Analyzing and Forecasting Energy Consumption in China’s Manufacturing Industry and Its Subindustries

Sun, Wei; Hou, Yufei; Guo, Lanjiang

doi:10.3390/su11010099

Cited by 9 publications

(8 citation statements)

References 62 publications

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“…Because the maximum deviation method can objectively determine the weight of the indicator, it is mainly used for multi-attribute decision-making (Sun et al 2019). The distribution of index weight can directly affect the rationality of the indicator setting, so the correct application of this method is of importance.…”

Section: Maximum Deviation Methodsmentioning

confidence: 99%

Big data revealed relationship between air pollution and manufacturing industry in China

2021

Self Cite

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Air pollution emissions can exceed the environmental self-purification capacity and trigger hazardous meteorological events, which have non negligible impacts on all aspects of society. The aim of this paper is to study the relationship between China's manufacturing industry benefits and air quality, taking into account the role of government policies in the era of big data, and to study the change points in the time series relationship between industry benefits and air quality. First, we apply and analyze big data and estimate values based on the maximum deviation method. Then, gray relational analysis is used to identify change points, which occur in 2005 and 2010 for both industry benefits and air quality. The total study period is divided into three subperiods:

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Section: Maximum Deviation Methodsmentioning

confidence: 99%

Big data revealed relationship between air pollution and manufacturing industry in China

2021

Self Cite

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“…A grey prediction model is an effective tool to deal with small sample prediction problems, and requires fewer basic data with high accuracy [57,58]. The common gray prediction model is GM (1,1), which has no specific requirements for sample size, and can be used to research future time distributions for specific time intervals.…”

Section: Gray Predicted Model (11)mentioning

confidence: 99%

Sustainable Development of New Urbanization from the Perspective of Coordination: A New Complex System of Urbanization‒Technology Innovation and the Atmospheric Environment

Jiang

Ding

Fang³

2019

Atmosphere

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Exploring the coordinated development of urbanization (U), technology innovation (T), and the atmospheric environment (A) is an important way to realize the sustainable development of new-type urbanization in China. Compared with existing research, we developed an integrated index system that accurately represents the overall effect of the three subsystems of UTA, and a new weight determination method, the structure entropy weight (SEW), was introduced. Then, we constructed a coordinated development index (CDI) of UTA to measure the level of sustainability of new-type urbanization. This study also analyzed trends observed in UTA for 11 cities in Zhejiang Province of China, using statistical panel data collected from 2006 to 2017. The results showed that: (1) urbanization efficiency, the benefits of technological innovation, and air quality weigh the most in the indicator systems, which indicates that they are key factors in the behavior of UTA. The subsystem scores of the 11 cities show regional differences to some extent. (2) Comparing the coordination level of UTA subsystems, we found that the order is: coordination degree of UT > coordination degree of UA > coordination degree of TA. This suggests that the atmospheric environment system improvement is an important strategic decision for sustainable urbanization in Zhejiang. (3) The UTACDI values of the 11 cities are not high enough, as the coordination is mainly low, basic, or good, while none of the cities reached the stage of excellent coordination. (4) Gray Model (1,1) revealed that the time taking to achieve excellent coordination varies for different cities. Hangzhou and Ningbo were predicted to reach the excellent coordination level in 2018. Other cities are predicted to take 2–4 years to adjust their urbanization strategies enough to be considered to have excellent coordination of their UTA system.

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“…Grey system predictive modeling is used to transform the actual value of a phenomenon in a certain time series into a differential equation, thus establishing a development model of the abstract system [46][47][48][49]. Under the circumstances, it is more reasonable to use the grey model to predict the economic polarization level of Jiangsu Province.…”

Section: Forecast and Warning Of Economic Polarizationmentioning

confidence: 99%

Temporal and Spatial Characteristics and Early Warning Analysis of Economic Polarization Evolution: A Case Study of Jiangsu Province in China

2019

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Economic polarization is a special manifestation of economic disparity which intensifies the gap between the rich and the poor in a region and brings about a series of social problems. Though more and more scholars are studying the phenomenon of economic polarization, there are few studies on polarization level division and early warning analysis in the existing literature. The main purpose of this paper is to propose a standard for rationally dividing the level of economic polarization. This paper firstly analyzes the current situation of economic polarization by using the economic data of 54 counties and cities in Jiangsu Province from 2000 to 2016 and secondly predicts the economic polarization level of Jiangsu Province from 2017 to 2015 through the grey model. We find that, according to the classification criteria of polarization levels, the phenomenon of economic polarization in Jiangsu Province is both not as serious as expected and at a moderate level of alertness. The results of this study can provide important reference value for the coordinated development of Jiangsu Province.

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Analyzing and Forecasting Energy Consumption in China’s Manufacturing Industry and Its Subindustries

Cited by 9 publications

References 62 publications

Big data revealed relationship between air pollution and manufacturing industry in China

Big data revealed relationship between air pollution and manufacturing industry in China

Sustainable Development of New Urbanization from the Perspective of Coordination: A New Complex System of Urbanization‒Technology Innovation and the Atmospheric Environment

Temporal and Spatial Characteristics and Early Warning Analysis of Economic Polarization Evolution: A Case Study of Jiangsu Province in China

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