Technical Evaluation of Grain Industry Based on Coefficient of Variation Weighting Method
Journal: Modern Economics & Management Forum DOI: 10.32629/memf.v5i2.1994
Abstract
Technological development is the driving force of progress. To comprehensively improve the technological development capacity of the grain industry and the conversion rate of agricultural scientific and technological achievements, it is necessary to build and improve a suitable technical system for the development of the grain industry. This paper uses the coefficient of variation weighting method to study the technological level of the grain industry, scientifically determining the weights of factors affecting competitiveness, and removing the influence of subjective factors on indicator weight assignment. Using the research methods in this paper to study the technology of the grain industry can help identify the shortcomings in the development of the grain industry and provide effective suggestions for promoting the healthy development of the grain industry.
Keywords
grain industry,grain industry technology, coefficient of variation weighting method, design production capacity
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[3] Utterback, B. Grain outlook.(forecast on exports in grain industry)
[4] Nitschke, T., & O’Keefe, Michael. (1997). Managing the linkage with primary producers: experiences in the australian grain industry. Supply Chain Management, 2(1), 4-6.
[5] Eldridge, S. M., Deborah, A., & Sally, K. (2006). Sample size for cluster randomized trials: effect of coefficient of variation of cluster size and analysis method. International Journal of Epidemiology(5), 1292.
[6] Aswin, I. C., Sankaran, P. G., & Sunoj, S. M. (2023). Reliability aspects of quantile-based residual coefficient of variation. International journal of reliability, quality and safety engineering(2), 30.
[7] Yeong, W. C., Tan, Y. Y., Lim, S. L., Khaw, K. W., & Khoo, M. B. C. (2022). A variable sample size run sum coefficient of variation chart. Quality and reliability engineering international.
[8] Mohammad, A., Chowdhury, Dewan, M., Nuruzzaman, & Hannan, M. A. (2014). Effect of Sliding Velocity and Relative Humidity on Friction Coefficient of Brass Sliding against Different Steel Counterfaces.
[9] TSAUR, ALLEN KEH-CHANG, C/O EASTMAN KODAK COMPANY, ROCHESTER, NEW YORK -, US, & KAM-NG, MAMIE, C/O EASTMAN KODAK COMPANY, ROCHESTER, NEW YORK, US. (1996). Method of producing an emulsion with table-shaped grains of a very low coefficient of variation., DE69206679D1.
[10] Xiongbing, Li, Yongfeng, Song, Feng, & Liu, et al. (2015). Evaluation of mean grain size using the multi-scale ultrasonic attenuation coefficient. Ndt & E International.
[11] Yuan, W., Liang, M., Jing, G., Fengfei, T., & Lianxi, S. (2013). The Study on the Indicator System for Strategic Environmental Assessment. International Conference on Environmental and Materials Engineering.
[12] Chuanqi, H. E., Liu, L., & Zhao, X. (2020). Study on indicator system of world modernization. Bulletin of Chinese Academy of Sciences, 35(11), 1373-1383.
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