Research on evaluation model based on D & A system
DOI:
https://doi.org/10.54097/hbem.v2i.2406Keywords:
Hierarchical analysis, genetic algorithm (GA), gray prediction model (GM(1,1)), evaluation modelAbstract
The evaluation system established by our team for the D&A system hopes to help ICM companies fully utilize the data of their own output to understand their strengths and weaknesses, and help ICM supply words to obtain higher benefits. We introduced the hierarchical analysis method (AHP) to calculate the weights of the nine tertiary indicators, among which the human capacity, technical solutions and data management had the largest weights, 0.5584, 0.5936 and 0.625. Next, we used the entropy weighting method (EWM) to calculate the weights of the secondary and tertiary indicators respectively. Subsequently, we used the genetic algorithm (GA) and combined with the conclusions drawn earlier to make the selection of the optimal solution, and the optimization was calculated to obtain the maximum value of 0.432.
Downloads
References
An Jingwen,Li Yuanchun,Liu Haidong,Zhen Haihong,Liang Ruiwen. Research on the evaluation index system of enterprise technology innovation capability maturity [Research on the evaluation index system of enterprise technology innovation capability maturity.doc-originality-document (book118.com)]. 2017.
Cao Siming, Wu Yi, Cao Kai, Chen Meng. Evaluation of comprehensive energy system operation service based on entropy weight and AHP[J]. Science and Technology Bulletin, 2021,37(12):56-60.
Chen Guanlin. The GDP forecast analysis of the three northeastern provinces based on the grey model [J]. China Business Review, 2022, (03): 10-13.
HollandJHGenetic algorithms. Scientific American,1992:44-50.
Liu Danyu. Exploring the construction of a training management system for front-line staff in ports [J]. Hebei Enterprise, 2019, (02): 125-126.
Qinghai Development Strategy Department. Research and application of process maturity assessment model of Qinghai Mobile [Process maturity assessment index system - China Mobile.docx (book118.com)], 2019.
Sun Baohua, Li Yunpeng, Yu Yuanqi, Tong Donghui, Cao Zhi. Maturity assessment of power information system based on big data and analytic hierarchy process [J]. Science and Technology Wind, 2019,(13):78.
Tao Hongfei, Sun Yixin, Wu Guowei, Li Kangyi. Maturity assessment of power information system based on big data and analytic hierarchy process [J]. China Electric Power, 2016,49(10):114-118.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
