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Rapid Control of Government Economic Environment Management Cost Based on Balanced Score Card.

EMC (economic management cost) of the government has become a hot topic of concern from all walks of life. Controlling and reducing government EMC is the requirement for building a conservation-oriented society and deepening the reform of public budget. Dynamic cost accounting calculates the cost of...

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Published in:Journal of Environmental & Public Health pp. 1 - 11
Main Authors: Wang, Yumei, Shen, Zhirong, Zhou, Yicheng
Format: research Journal Article
Published: Wiley-Blackwell 8/2/2022
Online Access:View this record in EBSCOhost
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    shortDbName: ccm
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        16879805
        9034
      jtl: Journal of Environmental & Public Health
      issn: 16879805
      maglogo: N
    pubinfo:
      dt: 8/2/2022
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        158307454
        158307454
        NLM35958389
        158307454
        10.1155/2022/8506676
        NLM35958389
        158307454
      ppf: 1
      ppct: 10
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      tig:
        atl: Rapid Control of Government Economic Environment Management Cost Based on Balanced Score Card.
      aug:
        au:
          Wang, Yumei
          Shen, Zhirong
          Zhou, Yicheng
        affil: Business School, Suzhou University of Science and Technology, Suzhou 215009, China
      sug:
        subj:
          Algorithms
          Conservation of Natural Resources
          Government
          Models, Theoretical
      ab: EMC (economic management cost) of the government has become a hot topic of concern from all walks of life. Controlling and reducing government EMC is the requirement for building a conservation-oriented society and deepening the reform of public budget. Dynamic cost accounting calculates the cost of cost objects through the confirmation, measurement, and distribution of production costs. In this article, it is innovatively proposed to integrate BSC (balanced score card) into EMC control, and analyze the logical relationship between system objectives and functions by using the mathematical model. Based on GA (genetic algorithm) cost optimization control concept and specific control ideas, individuals who meet the evolutionary characteristics are stored in the crossover database and participate in crossover operation as parents when crossing. In order to improve the local optimization ability of the algorithm, parallel mutation operation mechanism is introduced, which can execute multiple mutation rules at the same time. The results show that the average convergence time of this algorithm is 0.186s and the variance of population fitness is 288.19. The conclusion shows that the algorithm proposed in this article can overcome the problems of slow convergence speed, low accuracy, and local convergence of GA, and effectively improve the overall performance of the algorithm.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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