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Article
Publication date: 7 November 2016

Tianxiang Yao, Wenrong Cheng and Hong Gao

The purpose of this paper is to assess the natural disaster damage of Sichuan province and provide suggestions to prevent or decrease the loss owing to the natural disaster.

Abstract

Purpose

The purpose of this paper is to assess the natural disaster damage of Sichuan province and provide suggestions to prevent or decrease the loss owing to the natural disaster.

Design/methodology/approach

The disaster loss system of Sichuan is regarded as a grey system. Five evaluation indicators are selected such as the number of deaths, total affected area, collapsed houses, damaged houses, and the direct economic losses. Grey fixed-weight clustering approach is applied in the cluster analysis. In order to reduce the impact of human factors, grey correlation analysis method is applied to calculate the weights of grey fixed-weight clustering.

Findings

The results of this paper indicate that the frequency of occurrence of major natural disaster in Sichuan increased since 2008. The major natural disasters occurred in 2008, 2010, 2011, and 2013. In contrast, there was almost no major disaster during 2000-2007. Minor natural disaster occurred in 2002 and 2003.

Practical implications

Sichuan province is one of the provinces most affected by natural disasters in China. Natural disasters have occurred frequently in Sichuan province since 2008 and pose serious threats to life and property safety. They have become an important restricting factor for economic and social development. In order to prevent or decrease the effects of natural disasters, effective measures should be taken to protect the environment.

Originality/value

This paper first normalizes the raw sequence, calculates the weight, and then establishes the grey cluster model. A new method is applied to determine the weight when evaluating natural disaster damage.

Details

Grey Systems: Theory and Application, vol. 6 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 2 February 2015

Tianxiang Yao and Wenrong Cheng

The purpose of this paper is to find a method that has high precision to forecast the energy consumption of China’s manufacturing industry. The authors hope the predicted…

Abstract

Purpose

The purpose of this paper is to find a method that has high precision to forecast the energy consumption of China’s manufacturing industry. The authors hope the predicted data can provide references to the formulation of government’s energy strategy and the sustained growth of economy in China.

Design/methodology/approach

First, the authors respectively make use of regression prediction model and grey system theory GM(1,1) model to construct single model based the data of 2001-2010, analyze the advantages and disadvantages of single prediction models. The authors use the data of 2011 and 2012 to test the model. Second, the authors propose combination forecasting model of manufacturing’s energy consumption in China by using standard variance to allocate the weight. Finally, this model is applied to forecast China’s manufacturing energy consumption during 2013-2016.

Findings

The result shows that the combination model is a better one with higher accuracy; the authors can take the model as an effective tool to predict manufacturing’s energy consumption in China. And the energy consumption of China’s manufacturing industry continued to show a steady incremental trend.

Originality/value

This method takes full advantages of the effective information reflected by the single model and improves the prediction accuracy.

Details

Grey Systems: Theory and Application, vol. 5 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

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