Using Neural Networks to Integrate Structural Analysis Package and Optimization Package
學年 103
學期 2
出版（發表）日期 2015-03-25
作品名稱 Using Neural Networks to Integrate Structural Analysis Package and Optimization Package
作品名稱（其他語言）
著者 Kao, Chin-Sheng; Yeh, I-Cheng
單位
出版者
著錄名稱、卷期、頁數 Neural Computing and Applications ,pp.1-13
摘要 To solve structural optimization problems, it is necessary to integrate a structural analysis package and an optimization package. Since most structural analysis packages suffer from closeness of system, it is very difficult to integrate it with an optimization package. To overcome the difficulty, we propose a possible alternative, DAMDO, which integrate Design, Analysis, Modeling, Definition, and Optimization phases into an integration environment as follows. (1) Design: first generate many possible structural design alternatives. Each design alternative consists of many design variables X. (2) Analysis: employ the structural analysis software to analyze all structural design alternatives to obtain their internal forces and displacements. They are the response variables Y. (3) Modeling: employ artificial neural networks to build model Y=f(X) to obtain the relationship functions between the design variables X and the response variables Y. (4) Definition: employ the design variables X and the response variables Y to define the objective function and constraint functions. (5) Optimization: employ the optimization software to solve the optimization problem consisting of the objective function and the constraint functions to produce the optimum design variables X*. Optimization of truss structures were used to validate the DAMDO approach. The empirical results show that the truss optimization problems can be solved by the DAMDO approach, which employs neural networks to integrate the structural analysis package and optimization package without requiring direct integration of the two packages. This approach is promising in many engineering optimization domains which need to couple an analysis package and an optimization one to obtain the optimum solutions.
關鍵字 Artificial neural networks;optimization;truss structure
語言 en_US
ISSN 0941-0643 1433-3058
期刊性質 國外
收錄於 SCI
產學合作
通訊作者
審稿制度 是
國別 USA
公開徵稿
出版型式 ,電子版,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106191 )