Title
Engineering drawing man-hour forecasting based on BP-GA in design of chemical equipment
Abstract
The accurate man-hour forecasting is important in the control of project process and the optimization of human resources scheduling so as to cut the costs in the chemical plant design companies. This paper presents a framework, combining the Back Propagation (BP) Artificial Neural Network (ANN) and Genetic Algorithm (GA), for the forecast of Engineering Drawing Design Man-hour (EDDM), which is one of the most important work items in the design of chemical equipment. Based on the work flow analysis of chemical equipment design, the input variables are selected according to the result of contribution and correlation analysis. The data preprocessing and the forecasting model are also presented in details. Finally, the simulation results are discussed, which show that the model based on GA-BP ANN is better than the model based on the pure BP ANN, and the forecasting model based on GA-BP ANN is a helpful tool for EDDM forecasting.
Year
DOI
Venue
2014
10.1109/IConAC.2014.6935487
ICAC
Keywords
Field
DocType
production equipment,correlation analysis,data preprocessing,chemical industry,forecasting,process control,forecasting theory,eddm forecasting,chemical equipment design,project process control,chemical plant design company,forecasting model,human resources scheduling,engineering drawing man-hour forecasting,backpropagation,work flow analysis,optimization,genetic algorithm,ga-bp,engineering drawing man-hour,technical drawing,genetic algorithms,bp-ga,ga-bp ann,neural nets,back propagation artificial neural network
Man-hour,Engineering drawing,Scheduling (computing),Data pre-processing,Chemical plant,Engineering,Artificial neural network,Work flow,Backpropagation,Genetic algorithm
Conference
Citations 
PageRank 
References 
0
0.34
1
Authors
3
Name
Order
Citations
PageRank
Hua Ji100.68
Fu Xia200.34
Kai Cheng33912.36