关键词: 人工时, 化工设备设计, 定量预测, BP神经网络, 遗传算法, 支持向量机

Abstract: Aiming at the low prediction accuracy of man-hour estimation,a man-hour quantitative forecast model based on Genetic Algorithm_Back Propagation (GA_BP) for chemical equipment design was put forward.The management workflow and design features of chemical equipment design project were analyzed,and the historical data in user database were counted.The parameters' contribution and correlation analysis for statistical data were did to select proper input parameters for the model based on the acquirable difficulty levels of parameters during the forecast phase.A man-hour forecast model based on BP neural network was implemented,and the modeling of GA_BP and Support Vector Machine (SVM) algorithm were selected for defect of BP algorithm.The result showed that GA_BP algorithm was more suitable for the man-hour forecast of chemical equipment design.An application case modeled by GA_BP was presented.

Key words: man-hour, chemical equipment design, quantitative forecast, back-propagation neural network, genetic algorithms, support vector machine