Abstract: A long-term forecast method of timber growth ring density based on process neural network was proposed in this paper.Making use of the feature of process neural network with output function,after raw data are fitted to input functions and are represented as expansion of a same orthogonal basis,process neural networks is learned by hybrid genetic algorithm and the output function is obtained.The multi-pace long-term forecast is once achieved.Comparing with tradition time-series forecast method,the forecast precision is apparently improved.And a new method of time series long-term forecast question is provided in this paper.

Key words: growth ring density, long-term forecast, hybrid genetic algorithm, process neural network