Study On Pyrolysis Kinetic Characteristics Of MSW And It's Artifical Networks Predication

Incineration technology was one of the main municipal solid waste (MSW) disposal measures employed in the world, and the kinetic parameters of MSW are important to the design and operation of thermal conversion systems. Because of the lack of kinetic parameters of MSW during designing thermal conversion systems, we use neural network model to predict these parameters. By means of neural network, only using the proportion of components of MSW can predict kinetic parameters. Because the proportion of components of MSW can be easily obtained, our predicting model will facilitate understanding pyrolysis kinetic characteristics of MSW without employing experimental methods.This dissertation was composed of some main parts as follow:This dissertation summariced international development of researches on pyrolysis kinetic characteristics of MSW and latest progress report for artificial neural networks systematically.This dissertation introduced the experiment device and pyrolysis kinetic model adopting by us. Kinetic characteristics of single component and their mixtures were studied. This paper revealed how each component interacts with each other and how they influence the kinetic characteristics of their mixtures.This paper introduced the process of constructing predication models for pyrolysis kinetic characteristics 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, and biases and learning rate.