| Summary: | 碩士 === 國立雲林科技大學 === 環境與安全工程技術研究所 === 88 === According to statistics, every business field spends more than NT$ 1 billion annually on the prevention and treatment of water pollution. However, it is difficult to acquire the information of cost trends for each department when listing the budget or estimating the cost due to lack of data. Another problem is that it is not easy to assess the benefits of construction. In addition, because of the rising awareness of environmental protection, more and more sewers and wastewater treatment plants are built. This is an urgent issue today. Moreover, how to make economic as well as rational plans and settlements before building the wastewater treatment plants has become a vital task for the government and private groups.
Therefore, this study focuses on the fifty of wastewater treatment plants which were built in Taiwan. The cost function estimates of wastewater treatment plants were compare and studied by using the Regression Analysis, Simple Linear Regression Model, Multiple linear Regression Model, Power Function Regression Model, Cobb-Douglas Function Model, Translog Regression Model, and Artificial Neural Network.
The results show that in each analysis using single variables and multiple variables to evaluate their influence on the total construction capital of wastewater treatment plants, the best estimating model is Artificial Neural Network which uses numerical data for the input type by accumulated generated operation. Through the way of accumulated generating operation could both reduce the randomization of the system and the disorder of the numerical data as well as increasing their regularity more efficiently and then enhance function of the Network. Therefore, the result of this study can be used by the government and the related authorities as the reference and basis when they draft the project of water pollution prevention and treatment. Moreover, they also can estimate the expense of construction and list the budget based on this reference when planning to build the wastewater treatment plant.
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