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粮食生产潜力短期预测的“趋势-波动模型”的验证 |
Verification of“Trend-Volatility Model”in Short-Term Forecast of Grain Production Potential |
Received:August 11, 2015 |
DOI:10.13254/j.jare.2015.0192 |
中文关键词: 粮食生产潜力;短期预测;趋势-波动模型;验证 |
英文关键词: grain production potential;short-term forecast;trend-volatility model;verification |
基金项目:中国农业科学院科技创新工程项目(2014-cxgc-hyl) |
Author Name | Affiliation | E-mail | MI Chang-hong | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | LIU Shu-tian | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | ZHENG Hong-yan | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | LI Jing-ya | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | HUANG Zhi-ping | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | HOU Yan-lin | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | bjyours@sina.com | WANG Nong | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | CAI Yan-ming | Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China | | WANG Shuo-jin | Beijing Research Center for Information Technology in Agriculture, Beijing 100089, China | | HOU Xian-da | Software Development and Service Center of Beijing Yours, Beijing 100089, China | |
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中文摘要: |
应用全国、31个省、6个典型地区和16个典型县的数据对粮食生产潜力短期预测的"趋势-波动模型"进行了系统性的验证和讨论。研究结果表明:(1)预测误差大小反映短期生产潜力的预测精度,预测误差大的主要原因是经济发达地区高产农田被大量占用和(或)蔬菜、水果种植面积大幅度增加而短期内使粮食单产下降;(2)小趋势修正方法是"趋势-波动模型"中不可缺少的一部分,它能将大趋势预测不能包括的短期如气象因素、科技投入、社会因素等影响纳入预测中,提高预测精度;(3)就我国近些年来的实际情况而言,越是经济发达的地区短期生产潜力的波动越大;同样发达地区短期潜力存在增加-下降-回升阶段;(4)就短期生产潜力预测精度而言:国家级大于省级、省级大于地区级、地区级大于县级;不同省、不同地区、不同县之间预测精度差别比较大,这与境内气候的互补性和农田抗御自然灾害的能力有关。 |
英文摘要: |
The "trend-volatility model" in short-term forecasting of grain production potential was verified and discussed systematically by using the grain production data from 1949 to 2014, in 16 typical counties and 6 typical districts, and 31 provinces, of China. The results showed as follows:(1) Size of forecast error reflected the precision of short-term production potential, the main reason of large prediction error was a great amount of high yield farmlands were occupied in developed areas and a great increase of vegetable and fruit planted that made grain yield decreased in a short time;(2) The micro-trend amendment method was a necessary part of "trend-volatility model", which could involve the short-term factors such as meteorological factors, science and technology input, social factors and other effects, while macro-trend prediction could not. Therefore, The micro-trend amendment method could improve the forecast precision.(3) In terms of actual situation in recent years in China, the more developed the areas was, the bigger the volatility of short-term production potential was; For the short-term production potential, the stage of increasing-decreasing-recovering also existed in developed areas;(4) In the terms of forecast precision of short-terms production potential, the scale of national was higher than the scale of province, the scale of province was higher than the scale of district, the scale of district was higher than the scale of county. And it was large differences in precision between different provinces, different districts and different counties respectively, which was concerned to the complementarity of domestic climate and the ability of the farmland resistance to natural disasters. |
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