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# Article citations

L. S. Thomas. Decision making with the analytic hierarchy pro- cess. International Journal of Services Sciences, 2008, 1(1): 83-98.

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• TITLE: 基于模糊贴近度的震后恢复预测模型——以日本地震经济恢复为例A Forecast Model Based on Fuzzy Approach for the Recovery in Economy after the Earthquake——Illustrated by the Case in Predicting the Recovery in Japanese Economy after the Earthquake
• AUTHORS: 黄珂, 刘亚坤, 韩国文
• KEYWORDS: 地震恢复预测；模糊数学；主成分分析<br/>Earthquake Forecast; Fuzzy Mathematics; Principal Component Analysis (PCA)
• JOURNAL NAME: Finance Oct 15, 2014
• ABSTRACT: 现阶段，对地震恢复的预测往往缺乏系统的量化预测机制。能否有效地对地震的恢复进行预测，对政府正确评价和全面分析目标地震情况，展开合理的震后重建工作有着重要的指导作用。利用巨灾从发生到重建过程具有相似性的特点，选择历史上地震构建系统模型进行预测。在对照地震权值确定方面，引入模糊数学中贴近度。在实证部分，以对最近日本大地震恢复进行预测为例，将预测模型与真实预测情况进行拟合，效果显著。最后，为了能够详细说明预测对政府决策的潜在重要性，根据模型预测的日本综合恢复度和单个经济指标的恢复度，详细的从制造业，能源和投资三个方面探讨了本次地震对我国经济的影响。 At present, it lacks systematic quantitative forecasting models for the recovery in economy after the earthquake. On the other hand, only when the government makes a precise predication for the recovery of the earthquake could it have a sound and correct analysis on the earthquake to undertake proper practices for the reconstructing project after the earthquake. Therefore, after taking the similarity among disasters through- out the procedure of reconstruction into account, we establish the forecasting model via comparing several earthquakes which share most common with the target one. In addition, the degree of similarity in fuzzy mathematics is introduced here. In the empirical analysis section, the recent Japanese earthquake is used to illustrate the exactness of the model. The result of the empirical analysis shows a strong similarity between the real data and our forecasting ones. Last, in order to prove the importance for our model in the government policy after the earthquake, we thoroughly analyze the earthquake effect on our country under the section of manufacturing, energy and investment based on the economy as a whole and the main economic indictors’ recovery computed from our model.