太阳黑子与杉木生长关系  

THE RELATIONSHIP BETWEEN SUN-SPOT AND GROWTH OF CUNNINGHAMIA LANCEOLATA

作　　者：吴承祯[1] 洪伟[1] 姜志林[2] 

机构地区：[1]福建农林大学,南平353001 [2]南京林业大学,南京210037

出　　处：《应用与环境生物学报》2001年第2期106-112,共7页Chinese Journal of Applied and Environmental Biology

基　　金：福建自然科学基金!资助项目 (F991 )

摘　　要：根据多层误差反传网络结构模型和三次设计发展了一种太阳黑子人工神经网络预报方法 .以杉木胸径生长的年轮指数和太阳黑子自相关因子为输入变量 ,应用改进的人工神经网络方法建立了太阳黑子相对数年平均值的预测模型 ,模型的模拟回归优度为 93.3% ,预测精度达到 95 .74% .并对网络模型中各变量进行灵敏度分析 ,分析表明 ,杉木胸径生长的年轮指数对太阳黑子相对数年平均值影响较平坦 ,而太阳黑子自相关因子Yt-4 和Yt-2 对太阳黑子相对数年平均值影响较灵敏 ,3个因子对太阳黑子相对数年平均值均存在一定的影响 .图 2表 5参A new forecast method of sun-spot is developed based on the artificial neural network of the back propagation model. In this paper, the modified artificial neural network method is used to establish forecast model of sun-spot, regarding the ring index of diameter at breast height of Cunninghamia lanceolata and auto-correlated factors of sun-spot as forecast factors. The simulating regression precision of model is 93.3%, and the predicting precision of model is 95.74%. Based on the artificial neural network model, the sensitivity analysis on each variable of model shows that the effect of ring index of diameter at breast height of Cunninghamia lanceolata on sun-spot is even, and the effects of auto-correlated factors of sun-spot on sun-spot are sensitive, which shows that three variables all have significant effects on sun-spot. Fig 2, Tab 5, Ref 19

关 键 词：人工神经网络方法 太阳黑子 杉木生长 年轮指数 

分 类 号：S791[农业科学—林木遗传育种] P182.41[农业科学—林学]