THERMAL SCIENCE

International Scientific Journal

Authors of this Paper

External Links

THE INPUT AND OUTPUT RELATIONSHIP OF WATER RESOURCE IN JILIN FROM 2004 TO 2017

ABSTRACT
Jilin is an important grain producing area and heavy industry base in China. With the economic development and improvement of people's livelihood, water resource issues have been becoming increasingly prominent, Jilin Province comprehensive utilization of water resources is not efficient. The traditional method of water consumption per 10000 Yuan of output value cannot objectively reflect the water-use efficiency of different local industrial structures. Therefore, this paper builds the data envelopment analysis model based on the input-output relationship. In order to meet the requirements of data envelopment analysis model for data analysis, this paper introduces the principal component analysis method, and reduces the 16 water resources input indicators and 14 water resources output indicators of Jilin Province from 2004 to 2017 to 3 input principal components and 2 output principal components. The multi-model data envelopment analysis method is used to analyze the water-use efficiency of Jilin Province, and the results show that with the rapid economic growth, the water resources efficiency in 2010-2013 was relatively poor, there was a waste of water resources, and the management technology was backward, but with the deepening of the industrial transformation and upgrading, farming modernization and revitalizing the strategy of the old industrial base in Northeast China, the water-use efficiency and the water resources carrying capacity of Jilin Province has been improved.
KEYWORDS
PAPER SUBMITTED: 2019-04-28
PAPER REVISED: 2019-06-19
PAPER ACCEPTED: 2019-08-08
PUBLISHED ONLINE: 2020-06-21
DOI REFERENCE: https://doi.org/10.2298/TSCI2004337S
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2020, VOLUME 24, ISSUE 4, PAGES [2337 - 2345]
REFERENCES
  1. Wang, X. F., Study of Water Resources Efficiency by Considering the Regional Water Carrying Capaci-ty (in Chinese), Urban and Environmental Studies, 1 (2018), 2, pp. 97-110
  2. Yang, G. L., et al., Review of Data Envelopment Analysis (in Chinese), Journal of Systems Engineering, 28 (2013), 4, pp. 840-860
  3. Charnes, A., et al., Measuring the Efficiency of Decision Making Units, European Journal of Operation-al Research, 2 (1978), 6, pp. 429-444
  4. Yang, X. H., et al., Chaos Gray-Coded Genetic Algorithm and Its Application for Pollution Source Iden-tifications in Convection-Diffusion Equation, Communications in Nonlinear Science and Numerical Simulation, 13 (2008), 8, pp. 1676-1688
  5. Li, Z. M., Liao, H. C., Input and Output Analysis of Water Resources Across China in 2010 (in Chi-nese), Resources Science, 34 (2012), 12, pp. 2274-2281
  6. Yang, X. H., et al., Improved Gray-Encoded Evolution Algorithm Based on Chaos Cluster for Parameter Optimization of Moisture Movement, Thermal Science, 21 (2017), 4, pp. 1581-1585
  7. Sun, F. H., et al., Evaluation of Utilization Efficiency of Regional Agricultural Water Resources Based on Three-Stage DEA-Malmquist Model (in Chinese), Journal of Economics of Water Resources, 37 (2019), 2, pp. 53-58
  8. Cao, F, L., Analysis of Industrial Water Resources Utilization Efficiency Based on DEA Method (in Chinese), Energy Conservation & Environmental Protection, 7 (2018), 10, pp. 64-67
  9. Banker, R. D., et al., Some Models for Estimating Technical and Scale Inefficiencies in Data Envelop-ment Analysis, Management science, 30 (1984), 9, pp. 1078-1092
  10. Xu, J. H., Prediction of Urban Water Demand Based on Improved Principal Component Analysis Meth-od (in Chinese), Water Resources Development and Management, 1 (2019), 3, pp. 23-25
  11. Wu, Y., He, J.-H. A Remark on Samuelson's Variational Principle in Economics, Applied Mathematics Letters, 84 (2018), Oct., pp. 143-147
  12. He, J. H. A Modified Li-He's Variational Principle for Plasma, International Journal of Numerical Methods for Heat and Fluid Flow, On-line first, doi.org/10.1108/HFF-06-2019-0523, 2019
  13. He, J. H. Variational Principle for the Generalized KdV-Burgers Equation with Fractal Derivatives for Shallow Water Waves, J. Appl. Comput. Mech., 6 (2020), 4, pp. 735-740
  14. He, J. H., Sun, C., A Variational Principle for a Thin Film Equation, Journal of Mathematical Chemis-try, 57 (2019), 9, pp. 2075-2081
  15. Jolliffe, I. T., Principal Component Analysis, 2nd ed., New York: Springer-Verlag New York Inc., USA, 2002

© 2020 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence