Tender-assisted Decision-making Based On Data Mining Research

For a long time, the main method of resource outfit in bidding document of project is random mode, and the basis of decision making are tendering documents and means of bidding evaluation. Then it results the lack of scientific and systematic way. So that it is urgent to find a new and scientific method for decision making. Nowadays, many corporations already have abundant data of manpower, equipments, occupation, market, and so on, but these data resource have not brought much benefit in decision making effectively. On the other hand, data mining can mine useful knowledge or information from these massive data. In this dissertation, we combine the technology of data mining, existing resource of tendering corporation, tendering process and tendering discipline, and study the system of auxiliary decision making for bidding based on data mining. The main work and contributions in the dissertation are summarized as follows:1. The definition and basic idea of data mining are described, and then the operating process, types, and application are also analyzed deeply. At the same time, the basic conception, question class, function needed in decision-making supporting system are analyzed too. Additional, the usefulness of data mining in decision-making supporting system is explained.2. The architecture of decision-making supporting system based on data mining is designed. Firstly, the requirement about data, tendering policy, work process, decision making modes, is discussed. And then the software and hard architecture of the system is designed in detail. Besides, the system is divided into several sub-systems according to the functionality.3. Based on the analyses of method of designing database, the requirement of database in the system is discussed, and accordingly, the conceptual model and logical model of database is designed.4. Two decision-making models are discussed, which are decision-making model based on gray theory and decision-making model based on artificial neutral network. The main content analyzed is the working principle and the working process. The modifications to the models for our system are explained also, and some examples is given for demonstration.5. The implement of the system is discussed in this section, including the selection of developing environment, developing tools, database, and so on. And the important interface and algorithm code in the system are described in this chapter, such as algorithm of artificial neutral network.