The Research Of Order Decision Support System Based On Big Data In The ERP Environment

In the fierce market competition, how to forecast the market price as well asestimate the cost of the order quickly and accurately is of great significance for assistingenterprises in bidding decision due to complexity and diversity of products, dynamics ofprice in raw material market, uncertainty of process routes and working hours. Orderdecision support system based on big data in the ERP environment is constructed basedon the analysis of traditional cost estimation, combining with ERP system and the latestbig data processing and analysis technology, JavaWeb technology, case-based reasoningtechnology, BP neural network technology, etc. The main work is as follows:（1）The theoretical basis and feasibility analysis of order decision support systembased on big data in the ERP environment. Firstly, the related theories and systemstructure of decision support system (DSS) is sorted. Secondly, the principles of CBRtechnology, BP neural network technology, big data technologies, used in the paper isdescribed. Finally, the feasibility of order decision support system based on big data inthe ERP environment is analyzed.（2）Order’s market price forecasting model, order’s current cost estimating modeland order’s future cost predicting model are established. Firstly, object-oriented caserepresentation model, case storage model, case similarity calculation model andcase-based reasoning BP neural network estimating the order’s market price model areconstructed. And business-oriented ERP order’s current cost and market priceestimating model and order’s future cost and market price trend predicting model basedon double exponential smoothing are built.（3）Distributed webpage crawling and data extraction model is constructed. Basedon the theory and technology of big data, Hadoop and Nutch-based distributed webpagecrawling and data extraction model is established, which is used to crawl materials price,calculate the producer price index (PPI) and other information.（4）Design and implementation of order’s intelligent decision support system. Byanalyzing the current and historical data of the ERP system (used B/S architecture,based on Java programming language, Extjs4.0, Struts2, Hibernate, Spring, etc.)developed by the author and his team, the prototype of order’s intelligent decisionsupport system based on Hadoop, Hbase, Nutch and other big data framework is designed and implemented.