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The flooding velocity is an important but difficult to accurately predict parameter for the packed column design. With the appearance of new packing shapes, traditional empirical models are insufficient to satisfy the requirement of engineering applications. In this paper, a novel approach using least squares-support vector machine (LS-SVM) is proposed to predict the flooding velocity in the randomly...
Futures price forecasting based on least squares support vector machine is presented in the paper. In order to improve the prediction performance of least squares support vector machine, the experimental data can be normalized and appropriate parameters are selected by genetic algorithm. Least squares support vector machine is used to create the prediction model for futures price, and BP neural network...
This paper proposes an algorithm which combines Particle Swarm Optimization (PSO) with Least Squares Support Vector Machines (LSSVM) to identify lithology by using well logging data. First of all, PSO is used for optimizing the main parameters of LSSVM, and then by using the optimized parameters to obtain a better PSO-LSSVM classification model which can be used to identify lithology with logging...
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