Early-Warning Of Sustainable Development Of Resource-Based Industrial Cluster In Yulin

Resources are the material basis of the survival of human society and economic development. The history of many resource-rich regions at home and abroad shows that the exploitation and utilization of resources not only brought rapid economic prosperity, but also led to the degradation of local economic, social and ecological environment. Industrial cluster is the characteristic of the resource-based industrial development. As an evolving body of life, in fact, industrial cluster is like a double-edged sword, and its risks and advantages exist side by side, and it cannot guarantee the sustainable development of regional economy. Therefore the ignorance of the sustainable development of resource-based industrial cluster may endanger an industry, or even a regional economy will enter recession for decades. As a result, it is essential for us to pay attention to the sustainable development of resource-based industrial cluster, explore the forming and operating mechanism of the resource-based industrial cluster, construct theoretical framework of early-warning on sustainable development of resource-based industrial cluster, and explore the strategies on the sustainable development on the resource-based industrial cluster. These strategies can ensure Yulin resource-based sustainable exploitation, promote the entire national economic development,and enhance the sustainable competitiveness of Yulin resource-based industrial cluster. So it is greatly significant in theory and practice to study early-warning of sustainable development on resource-based industrial cluster in Yulin.In the doctoral dissertation, the research illustrates the current study of early-warning of sustainable development of resource-based industrial cluster at home and abroad, defines the early-warning of the sustainable development of resource-based industial cluster and its characteristics. From the perspective of systematic analysis, the dissertation analyzes the elements forming of sustainable development of resource-based industrial cluster, and designs these early-warning indicators and the early-warning model in resource-based industrial cluster with the application of artificial neural network warning method and AHP.The dissertation combines the related data and early-warning model in an organic way by the use of artificial neural network tool in software Matlab7.1. The findings of the research offer some effective solutions to the contradictions among the regional economic development , the exploitation of resources,ecological environment protection and life level which help us correctly deal with the relations of nature, ecology,society and economy. economic development, population and environmental protection.The doctoral dissertation includes the following six parts;(1) The first part illustrates the reasons, purposes and significance of conducting the research, offers the full and systematic analysis of the previous and current related research at home and abroad, and introduces the innovations, research outline and method.(2) The second part, beginning with the definition and characteristics of resource-based industrial cluster, illustrates the conditions forming of resource-based industrial cluster and its meaning and characteristics. Based on these, the research offers the notion of the early-warning of sustainable development of resource-based industrial cluster, and constructs the theoretical framework for the early-warning of sustainable development of resource-based industrial cluster in Yulin.(3) The third part analyzes the components of sustainable development of resource-based industrial cluster, and offers the four subsystems which are economic subsystem, social subsystem, the environment subsystem and supported subsystem.(4) The fourth part constructs the early-warning indicators composed of 28 indicators. These indicators include four subsystem warning index of economic development,ecological environment,social development,and supporting subsystem.(5) The fifth part,through the construction of the early-warning model of sustainable development, the dissertation outlines Yulin resource-based industrial cluster warning system, predicts its'sustainable development degree with the help of the artificial neural network Matlab7.1, finally calculates the degree of resource-based industrial cluster sustainable development in Yulin.(6) The last part proposes some measures of the sustainable development according to the findings and the present situation of resource-based industrial clusters in Yulin.The innovations of the dissertation show themselves in the following two aspects:(1) Propose and calculate the Degree of Resource-based Industrial Cluster Sustainable DevelopmentIn the doctoral dissertation, the " Degree of Resource-based Cluster Sustainable Development" is proposed, and the early-warning model is constructed. This dissertation uses AHP to calculate the weight and the normalized score of every early-warning index, then calculates the degree of the sustainable development of each subsystem and resource-based industrial cluster about Yulin in 1998-2012. The concept is different from qualitative and static expression of of industrial cluster, and overcomes the dispersion of early-warning index system. So it predicts the development process and trend of the sustainable development of resource-based industrial cluster in Yulin by means of quantitative and dynamical way.(2) Examine the early-warning of Yulin resource-based industrial cluster with the application of the artificial neural networkFrom the industrial cluster researchs at home and abroad, it's still rare to apply the artificial neural network analysis to early-warning of sustainable development of resource-based industrial cluster, especially the research in depth and length. With the help of the warning function of artificial neural network, the dissertation constructs the early-warning model of sustainable development of resource-based industrial cluster. The dissertation maps out the various subsystems and the development trend of indicators in Yulin resource-based industrial cluster for the next five years.Based on the current development of resource-based industrial cluster in Yulin, the doctoral dissertation applies the artificial neural network to the construction of the theoretical basis of early-warning model in the sustainable development of resource-based industrial cluster. The findings show that the trend of sustainable development of industry cluster in yulin in 1998-2012 is good, the results correspond to the current situation of industrial development in Yulin, the designing of early-warning indicators of resource-based industrial cluster can effectively reflect the characteristics of resource-based industrial cluster, and the construction of warning model of sustainable development can accurately measure the development involved in resource-based industrial cluster, and early-warning function of artificial neural network can improve the accuracy of resource-based industrial cluster warning. Based on the results of the early-warning, the dissertation proposes some strategies of sustainable development of resource-based industrial cluster.