基于改进粒子群优化算法的支持向量机参数优化及其应用

2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI:10.1109/iip57348.2022.00050

Lu Zhou, Yu-qing Cui

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引用次数: 0

摘要

提出了一种改进的粒子群优化算法，并将其应用于支持向量机的参数优化。通过优化后的支持向量机对典型的Mackey-Glass混沌序列进行预测，与普通粒子群算法组合后，仿真结果表明，该算法的预测误差远远小于普通粒子群算法的相应部分。

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Parameter Optimization and Its Application of Support Vector Machines Based on Improved Particle Swarm Optimization Algorithm

An improved particle swarm optimization algorithm is proposed, and it is applied to optimize the parameters of support vector machine. The typical Mackey-Glass chaos sequence is predicted through the optimized SVM, when comprised with the normal PSO algorithm, simulation results show that the arrived errors are far smaller than the corresponding part of normal PSO algorithm.

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2022 4th International Conference on Intelligent Information Processing (IIP)

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