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基于模糊时间序列的农用拖拉机总数量预测 被引量:1

Prediction of Total Number of Agricultural Tractor Based on Fuzzy Time Series
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摘要 改进一种模糊时间序列,应用于全国农用拖拉机总数量预测,并为我国拖拉机的发展提供合理的指导建议。与经典层次模型Song模型和Chen模型预测全国农用拖拉机总数量比较,改进的模糊时间序列模型预测的平均误差率降低了10多倍,且其计算过程大大简化,易于运用。预测结果表明:我国农用拖拉机总数量在缓慢增长,其中农用大中型拖拉机增长率高于小型拖拉机,与实际土地整治、大中型机械取代小微型机械下田作业的状况相符;大中型拖拉机配备的农具台数增长率大于农用大中型拖拉机的增长率,但拖拉机产能过剩,造成浪费,政府应合理调控。 An improved fuzzy time series is used to predict the total number of agricultural tractors in China. It also provides reasonable guidance for the development of tractors in China and compares with the classical hierarchical model Song model and Chen model to predict the total number of agricultural tractors in China. The average error rate of the improved fuzzy time series model is reduced by more than 10 times, and the calculation process is greatly simplified and easy to use. The prediction results show that the total number of agricultural tractors in China is increasing slowly. Among them, the growth rate of large and medium-sized agricultural tractors is higher than that of small tractors, which is consistent with the actual land consolidation that large and medium-sized machinery replaces small-micro machine in field operation. At the same time, the increase rate of farm tools equipped with large and medium-sized tractors is higher than that of large and medium-sized agricultural tractors, but the overcapacity of tractors causes waste, so the government should adopt reasonable regulation and control.
作者 王炎林 陈建 王卓 胡陈君 郑延莉 曹中华 方晶晶 罗泽勇 Wang Yanlin;Chen Jian;Wang Zhuo;Hu Chengjun;Zheng Yanli;Cao Zhonghua;Fang Jingjing;Luo Zeyoing(Southwest University , College of Engineering and Technology, Chongqing 400716, China)
出处 《农机化研究》 北大核心 2019年第4期251-256,共6页 Journal of Agricultural Mechanization Research
基金 重庆市重点产业共性关键技术创新专项项目(cstc2015zdcztzx80003)
关键词 农用拖拉机 预测 模糊时间序列 模型对比 agricultural tractor prediction fuzzy time series model comparison
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