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Hunan Construction Land Demand Forecast

Posted on:2011-10-07Degree:MasterType:Thesis
Country:ChinaCandidate:H GuoFull Text:PDF
GTID:2199360305494489Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
The land for humans are basic of all production and living space, also the source of material wealth. Different from With the production characteristics of agricultural society, In the modern society, industrialization, urbanization continually promote the development of civilization, the people gave land more significance. The demand for it becomes more complex and varied. China has high population and land resources is tense. For the rational utilization of every inch of land, China's constitution provides the world's most rigorous land use policy。The development of the national economy needs to use the land for construction, "Enclosure", abuse of the land cause plantation destroy frequently occurred. As a result, nations must strengthen the regulation of land resources. For allocation of land resources's internal economic law and the government regulation, consider influence between construction land controlling and economic development, and prevent excessive construction land expansion. Therefore, hunan construction land demand forecasting is an important topic.This article focus on the topic in hunan province in recent years of economic and social development of the macro data and the end of the relationship between the construction land use acreage, introduces the related mathematical models predict,and according to the features of the influence factors choosing multiple regression method for fitting data, and the related factors for construction of prediction model. In the research process, system theory, induce deduction, comparison and empirical analysis, etc. Based on the domestic research and quantitative data related, constructs hunan construction land multiple regression forecasting model, and analyses its sophistication and rationality.
Keywords/Search Tags:Land for construction purposes, Forecasting, multiple regression method
PDF Full Text Request
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