| Based on the related time series data from 1978 to 2012 in Henan Province, constructed the genetic algorithm-BP neural network model and measured the intensive use of agricultural land. On this basis, using the cointegration theory, error correction model, general impulse response function and variance decomposition, researched the dynamic response relationship between intensive use of agricultural land and its influencing factors. The results showed that: There were a long-term equilibrium relationship between the comprehensive index of intensive use of agricultural land and per capita income of farmers, total value of farm output, per capital arable land and policy and rules. The promoting role to the intensive use of agricultural land by the per capita income of farmers, total value of farm output, policy and rules were more significant in long term. The per capita income of farmers and policy and rules was the major source for forecasting variance of intensive use of agricultural land. The total contribution was kept above 52%. But the contribution of total value of farm output and per capital arable land to forecasting variance of intensive use of agricultural land was below 14%. On the whole, the per capita income of farmers and policy and rules were the major factor to affec the intensive use of agricultural land. Finally, according to the research conclusion, put forward the related policy and suggestions. |