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As an effective global search method, genetic algorithm has obvious advantages. But it usually has problems of premature convergence and local optimum in practical application. According to this, a new algorithm with improved selection, crossover and mutation is proposed. Through the simulation experiments, the improved algorithm shows its faster convergence and better stability. It is valid which...
Support Vector Machine (SVM) is a useful technique for data classification with successful applications in different fields of bioinformatics, image segmentation, data mining, etc. A key problem of these methods is how to choose an optimal kernel and how to optimize its parameters in the learning process of SVM. The objective of this study is to propose a Genetic Algorithm approach for parameter optimization...
Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) and GA (genetic algorithm) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM and GA to improve the fault...
This paper presents the results achieved by fault classifier ensembles based on a model-free supervised learning approach for diagnosing faults on oil rigs motor pumps. The main goal is to compare two feature-based ensemble construction methods, and present a third variation from one of them. The use of ensembles instead of single classifier systems has been widely applied in classification problems...
The cancer classification through gene expression patterns becomes one of the most promising applications of the microarray technology. It is also a significant procedure in bioinformatics. In this study a grid computing based evolutionary mining approach is proposed as discriminant function for gene selection and tumor classification. The proposed approach is based on the grid computing infrastructure...
In order to more accurately predict industrial emissions, the paper selected BP and GA-BP neural network to establish the prediction model between the foreign trade and industrial waste discharge. Compared of different forecasting methods and examples of analysis of results, it shows that GA-BP neural network had higher accuracy, tolerant and excellent generalization ability than other model on ecology...
The Internet's numerous benefits have always been coupled with shortcomings due to the abuses of online anonymity. Writeprint identification is a technique to identify individuals based on textual identity cues people leave behind online messages. Character n-gram is one of the most effective approaches to identify writeprint according to previous research. In this study, we propose a variable length...
Recently, multi detector row computed tomography (MDCT) has been introduced into medical fields. By the development of MDCT, images with high quality are provided into medical fields. So many related image processing techniques are proposed into medical image processing fields for extraction of abnormal area. In the medical image processing field, segmentation is one of the most important problems...
In the last years, the area of Multicriteria Decision Analysis (MCDA) has brought about new methods to cope with classification problems, among which those based on the concept of prototypes. These refer to specific alternatives (samples) of the training dataset that are good representatives of the groups they fit in. In this paper, experiments are conducted over two prototype selection (PS) techniques...
The feature subset selection is a key preprocessing part in the detection of the stored-grain insects based on the image recognition technology. According to the global optimization ability of the particle swarm optimization (PSO) and the superior classification performance of the support vector machines (SVM), this study proposed a method based on PSO and SVM to improve the classification accuracy...
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