| 集对分析在城市空气污染预报中的应用研究 |
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| 引用本文： | 诸晓明,王国强.集对分析在城市空气污染预报中的应用研究[J].应用气象学报,2006,17(1):124-128. |
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| 作者姓名： | 诸晓明 王国强 |
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| 作者单位： | 浙江省绍兴市气象台, 绍兴 312000 |
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| 摘 要： | 在城市空气污染预报模型中, 精心挑选的因子具有较好的预报性能, 但是因子的优良性能并非始终不变, 而有时个别因子的不良表现往往可能导致预报的失败。根据集对分析 (SPA) 把不确定性和确定性作为一个动态的同异反系统处理的思想, 动态地分析和处理每次预报中因子作用的变化, 即每次预报前, 先对因子进行态势判别和同异反分析, 然后使可能干扰预报的弱势因子的作用受到有效抑制, 使有助于预报的强势因子的作用得到充分发挥, 从而实现了因子作用大小在各次预报中的动态变化, 取得了较为满意的效果。在预报模型中增加不确定性处理有助于提高预报准确率。
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| 关 键 词： | 集对分析 不确定性 联系度 动态多元回归模型 空气污染预报 |
| 收稿时间： | 2005-03-11 |
| 修稿时间： | 2005-10-20 |
The Application of Set Pair Analysis on City Air Pollution Index Forecasting |
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| Zhu Xiaoming,Wang Guoqiang.The Application of Set Pair Analysis on City Air Pollution Index Forecasting[J].Quarterly Journal of Applied Meteorology,2006,17(1):124-128. |
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| Authors: | Zhu Xiaoming Wang Guoqiang |
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| Institution: | Shaoxing Meteorological Observatory, Zhejiang Province, Shaoxing 312000 |
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| Abstract: | The predictors of city air pollution forecast models which are specially selected have prefer forecast ability in general.But sometimes when the situation changes,some predictors are negative and may result in failure of the forecast model.According to the principle of Set Pair Analysis(SPA),regarding uncertainty and certainty as a dynamic systematic procession,the evolution of predictors' action in every forecasting is analyzed and processed dynamically.That is to say,the judgment of potential states and Identical-Discrepancy-Contrary Analysis are made about predictors before being used to calculate weather forecast,then the effect of predictors on weak potential state which may interfere forecasting is suppressed effectively,while those predictors on strong potential state which may be contributed to forecasting is given full play.As a result the dynamic evolution in the structure of predictors is made in the forecast model,and the rationality of forecasting mechanisms and the ability of models are intensified.So adding the processing uncertainty to the forecasting model is help to improve the forecasting accuracy. |
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| Keywords: | set pair analysis uncertainty connection degree dynamic multiple regression model air pollution forecasting |
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