农机总动力影响因素的灰色关联分析——基于G-P算法  

Grey Correlation Analysis on Impact Factors of Agricultural Machinery Total Power——Based on GP Algorithm

作　　者：许淑芹[1] 周桂霞[1] 于海明[1] 金忠波[1] 张雪峰[1] 秦春兰[1] 

机构地区：[1]黑龙江八一农垦大学工程学院,黑龙江大庆163319

出　　处：《农机化研究》2016年第12期56-60 65,65,共6页Journal of Agricultural Mechanization Research

基　　金：黑龙江省自然科学基金项目(C2015037)

摘　　要：应用混沌理论中的饱和关联维数法(G-P)与灰色关联分析法,对黑龙江省农机总动力的影响因素进行量化分析;以黑龙江省农机总动力作为灰色关联的模型输出因子及饱和关联维数法计算的对象,从农业劳动力、土地生产规模、购买农机的经济环境及农机具的装备数量等4个不同的角度出发,选择14个不同的农机总动力影响因素作为灰色关联的输入因子。最终,由饱和关联维数法计算农机总动力的嵌入维数,并与灰色关联法对影响因素进行对比分析,得出了影响黑龙江省农机发展的8个主要影响因素,对主要影响因素进行了深入分析,并根据分析结果提出了促进农业机械化发展的建议。This paper use the GP algorithm and grey correlation to quantify the impact factors of Agricultural Machinery Total Power of Heilongjiang Province .It takes the Agricultural Machinery Total Power of Heilongjiang Province as gray re-lational model output factor and GP method of research object .From four different angles of agricultural labor , land pro-duction scale, to buy farm machinery economic environment, the number of farm machinery equipment to select 14 different Agricultural Machine Power factors as input factor of Grey Relational Model .The final step will combine the em-bedding dimension of Agricultural Machine Power which is calculated by GP method with the comparative Analysis result of gray correlation method 14 factors.It is observed that there are eight main factors affecting Agricultural Mechanization development of Heilongjiang Province .Overall, the main factors are deeply analyzed and some recommendations based on the analysis results to promote the Agricultural Mechanization development .

关 键 词：农机总动力 灰色关联分析 G-P算法 最佳嵌入维数 

分 类 号：S232.3[农业科学—农业机械化工程]