Font Size: a A A

Research On The Sustainable Development Of Mining Industry Of Guangxi

Posted on:2007-06-30Degree:MasterType:Thesis
Country:ChinaCandidate:Q P GaoFull Text:PDF
GTID:2189360185987331Subject:Mining engineering
Abstract/Summary:PDF Full Text Request
Sustainable development is not only the common development strategy for man to deal with and coordinate the interrelations of population ,resources and environment in the 21st centure , but also the only way for man to seek for better living and development. The sustainable utilization of the mineral resources and the sustainable development of the mining industry constitute important parts of the problems of sustainable development. The mining industry is one of the pillar industries of Guangxi and the sustainable development of the mining industry of Guangxi is of great significance to the economic and social sustainable development of Guangxi.By analyzing this paper deems the exploration and prospecting system of mineral resources a complex and time varying dynamic system, it has many factors and its dynamic system has properties of time-varying, non-linearity and random. With artificial neural network this paper forecasts the reserves of mineral resources that will be found out in the next five years. Based on analyzing the exploration and prospecting system of mineral resources with systems engineering theory, this paper brings forward several factors determining the reserves of mineral resources that will be found out: quantity and quality of the mineral resources in the region, the quantity and structure of the employees engaging in the mineral prospecting industry, the amount of geologic prospecting projects, the investment of geologic prospecting industry, the amount and investment and production of geologic prospecting scientific research projects, and growth rate of GDP. This paper presents an artificial neural network for forecasting the reserves of mineral resources that will be found out and then...
Keywords/Search Tags:Guangxi, mineral resources, artificial neural network, analytic hierarchy process
PDF Full Text Request
Related items