Abstract

Artificial Neural Network (ANN) is a new type of intelligence system, which imitates the biological neural contracture. It is a never-unit-linked network based on the theory of biology nerve nets. It mainly researches the information distribution and signal process in the complicated multi-dimensional non-linear system, also the principle and method of signal processing, at the same time, applies them to solving the practical problems in engineering. The research on this subject combines the fundamental subjects such as biology, cognitive science, non-liner science with these engineering subjects like computer, electronics, AI, information processing, model recognizing and so on. It has a bright applying promise. BP neural network is a multi-layer feed-forward artificial neural network which is the most widely used and researched at present. It has simple structure, good non-linear quality, extremely high fitting accuracy, flexible and effective storage, and the hierarchy of model structure is easy to implement. In this paper, a simple and feasible BP neural network model, whose strong nonlinear ability is utilized, to predict the potential distribution of Mikania micrantha in Guangzhou. An improved model based on LM algorithm is proposed, and the results show that the potential distribution area and the actual distribution area have a good correspondence.

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