability of intelligent BIT for More-Electric Aircraft Electrical Power System (MEAEPS). In constructing the BIT system, the wavelet packet transform is applied to extract fault features. Through the wavelet...
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