基于蚁群支持向量机的短期负荷预测

支持向量机(SVM)是一种在统计学习理论基础之上发展起来的针对小样本数据且具有优良推广性能的机器学习方法。阐述了SVM的基本原理及特性，并采用一种新的适用于连续问题的蚁群优化算法（MG-CACO）对SVM核函数的参数进行了优化。同时介绍了基于MG-CACO算法的支持向量机技术的设计思想和特点。并对一实际电网的短期负荷预测进行了实例研究，其结果验证了基于MG-CACO算法的支持向量机预测方法提高了预测精度，此方法在短期负荷预测中的可行性和有效性。

Short-term load forecasting based on MG-CACO and SVM method

Support Vector Machine(SVM) as a machine learning method is based on solid theory foundation of Statistical Learning Theory and focuses on small samples.It has good generalization and has received good applications.The theory and characteristics of SVM are expatiated,a new continuous ant colony optimization algorithm called MG-CACO is used to optimize the kernel parameter of SVM in this paper.The design idea and characteristics of MG-CACO and SVM are introduced .Then the application of SVM to a short-term l...