Research On The Process Cost Estimation Based On Features And Intelligent Computation

Modern enterprises are experiencing the fierce market competition. The changing of themarket demand and technical innovation, the development of international trade andeconomic globalization has made products have shorter life cycle and faseter developmentspeed. The cost estimation and control can reduce the waste of resources in labor power,material and financial and improve the techinal level of the enterprises and even the wholemanufacturing.This paper which is from the perspective of cost refine management combines with theconditions of the short development time and insufficient basic data, labour power, materialand financial resources. Propose the method of the process cost estimation based on featuresand intelligent computation.The theories of cost accounting, Enterprise Resource Planningand computer technology are used for reference. Estimate the cost of pruducts fastly andaccurately which has profound meaning to improve the competition ability and productionenvironment of the enterprise.The article first discusses the background, purpose and significance of the research andthe state of the related situations and problems. Then discusses the basic knowledge of theprocess cost estimation, the flow of the process cost estimation based on working procedure,intelligent calculation method and characteristics, the definition of the product features, theflow of process cost estimation based on features and intelligent calculation, process featuresmethod, the definition of Fuzzy set, the representation fuzzy membership function andrelation, Rough sets and its basic ideas and neural network model. Through the research forthe process cost estimation method based on working procedure estimate the process cost ofproducts. This can be used for simulation and forecast on process cost estimation based onfeatures and intelligent computation. Then establish the features-process cost model, eliminatethe fuzziness of the process cost features model by using the fuzzy theory method. Deal withthe incomplete and inaccurate datas in the process cost feature model for the analysis andsimplification of the characteristic attributes, and programme with MATLAB. Finallysummarize the problems when programme MATLAB-BP neural network program. Simulateand forecast the model through the MATLAB programs and compare different BP networkprograms with different parameters. This can make the result predicted reach higher precisionand meet the needs of the process cost estimation.