摘要
森林自然稀疏规律的研究已经有了很大发展，并提出了许多经验的或理论的表达式。本研究介绍了人工神经网络方法，首次建立了马尾松人工林自然稀疏规律的三层前馈反向传播神经网络模型。仿真结果表明，人工神经网络模型能很好地符合实际的观测资料，具有良好的使用价值，从而丰富了该领域的研究方法。
The research on forest self-thinning has been developed greatly, and a lot oftheoretical or empirical formulations were proposed. In this paper a method of artificialneural network is introduced, and a model of three-level feedtoward back-propagationneural network to simulate self-thinning law of Pinus massoniana is established for the firsttime. The result of simulation shows that artificial neural network model can fit the observeddata very well, and it is very useful in practice, which will enrich the research method offorest self-thinning.
出处
《热带亚热带植物学报》
CAS
CSCD
1999年第3期210-216,共7页
Journal of Tropical and Subtropical Botany
基金
福建省自然科学基金!F991
关键词
人工神经网络
马尾松
密度
Artificial neural network, Pinus massoniana, Density change
