摘要
针对群体智能和约束优化问题的特点,提出了将QPSO算法应用于求解约束优化问题,证明QPSO算法在SVM领域中具有很高的应用价值,并为解决大规模的QP问题开辟了一条新的途径。
According to the characters of swarm intelligence and constrained optimization, this paper proposed a method to solve a linearly constrained quadratic optimization problem in training support vector machines with QPSO. Testified QPSO has determinate applied value in the field of support vector machines, and it is a new way for quadratic programming problem with a large number of example vectors.
出处
《计算机应用研究》
CSCD
北大核心
2007年第7期94-96,119,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(60474030)
关键词
支持向量机
量子行为粒子群优化
二次规划
support vector machines
quantum-behaved particle swarm optimization （RPSO）
quadratic programming problem
