基于GM(1,1)模型的森林有害生物灾害预测  

Forest pest disaster prediction based on the GM(1,1) model

作　　者：高晓巍[1] GAO Xiaowei(School of Science,Qiqihar University,Qiqihar 161006,China)

机构地区：[1]齐齐哈尔大学理学院,黑龙江齐齐哈尔161006

出　　处：《高师理科学刊》2022年第12期23-26,共4页Journal of Science of Teachers＇College and University

基　　金：国家自然科学基金项目(30870434);黑龙江省自然科学基金项目(LH2020A023);黑龙江省省属高校基本科研业务费科研项目(135409318);黑龙江省省属高等学校基本科研业务费科研项目(135509121)。

摘　　要：近年来,我国森林有害生物防治与管理工作取得了阶段性的进展,但由于全球气候变暖、国际形式变化、人工造林数量增加等因素,森林有害生物灾害面积虽然得到逐步控制,但灾害的主要矛盾却悄然发生了变化.以中国2013—2020年森林虫害发生面积、森林病害发生面积、森林鼠(兔)害发生面积、森林有害植物发生面积的数据信息为研究对象,利用灰色预测模型能够在小样本信息中生成、开发、提取有价值信息的特点,对引起森林灾害的主要因素进行数据拟合与预测.对部分数据波动性比较小的情况,利用对数变换及变权实现了对初始数据的转换,提高了GM(1,1)模型的预测精度,为林业部门的管理与决策提供可靠的理论依据.In recent years,forest pest control and management of China have made some progress.However,due to global warming,the change of international form,and the increase of afforestation,although forest pest disaster area has been gradually controlled,the main contradiction of disaster has been changed quietly.Taking the data information of forest pest occurrence area,forest disease occurrence area,forest rat(rabbit)injury occurrence area and forest harmful plant occurrence area of China from 2013 to 2020 as the research object,data fitting and prediction for the main factors causing forest disasters was carried out by the grey prediction model,which can generate,develop and extract valuable information from small sample information.When the fluctuation of some data is relatively small,logarithmic transformation and variable weight are used to convert the initial data,which improves the prediction accuracy of the model and provides a reliable theoretical basis for the management and decisionmaking of the forestry department.

关 键 词：森林有害生物灾害 对数弱化缓冲算子 GM(1 1)模型 预测分析 

分 类 号：O29[理学—应用数学] S718[理学—数学]