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A Novel Approach Based on SVM to Forecasting the Thermal Power Plant Construction Cost

Author: WuXiaoJuan
Tutor: KongFeng
School: North China Electric Power University (Hebei)
Course: Technology Economics and Management
Keywords: Thermal power plant Project cost Support Vector Machine Forecast
CLC: F224
Type: Master's thesis
Year: 2009
Downloads: 155
Quote: 1
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Abstract


Support Vector Machine is the statistical theory , machine learning , optimization theory and combination of structural risk minimization principle to establish the structure of the auto- learning model , the model structure is changed by adjusting the control parameters , become neural networks , fuzzy identification method For black-box method for identification of hot spots . It can be used to solve the practical problems of the small sample , nonlinearity , high dimension recognition and local minimum points . In recent years , it got a lot of applications in pattern recognition, regression analysis and feature extraction . The paper by exploring support vector machine thermal power plant project cost forecasting , so as to achieve the purpose of to seek a more rational , more rapid prediction method . System prediction method of the use of support vector machines , combined with the trends and characteristics of the cost of thermal power projects , the establishment of a thermal power plant project cost forecasting model to forecast project cost . And on support vector machine by way of example in the application and operation of the thermal power plant project cost forecasting process .

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CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
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