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自然资源约束下的我国资源型区域可持续发展研究
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摘要
随着经济不断发展及资源短缺状况进一步加剧,资源型区域的可持续发展,不但是其自身的现实需要,也是我国和谐社会构建的关键所在,其现实意义、历史意义及理论意义明显。本文运用可持续发展理论、复杂系统理论、经济预警理论和界面管理理论,从资源型区域的经济发展规律和特征入手,结合BP神经网络及遗传算法构建相关模型,揭示了自然资源约束下资源型区域可持续发展系统的复杂性机理。研究包括以下内容:
     第一,借鉴系统理论,从当代哲学角度对可持续发展的内涵进行了剖析,探明可持续发展是科学技术上、经济价值上、伦理道德上“规范”的发展。并在资源型区域相关理论基础上,从整体视角,对自然资源约束下的资源型区域可持续发展系统进行了分析,构建了全文研究的理论框架体系。
     第二,基于经济预警理论,分析了资源型区域可持续发展预警的紧迫性和必要性。并在深入剖析各种预警方法优缺点的基础上,选择经遗传算法优化后的BP神经网络,作为资源型区域自然资源约束下可持续发展预警的有效科学方法。并将该算法对自然资源约束下可持续发展预警的实现过程,抽象为在输入模块、计算模块、输出模块之间进行的,从接收任务、确定目标到通过预警信号识别系统进行预警的流程。
     第三,研究了自然资源约束下的资源型区域可持续发展系统界面。借助系统动力学分析工具,对资源型区域可持续发展系统矛盾的集中点进行了剖析,研究了导致界面问题发生的、存在于各个子系统界面上的障碍,并从技术创新、制度创新、文化创新角度找到了界面障碍跨越的思路。
     第四,选择资源型区域的典型代表——山西省做实证分析,验证并完善了各种理论研究成果。在山西省经济资源现状的深入分析基础上,应用GA-BP预警模型,对其自然资源约束下的可持续发展状态进行现实判断。并应用界面分析的相关成果,提出合理化建议,以缓解山西未来生态承载的超负荷运转。
With the development of economy and the resources further aggravated situation, the sustainable development of resources region has an obvious sense in realism, history and theory. It is not only the reality needs of resource-based region, but also the key to build a harmonious society in China. In this dissertation, the use of sustainable development theory, complex system theory, economic early warning theory and interface management theory, combined with BP neural networks and genetic algorithms to build a model, reveals the complex mechanism of natural resource-constrained sustainable development system in resource-based region of China. The paper covers the following aspects.
     Firstly, from a philosophical point of view, it proves that the sustainable development is the common development on science and technology, economic value and the ethical norm by using system theory. On the basis of relevant theories, it analyzes the resource-based regional sustainable development system under the natural resources constraints to build a theoretical framework for the full text of the research system.
     Secondly, based on economic early warning theory, this dissertation analyzes the urgency and necessity of doing sustainable development early warning in resource-based region. Moreover it chooses the BP neural network optimized by the genetic algorithm as the efficiency method to the resources regional sustainable development early warning after in-depth analysis of the advantages and disadvantages of various methods. Then it also applies this model to the realization of sustainable ecological carrying capacity early warning.
     Thirdly, it researches interfaces of regional sustainable development system under the natural resources constraints. Using the system dynamics, the dissertation takes analysis on the conflict focalization between subsystems. It still points out the reason of causing interface barriers then finds the new ways spanning those barriers from technological innovation, system innovation and culture Innovation.
     Fourthly, this dissertation chooses Shanxi Province as a good resource-based region case in point to do empirical analysis and to verify a variety of theoretical research results. It forms a judgment of the natural resources constrainted sustainable development state in Shanxi Province under in-depth analysis of economic resourcesand the guidance of the GA-BP early warning model. Then it puts forward some reasonable suggestions to settle the overloaded ecological carrying of Shanxi Province in the future.
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