摘要
半导体制造系统的生产作业计划与调度优化困难、可行性较低的现状,对半导体制造系统的日产出预测提出了需求。在对预测研究现状进行分析的基础上,针对半导体制造系统的日产出时间序列体现的非线性的确定性而又类似随机的特点,提出一种基于混沌相空间重构的蚂蚁—神经网络模型的预测方法。混沌相空间重构理论用于日产出时间序列的重构;神经网络用于日产出预测模型的构建;蚂蚁算法用于神经网络预测模型的权值和阈值参数的训练。通过某企业的实际生产数据进行测试,并与传统的预测方法比较,证明了该预测方法的有效性。
In order to manage and control semiconductor wafer fabrication system （SWFS） more effectively, the daily output prediction data of wafer fabrication are often used in the planning and scheduling of SWFS. Because of nonlinear certainty and stochastic character of the daily output time series, an artificial neural network prediction method based on phase space reconstruction and ant colony optimization is proposed, in which the chaos phase space reconstruction theory is used to reconstruct the daily output time serials, the neural network is used to construct the daily output prediction model, the ant algorithm is used to train the weight and bias values of the neural network prediction model. Through testing with factory production data and comparing with traditional prediction methods, the effectiveness of the the proposed prediction method is proved.
出处
《机械工程学报》
EI
CAS
CSCD
北大核心
2009年第8期176-181,共6页
Journal of Mechanical Engineering
基金
国家自然科学基金资助项目(50575137)
关键词
日产出预测
相空间重构
神经网络
蚂蚁算法
Daily output prediction Phase space reconstruction Neural network Ant algorithm
