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An Improved LS-SVM Based on Quantum PSO Algorithm and Its Application

机译:一种基于量子PSO算法及其应用的改进的LS-SVM

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In order to avoid the problem of inverse matrix calculation in LS-SVM algorithm, an improved LS-SVM based on quantum PSO algorithm is presented, the main process is to encode the particle swarm with quantum bit, then solve the linear equation set with the iterative quantum PSO algorithm. So the training velocity of LS-SVM algorithm is improved, the computer memory is saved, and the least square solution is always obtained. The actual application in Changqing oil-field indicates the application effect is better than that of classical SVM and LM neural network in oil layer recognition, the improved LS-SVM algorithm not only improves the accuracy of recognition, but also accelerates the velocity of convergence, and the result of oil layer recognition is fully accord with that of oil trial.
机译:为了避免LS-SVM算法中的逆矩阵计算问题,提出了一种基于量子PSO算法的改进的LS-SVM,主要过程是用量子位对粒子蜂拥,然后用Quantum比特求解线性方程式迭代量子PSO算法。因此,LS-SVM算法的训练速度得到改善,保存了计算机存储器,始终获得最小二乘解。长庆油田的实际应用表明应用效果优于古典SVM和LM神经网络的油层识别,改善的LS-SVM算法不仅提高了识别的准确性,还加速了收敛的速度,油层识别的结果完全符合石油试验。

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