Zaiwu Gong

Risk assessment of rainstorm and flood disasters in China between 2004 and 2009 based on gray fixed weight cluster analysis

Rainstorm and flood disasters frequently occur in China, causing heavy losses for people’s lives and property and reducing the capability of sustainable development of the national and local economy. In this study, the risks of the rainstorm and flood disasters are assessed for the Chinese mainland, excluding Hong Kong, Macao, and Taiwan and also employ the historical data of seven indicators, including the affected area of crops, the affected population, the direct economic loss, and etc., from 2004 to 2009. Based on the large 1,302 historical sample data, the impact of rainstorm and flood disasters were analyzed using the methodology of gray fixed weight cluster analysis according to disaster losses, which were divided into the three gray classes of high, medium, and low. The regional differences of the risk assessment of the rainstorm and flood disasters are discussed, and the dynamical risk zoning map is conducted. The results show a consistent conclusion with the actual losses of rainstorm and flood disasters over each administrative district, which can provide more scientific evidence for the relevant departments of disaster prevention and mitigation.

Generalized discrete GM (1, 1) model

In this paper a generalized discrete GM(1,1) model with optimized initial value (GDGM) is put forwarded to provide the solution steps in order to solve the grey prediction modeling of non-equidistance series. This method can be utilized in solving the non-equidistance grey prediction problem with integral interval or digital interval. The GDGM model has no strict data requirement to the raw data sequence. It expands the application range of traditional GM(1,1) model and non-equidistance grey prediction model in many aspects and has higher prediction accuracy. The numerical results indicate GDGM model can perfectly simulate non-equidistance exponential series.

Efficiency assessment of the energy consumption and economic indicators in Beijing under the influence of short-term climatic factors: based on data envelopment analysis methodology

In this paper, the data envelopment analysis (DEA) method is introduced to analyze the input–output efficiency of energy consumption and economic indicators in Beijing city under the influence of short-term climatic factors. Total energy consumption, fixed asset investment, average temperature, precipitation, sunshine hours, average wind velocity and the average pressure being employed as the input variables, gross domestic product (GDP) and per capita disposable income being employed as the output variables, effective technology and the validity of the scale of DEA of 31 decision-making units (DMUs) under the influence of the short-term climatic factors are analyzed, and the inefficient DMUs are improved. Empirical analysis shows that both energy consumption and economic growth are sensitive to short-term climate condition, and the reasonable employing of extreme climatic conditions is a question worthy of consideration. This study provides effective basis for the scientific and reasonable arrangement of Beijing city’s short-term climatic resources and energy–economic development.

The comprehensive risk evaluation on rainstorm and flood disaster losses in China mainland from 2004 to 2009: based on the triangular gray correlation theory

In this paper, we introduce the gray correlation method of risk evaluation in meteorological disaster losses based on historical disaster data in China (mainland) and apply the improved gray relational analysis model (the triangular gray relational model) to the risk evaluation of rainstorm and flood disaster losses. In addition, we divide the risk grade standards of rainstorm and flood disaster losses according to 186 rainstorm and flood disaster data of four optimization indexes (disaster area, suffered population, collapsed houses, and direct economic losses), evaluate the extent of dynamic rainstorm and flood disaster losses in 31 provinces of China (Hong Kong, Macao, and Taiwan exclusive) comprehensively, and draw China’s zoning map of rainstorm and flood disaster from 2004 to 2009. The method provides reasonable and effective references for national disaster preventions which can be used in other researches focused on risk evaluation of meteorological disaster losses.

Co-integration analysis between GDP and meteorological catastrophic factors of Nanjing city based on the buffer operator

This paper analyzes the relationship between meteorological catastrophic factors and gross domestic product (GDP) growth rate of Nanjing city (China). The sample spans the period 1980–2010, including GDP growth rate and meteorological catastrophic factors (extreme precipitation, extreme temperature and extreme wind speed). We utilize econometric methods to take co-integration analysis and Granger causality test among GDP growth rate and the time series of meteorological catastrophic factors of Nanjing city processed by buffer operators. Finally, the paper shows the short-term changes in minimum atmospheric pressure, extreme high temperature, and minimum relative humidity, which has a positive impact on GDP; the cumulative effect of extreme precipitation and GDP affects each other to some extent, they are mutually Granger causes. Moreover, at the 95xa0% confidence level, we believe that maximum wind speed is the Granger causation of GDP growth rate.

