The Applied Researchofthe Bpneural Network Model Improved By GA-LM Arithmeticabout The Update Of The Datum Land Pricein Yan’an City

Benchmark price is an important means of government regulation of the land market， and it has a great significance for the economic development of a city or even livelihood to determine the premium.There are so many factors influencing of the premium，in the weightsdetermining of every factors and the selection of benchmark price evaluation model there area lot of subjectivityempirical and uncertainty. The traditional land evaluation methods arealways time-consuming、low degree of intelligence and functionality by the mean time. So ithas certain reference value to solve the updating problems of the benchmark price in another new assessment model.For the unique learning ability and the advantages of parallel distributed processinginformation，the B-P neural network as a core part of the artificial network is widely used inall walks of life research. Neural network is suited to solve the inaccurate informationambiguity problem of multi-factors that have imprecise subjectivity and low intelligent，andthis determines the feasibility and rationality of B-P neural network benchmark premiumupdating. Since the B-P neural network has some flaws，and how to improve it andsuccessfully solve the practical problem is the hotspot in some related research areas.Based on the analysis of the influence factor and evaluation modelabout benchmark landprice，start from the characteristic and counting process of GA and LM arithmetic，study theassessment method of benchmark land price based on the B-P neural network combined GAwith LM arithmeticin tentative，analyze and demonstrate the rationality and feasibility of thismethod，apply to the update of datum land pricein Yan’an city successfully.