Design process optimization and profit calculation module development simulation analysis of financial accounting information system based on particle swarm optimization (PSO)

  • Jianfei Shen
  • Lincong HanEmail author
Original Article


The rapid development of information technology and the tremendous changes of management ideas and management methods promote the continuous updating of management financial accounting system. The advantages of accounting information system are based on abundant data sources, timely business processing and fast transmission and reflection of all-round faithfulness. Based on the influence of information technology, this paper studies the related theories of process optimization and profit calculation module of financial accounting information system reconstruction by particle swarm optimization algorithm. The various data interfaces are gradually unified to better realize the sharing of information. The research shows that the particle swarm algorithm is used to compare the core functions of accounting information system (such as accounting, certificate filling, voucher review, voucher query, detailed ledger, general ledger, end-of-year carry-over, financial analysis, etc.). Calculation. Research shows that reorganizing accounting business processes can greatly improve the usefulness of accounting information decision-making, thereby enhancing the competitiveness of enterprises.


Particle swarm optimization algorithm Financial accounting information system Process optimization Profit calculation module development 



  1. Aghaei J, Muttaqi KM, Azizivahed A et al (2014) Distribution expansion planning considering reliability and security of energy using modified PSO (particle swarm optimization) algorithm. Energy 65(2):398–411CrossRefGoogle Scholar
  2. Bhimani A, Gulamhussen MA, Lopes SDR (2013) The role of financial, macroeconomic, and non-financial information in bank loan default timing prediction. Eur Account Rev 22(4):739–763CrossRefGoogle Scholar
  3. Bhimani A, Gulamhussen MA, Lopes SDR (2014) Owner liability and financial reporting information as predictors of firm default in bank loans. Rev Account Stud 19(2):769–804Google Scholar
  4. Brown R, Jones M (2015) Mapping and exploring the topography of contemporary financial accounting research. Br Account Rev 47(3):237–261CrossRefGoogle Scholar
  5. Crawley M, Wahlen J (2014) Analytics in empirical/archival financial accounting research. Bus Horiz 57(5):583–593CrossRefGoogle Scholar
  6. De Waegenaere A, Sansing R, Wielhouwer JL (2015) Financial accounting effects of tax aggressiveness: contracting and measurement. Contemp Account Res 32(1):223–242CrossRefGoogle Scholar
  7. Hu W, Yen GG (2015) Adaptive multiobjective particle swarm optimization based on parallel cell coordinate system. IEEE Trans Evol Comput 19(1):1–18CrossRefGoogle Scholar
  8. Hung J-C (2015) Robust Kalman filter based on a fuzzy GARCH model to forecast volatility using particle swarm optimization. Soft Comput 19(10):2861–2869CrossRefGoogle Scholar
  9. Järvenpää M, Teittinen H, Pellinen J (2013) ERP in action—challenges and benefits for management control in SME context. Int J Account Inf Syst 14(4):278–296CrossRefGoogle Scholar
  10. Kaspersen M, Johansen TR (2016) Changing social and environmental reporting systems. J Bus Ethics 135(4):731–749CrossRefGoogle Scholar
  11. Kiani M, Pourtakdoust SH (2015) State estimation of nonlinear dynamic systems using weighted variance-based adaptive particle swarm optimization. Appl Soft Comput 34:1–17CrossRefGoogle Scholar
  12. Lee YL, Elsaleh AA, Ismail M (2014) Gravity-based particle swarm optimization with hybrid cooperative swarm approach for global optimization. J Intell Fuzzy Syst 26(1):465–481Google Scholar
  13. Mahmoodabadi MJ, Salahshoor Mottaghi Z, Bagheri A (2014) HEPSO: high exploration particle swarm optimization. Inf Sci 273(18):101–111CrossRefGoogle Scholar
  14. Michel M, Menini A, Parbonetti A (2015) Fair value accounting: information or confusion for financial markets? Rev Account Stud 20(1):559–591CrossRefGoogle Scholar
  15. Niknam T, Narimani MR, Jabbari M (2013) Dynamic optimal power flow using hybrid particle swarm optimization and simulated annealing. Int Trans Electr Energy Syst 23(7):975–1001CrossRefGoogle Scholar
  16. Oh K, Choi W, Jeong SW et al (2014) The effect of different levels of internal control over financial reporting regulation on the quality of accounting information: evidence from Korea. Asia Pac J Account Econ 21(4):412–442CrossRefGoogle Scholar
  17. Rahimikia E, Mohammadi S, Rahmani T et al (2018) Detecting corporate tax evasion using a hybrid intelligent system: a case study of Iran. Int J Account Inf Syst 25:1–17CrossRefGoogle Scholar
  18. Stoppato A, Cavazzini G et al (2014) A PSO (particle swarm optimization)-based model for the optimal management of a small PV (Photovoltaic)-pump hydro energy storage in a rural dry area. Energy 76:168–174CrossRefGoogle Scholar
  19. Taipaleenmaki J, Ikaheimo S (2013) On the convergence of management accounting and financial accounting—the role of information technology in accounting change. Int J Account Inf Syst 14(4):321–348CrossRefGoogle Scholar
  20. Wang L, Geng H, Liu P et al (2015) Particle swarm optimization based dictionary learning for remote sensing big data. Knowl Based Syst 79:43–50CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Economics and ManagementNorth China Electric Power UniversityBeijingChina

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