Municipal Solid Waste Planning And Management, Intelligent Decision Support System

Municipal solid waste (MSW) management is an important content of social economy development general planning. Scientific and reasonable MSW management is very important for protecting city environment and promoting sustainable development of social economy. However, now the factual management is always lack of scientific decision-making and objectivity, pursuing the form one-sidedly while neglecting the quality, paying attention to local management while neglecting comprehensive management due to lacking whole conception, which leads to MSW management in form. In addition, in technical method of management, although application of computer substitutes for conventional manual method step by step, the decision-making of management is still manual work and that most of information management are restricted to attribute data, not involving in decision process of spatial distribution. So aiming at the problems of present MSW management, the dissertation sets up a decision support system for MSW planning and management by forming relevant aid decision-making models and integrating with artificial intelligence and GIS to realize decision visualization and intelligentizing, which can provide technique support for MSW planning and management scientifically, reasonably and efficiently.Intelligent decision support system (IDSS), a latest-model information system that introduces artificial intelligent technology into decision support system, concentrates on semi-structural and non-structural matter. Based on the groping research of the principle, the model and the realization method of MSWIDSS(Municipal Solid Waste Intelligence Decision Support System), the dissertation presents an intelligent decision-making method for municipal solid waste planning and management and studies the organization of decision-making model system the design for model base system, the establishment of intelligent model and visualization model outstandingly combining with practice.Firstly, after consulting many domestic and foreign literatures, the studies of MSW management were comprehensively summarized in this dissertation. Starting with the practice of MSW management operation, the dissertation defines the concept and meaning of MSW management system. And then according to the sustainable development of MSW management, the necessity of MSW planning and management is pointed out and its principle is dissertated. On the basis of these, the dissertation put more forward the key of MSW planning and management is the quantity determination and spatial distribution of MSW treatment facilities as well as system planning from which an organizing system of MSW decision-making models is set up. Aiming at the practice and characteristic of Kunming city, by means of the mutual collaboration among model-base, data-base and expert knowledge-base, multilayer decision-making is come true and a comparatively perfect MSWIDSS is designed and realized with visual and intelligent characteristics for the first time.Secondly, starting with the practical of MSW planning and management, combined traditional mathematics modeling method with artificial intelligence, the dissertation elucidates how to solve the uncertain, and the non-construct problem and the problem of the accurate model which is hardly built by means of mathematical formulation, through multi-attributes expert decision model of MSW facilities site selection and artificial network model of MSW amount and ingredients forecast. Thus, it is possible that the application system possesses the function of intelligent decision-making.Thirdly, in traditional BP neural network modeling, by introducing Levenberg-Marquardt algorithm, a MSW prediction model based on LMBP algorithm is developed. The model has stable performance and speedy convergence ability. Compared with the MSW prediction models in common use (e.g. grey-prediction model, MSW prediction method based on population growth), LMBP model has upmost prediction precision.Fourthly, aiming at that the complicated waste disposal facilities site selection need a great deal of expert knowledge, take a waste incinerator siting for example, multi-attribute utility evaluation decision criteria table is set up for the first time. The table with detailed and objective content is an important base by which expert knowledge can be transformed into systemic knowledge-database, and waste incinerator siting can be realized combining with mathematics planning model and multi-attribute utility evaluation method.Fifthly, take kunming city for example, on the basis of detailed research, MSW management system of kunming city is optimized roundly using planning and management model for the first time. It's result can serve decision-making of kunming municipality. Sixth, based on the decision-making models and integrating with GIS efficiently. The software platform of this system is ARCGIS and the development tool is VS.NET. Class libraries development method has been adopted and the functions include data base management, visualization inquiring of basic data and graph data, quantity determination of MSW disposal facilities, spatial distribution of of MSW disposal facilities, system planning and outputs of graphic chart have been realized. The system consists of spatial database, attribute database, model base, their corresponding management system and human-computer interactive interface, with the operating mode of models driving. The connection of models and data is realized by the perfect interface functions. The human-computer interactive interface provides information by Figure and data, while decision maker can set and modify model parameters by menu and dialog box. The system has friendly interface and with simplicity of operation and good adaptability.In conclusion, on the basis of the function, goal, technology requirement, system framework and design principle, the realization mechanism of MSWIDSS's system integrating from the organization system of decision-making models, data-base system, model-base system, artificial intelligent modeling and GIS module technique is expounded. Finally, an application system aimed to MSW planning and management is designed and realized.