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A Research On The Optimization Of Regional Water-saving Agriculture Industrial Structure Based On Genetic Algorithms

Posted on:2009-03-21Degree:MasterType:Thesis
Country:ChinaCandidate:X DingFull Text:PDF
GTID:2132360242993449Subject:Water Resources and Hydropower Engineering
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China is deficient in water resources which lost balance in space and time. Agriculture is a big consumer of water which occupies 70 percent of the consumption. As the population of our country will reach 1.6 billion by this century, the demand of agriculture products and the demand of water in agriculture will get to the peak. While the water demand in industry and daily life will grow more with the urbanization and this will take up more water from agriculture. All the situation make it urgent to find ways in saving water of agriculture.Under the conception of water demand management, it is one of the methods to resolve the contradiction between socio-economic development and water resources by adjusting the regional agriculture industrial structure, developing high-effective and water-saving agriculture, in order to promote the development of society and water-saving.Starting from the basic theory study of structure adjustment in water-saving, this thesis found an optimized model of regional water-saving agriculture industrial structure and provide important theory and methods for agriculture industrial structure adjustment under the restrain of water resources. The main points are as follows.(1) This paper clarifies the objective and sense of the study, summarizes the present study situation of Genetic Algorithms and agriculture industrial structure adjustment home and abroad, points out the main problems in the study and state the study method and technology line.(2) This paper puts forward a fundamental train of thought of optimization in water-saving agriculture industrial structure: The optimization of water-saving agriculture industrial structure sets sustained and high efficient utilization of regional water resources as basic objective, takes the agriculture industrial structure adjustment and optimization as main measures, the water-saving engineering technology, water-saving agricultural technology and water-saving management technology as supports, comprehensively consider the balance in demand and supply of regional water resources, in order to accomplish the coordination and unity in regional water-saving, economy and society to a maximum.(3) This paper makes a thorough analysis of the sense in agriculture industrial structure optimization, takes the lowest agricultural water consumption and highest economic and society benefit as objective function, regards such elements as natural resources, plant area, ecology and society need as restrains, founds an optimized model of regional water-saving agriculture industrial structure.(4) This paper presents the basic principles and realization technologies in Genetic Algorithms, points out the defects of Simple Genetic Algorithms, introduces Stochastic Weight Assignment method to determine the weight, transfers the multi-objective model into single-objective model, founds a optimization results by Genetic Algorithms.(5)Taking Yangzhou as an example, this paper analyzes the natural resources, agricultural development and agricultural water consumption situation, calculates the agricultural water need of Yangzhou by applying quota methods, determines regular parameters in models according to the development plan of economy and society and agriculture of Yangzhou, forecasts the time-varying parameters in regional population and agricultural per unit area yield by applying the GM(1,1) model, founds a optimized model of Yangzhou agriculture industrial structure by applying Genetic Algorithms, this provides foundation for setting up reasonable and effective policies in agriculture industrial structure and promoting the sustained development in agricultural water-saving, agricultural production and rural economy.
Keywords/Search Tags:water-saving, agriculture industrial structure, multi-objective optimization model, Genetic Algorithms, GM(1,1) model, stochastic weight assignment method
PDF Full Text Request
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