Group decision making methods of the incomplete IFPRs and IPRs

Abstract We propose optimal priority methods on the incomplete intuitionistic fuzzy preference relation (IFPR) and the incomplete interval preference relation (IPR). The least squares method has been used previously to derive the priority vector of the fuzzy preference relation (FPR). In this paper, we generalize the least squares method to IFPR and IPR based on our proposed multiplicative consistent conditions. We also investigate the relationships between the optimal models of incomplete IFPRs, IPRs and FPRs. We also apply the same method to the case of collective judgment with complete information. We illustrate the feasibility and effectiveness of our proposed methods with three numerical examples.

Risk prediction of low temperature in Nanjing city based on grey weighted Markov model

In this research, we calculate the days whose temperature is less than or equal to −5xa0°C in a year according to the data of the daily minimum temperature in Nanjing city (China) from 1951 to 2011, divide these days into 6 categories according to the number (one, two, three, four, five, six and above) of consecutive low-temperature days, and introduce a annual low-temperature weighted index series. We divide the 61 annual low-temperature weighted indexes of 1951–2011 into five states using the mean standard deviation method. Based on the observation sequence of state of low-temperature in 1951–2009, we simulate the real low-temperature states of 2010 and 2011 by employing both weighted Markov method and grey weighted Markov method. The results of both methods show that the values of simulation (predicted) state agree with those of real state. Based on the state series of low temperature in 1951–2011, we predict the future state of low temperature of Nanjing city in 2012 by utilizing both weighted Markov method and grey weighted Markov method. It is found that the risk of low temperature belongs to the third state when we use weighted Markov method; however, the risk of low temperature belongs to the second state when we use the latter method. Although the states of the risk of low temperature are different because they are predicted by different methods, the two states illustrate that the risk of low temperature of Nanjing city in 2012 is in a normal situation.

The discrete grey prediction model based on optimized initial value

When GM (1, 1) model is applied to simulate a pure exponential sequence, the errors usually occur. There are many kinds of limitation to the development coefficient and the primary sequence. The characteristics of the discrete GM (1, 1) model are analogous to the GM (1, 1) model. It can be regarded as the precise form of the formal model. The paper studied the growth rate of the simulation values under different initial values of discrete GM (1, 1) model. Appling optimization technique to solve the initial value, it proved that the modified discrete GM(1,1) model can perfectly simulate the exponential sequence.

Energy consumption index of China's manufacturing based on grey change-point —from the perspective of policy

Over the last three decades, Chinas manufacturing industry has developed rapidly, the demand for energy is rising, thus energy consumption grows increasingly, giving rise to the energy crisis. This article has collected energy data from 28 manufacturing industries from 1985-2012 and normalizes this data based on maximum deviation. It also works out the weight of each indicator and their comprehensive evaluation values to build the model of energy consumption index. In addition, this paper takes the manufacturing consumption index as a data column to determine the change-points in the trend of energy consumption index by using the correlation analysis method and constructing the search algorithm of change-points of a short time series. We have come to the conclusion that there is a decline in the trend of manufacturing consumption index, and the change-points of energy consumption index are in 1994 and 2005. According to the results, the data of energy consumption index is divided into the following three cycles:1985-1994,1995-2004,2005-2012. This research will do further analysis on the change-points and energy consumption index from the angle of national energy policy, and provides references for the establishment of Chinas energy policy.

Meteorological and environmental effects on manufacturing in Jiangsu, China

This paper studies the border effects and sensitivity of the economic output of manufacturing in Jiangsu, China, caused by meteorological and environmental factors. The meteorological data, environmental data and annual manufacturing data of Jiangsu from 1993 to 2011 are used as input for this paper. Based on the Douglas production function and the grey correlation analysis method, this paper discusses the typical relationship among meteorological disaster factors, environmental regulations and the economic output of manufacturing in Jiangsu, China. The empirical analysis shows that the development of typical manufacturing in Jiangsu, China, is influenced by meteorological and environmental factors.