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1、河北工業(yè)大學碩士學位論文電力營銷決策支持系統(tǒng)中的電量預測分析與研究姓名:趙美麗申請學位級別:碩士專業(yè):計算機應用技術指導教師:沈西挺20070101電力營銷決策支持系統(tǒng)應用技術和電量預測算法研究 iiANALYSIS AND RESEARCH ON POWER QUANTITY PREDICTION IN THE POWER SALES DECISION SUPPORT SYSTEM ABSTRACT Electricity is

2、very important to the national economy, with the thoroughly reforming of electric power system, the marketing of the electrical enterprises becomes faster and faster. Electrical business is running into a high speed de

3、velopment stage and electric power is changing from “seller’s market” to “buyer’s market” gradually. In this situation, the traditional management and management system can't meet the current needs, so adopting an

4、efficient power sales decision support system is more and more important. Predicting is the foundation and premise of correct decisions. Therefore, power predicting is an important part of power sales decision support s

5、ystem and it plays an important role in power sales decision making. First, the background and meaning of the research work is analyzed. The development and present situation of the research both at home and abroad is su

6、mmarized. Then some existent problems from them are found. Based on these, the research target of this paper is determined. Secondly, the development and basic mode of DSS is analyzed and the principles and functions of

7、three important parts of DSS are expounded. The power sales DSS and some applying techniques is summarized. Then, the advices for improving man-computer interactive system are given and the twice extracting mode for elec

8、tricity data is designed. Thirdly, according to the analysis towards the feasibility, rules and common methods for power quantity predicting, two predicting ways: vertical predicting and vertical combining with horizont

9、al predicting are put forward. The predicting models are imported and the seeking of model parameters, models characteristic etc is analysis or deduced. The experiment towards power quantity in seven sections of Tianjin

10、is done and the parameters and initial values are determined through it. Then, the error degree resulted in the predicting experiment are contrasted and analyzed. At last, the research work is summarized. KEY WORDS: p

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