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The deposition of the increasing municipal solid waste (MSW) has become one of the serious worldwide issues. The thermal treatment technology has become the dominant technology for MSW. The composition of MSW is very complicated and the pyrolysis process of MSW is a very complicated chemical reaction process, the people still can’t carry on the accurate description to the chemical reaction that take place during the pyrolysis process up to now.The familiar method that studies the pyrolysis of MSW is thermogravimetry analysis method. We change an angle to study the pyrolysis gas characteristic and make use of the ability of the artificial nerve network technique to catch non-linear regulation strongly. By inputting the environmental protection section statistics data, we carry on the estimate to the yield of the pyrolysis gas. This kind of the estimate can be the basis of the pyrolysis technique choice, design and the adjustment of the work condition. Through this kind of estimate, we can further the understanding of the pyrolysis mechanism.This paper overviews the pyrolysis technique of the domestic and the abroad to dispose MSW, and introduces the background, method, contents and significance of the research.Part Ⅰ, firstly, we selected typical six kinds of components(paper, food, textile, wood, plastic, rubber) as the experiment materials, and carried on the fast pyrolysis experiment on the each component of MSW to study the characteristic of the gas yield.Part Ⅱ, secondly, six components of MSW are mixed as the materials, and investigate the relationship of the gas yield and the heating value between the mixed garbage and the single garbage.Part Ⅲ, this paper introduced the process of constructing predication models for the pyrolysis gas yield of MSW, including mainly the selection of model structure, algorithm, node excitation function, number of neural networks, learning precision, node number of hidden layers, characteristics function, biases and learning rate.
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