| The prediction of basic data of land-use planning consists of several aspects, including population, urbanization level, gross domestic product, investment in fixed assets, total amount of arable land, total grain yield, every build terra and so on. A majority of previous land-use planning usually use traditional methods to predict basic data. These methods are single and the precision is very low, which give us a lot of errors in the procedure of prediction of demand and supply for land. It is an important question in land-use planning how to amend prediction model or seek much more appropriate and exacter model. So it is necessary to establish the basic data prediction system based on local area network, in order to achieve sharing query, feedback in time and improve the quality and efficiency of land resource management.There are many mathematic prediction methods to the population, total amount of arable land, total grain yield and investment in fixed assets by collecting domestic economy data and map based on the new land-use planning experiment of Liling, in Hunan province. Finally we build the most optimal prediction method through testing the error and precision for every model. On the support of Microsoft.NET, by C#, we build data prediction system based online, finish data query and prediction of basic data change in multi-period, improve the efficiency of office and sustain decision-making.Main results in this paper as follows:(1) Linear regression model, grey system model, logistic model and multivariate function regression model are built by using mathematical model, which are applied to prediction of population, total amount of arable land, total grain yield, gross domestic product and investment in fixed assets according to land-use planning basic data. The most optimal method for every object is selected according to simulating and analysing the prediction error and precision of basic data of land-use planning in Liling. |
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