摘要
为提高复杂环境模型参数识别的性能和效率,提出了改进单纯形法(IMSM)。该方法融合了随机全局搜索和单纯形法局部快速搜索两类算法的不同搜索机制,具有很强的广度搜索和深度搜索能力。以基于随机介质理论的抽水地面沉降时空耦合预测模型的参数识别为例,将IMSM算法应用于该模型中4个参数的优化识别。计算结果表明:无论在有扰动还是在没扰动条件下IMSM算法都能高效可靠地搜索到抽水地表沉降预计模型参数的全局最优解,说明此方法应用于复杂环境模型参数识别是可行的,同时,通过不同算法的比较也说明了IMSM算法在搜索性能和效率方面的优越性。
To improve the performance and efficiency of parameter identification in complicated environmental models,an improved simplex method（IMSM） is presented in this paper.The IMSM integrates a random global search algorithm and a simplex local search algorithm,and greatly enhances the capability of wide and deep searches.For instance,in the parameter identification for the time-space coupled predicting model,which predicts surface subsidence due to water pumping based on stochastic medium theory,the IMSM is applied to identify four parameters for the model.The results show that the global optimized solutions for these parameters can be reliably and effectively obtained under either the condition of non-disturbed data or the condition of disturbed data.This demonstrates that the IMSM is suitable for the parameter identification in complicated environmental models.Furthermore,the comparison among different optimized methods also shows that the IMSM has advantages in performance and efficiency over other methods.
出处
《辽宁工程技术大学学报（自然科学版）》
CAS
北大核心
2010年第6期1009-1012,共4页
Journal of Liaoning Technical University (Natural Science)
基金
河北省自然科学基金项目资助(E2010000872)
关键词
改进单纯形法
模型
参数识别
improved simplex method
model
parameter identification
