Sustainable Consumption Assessing And Warning System

Sustainable consumption is an essential part of sustainable development strategy. The realization of sustainable development is indispensable to sustainable production and sustainable consumption which is the mechanism of the former. The increasing expansion of human consumption demand has led to the predatory exploitation and damage of natural resources on earth, and serious pollution of eco-environment. Therefore, we could take sustainable consumption road, only through arresting unreasonable consumption demand, while we could come through ecological crisis only making sustainable consumption guiding human scientifically and reasonably consuming. Focusing on the importance of sustainable consumption is significant to promote economic, social as well as ecological sustainable development. For sorting out this subject, countries all over the world are actively seeking the way for sustainable consumption.By the author's documentary resources, there are massive researches on sustainable consumption both at home and abroad, including 1). Researches on concepts, connotations and meanings of sustainable consumption;2). Researches on the relationship of sustainable consumption and sustainable development;3). Researches on index system of sustainable consumption;4). Working out regional sustainable consumption strategy and specializing studies on trans-regional and transnational sustainable consumption. Based on a comprehensive analysis, the author points out there are some insufficiencies in those researches, such as placing too much emphasis on those concepts and theoretical analysis which are more qualitative researches. Although there are some sustainable consumption index at present, we have not built up compete evaluating and measuring system for sustainable consumption. So, this dissertation aims at establishing a system for assessing and measuring current sustainable lever, and using artificial neural network(ANN) to forecast sustainable consumption data as well as building on sustainable consumption warning system. This dissertation mainly solves the following key issues: establishing index system of sustainable consumption assessment, determining the contents of sustainable consumption assessment and using artificial neural network(ANN) to forecast sustainable consumption data as well as building on sustainable consumption warning system.Based on system analysis of consumption theory, this dissertation mainly studies on subjects like evaluating system of sustainable consumption, will put forward to the structure of assessment, system objective, index system and stages of assessment, build a sustainable consumption model, embody and determine index of assessment and contents, measure and evaluate the sustainable lever in the whole system., and by artificial neural network(ANN) build on a relatively complete sustainable consumption forecasting, assessing and warning system.There is five parts in this dissertation. The first part is an introduction, mainly introducing the occurrence and significance of sustainable consumption, discussing the theoretical sources of sustainable consumption, as well as putting forward the contents and logical structure of this research. The second part is an system analysis of sustainable consumption, mainly on equality, sustainability and harmony. Equality is the core of sustainable consumption, sustainability is the promise of a sound sustainable consumption, while harmony is the means of it. The third part is analysis of sustainable consumption index system. It tries to determine assessment index system of sustainable consumption, by analyzing about the establishing principle, structure, character and framework of sustainable consumption. The forth part is sustainable consumption assessing and warning system bas on ANN. It shows the function of sustainable consumption warning system, ANN and the design of warning system. The fifth part is the sustainable consumption assessing and warning system which is based on the application of ANN. Using ANN Tool of Matlab 6.5 to establish BP net forecasts sustainable consumption index, and then based on the outcome and factors of every index, it determines scores of these index, evaluates and warn of sustainable consumption system, and performs further analysis on the outcomes.This dissertation applies some economical theories, consumption economics and sustainable development theories and system theories to analyze the concepts, contents and index system, and to build up a sustainable consumption assessment system. And also, it combines methods of positivist and standard analysis , such as researches on the equality , sustainability and harmony are mainly with standard analysis, while the assessment of sustainable consumption is more with positivist method.The innovation in this dissertation is as following:1)the innovation of contents. At present , researches on this subject have placed too much emphasis on those concepts and theoretical analysis which are more qualitative researches. Although there are some sustainable consumption index at present, we have not built up compete evaluating and measuring system for sustainable consumption. This dissertation intents to building a sustainable consumption system, embodying and determine index of assessment and contents, determine the method of measuring sustainable consumption and establishing a relatively complete sustainable consumption assessing system.2). Innovation of research methods. The existing forecasting methods is linear analysis method. It has defects as it hard to cope with highly nonlinear model by index averaging, regression analysis, moving averaging models and also is lack of comprehensively applying various methods. However, sustainable consumption is a nonlinear, complex and open system. So far, we have not clear idea about the factors affecting it and the cause—effect relationship among them. In some sense, sustainable consumption system is still Black Box, or at least Grey Box. Therefore, the traditional linear method cannot be directly applied in this research. This dissertation uses BP neutral network's abilities of self-organized, self-adopted, and self-learnt, and the forecast for sustainable consumption assessment index achieves a good result. It overcomes the effects of artificial factors and fuzzy random during human assessment, assure precision of assessment, and has strong dynamic state. The nonlinear function applied which is more close to complicated nonlinear dynamic economic system. Can play a big role in preciously forecasting and warning.The deficiency in this dissertation is: Firstly, there is some doubt about scientific and reasonable assessment system. Based on system analysis theory and consumption theory, the author learned the former achievements and point out 5 subsystems and 33 index of assessment. However, the author still thinks the system is not enough mature, and needs further improvement. The major reason is the researches on consumption cover a wide field, including economy, society and resources, etch. So a practical way is to select relatively representative index. One single index cannot measure the differences among periods, among economic development across regions, among resources and environment, among cultures and among social institutions. In addition, considering the availability of data, those index with unavailable data have to be deleted, or be instead by proxy index. For the establishment of sustainable consumption assessment is heavily effected by man-made factors, the system requires expertise experiences and continuously adjustment.Second issue is assessing the forecast precision of index. ANN model in this dissertation has some limits as following: BP net has a slow convergence speed during learning course, which would result in local minimum value; the selection of structure of net and parameters are lack of theoretical support, it is just tentative and error-oriented; ANN model is Black Case work, it is lack of interpretive ability and theoretical foundation, etc. Besides, the whole forecast and warning system is based on the factual data. If the original data is not credit or missing, the outcome will not be worthwhile, and the aim of warning system is hard to achieve.Because of the author's ability and time schedule, the research in this dissertation is not well thought out. So please oblige me with teachers and classmates valuable comments.