Document Type : Research Paper

Authors

1 PhD Student in Information Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

2 Assistant Professor, Department of Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

3 Professor, Department of Management and Accounting, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran

Abstract

Making more profit in organizations requires accurate tools to strengthen the business for proper financial planning. Therefore, the purpose of this study was to demonstrate knowledge of the neural network to provide a framework for achieving the desired profit in the organization's financial planning. This research was of the applied type and was performed by the analytical survey method. The study population was the organizations present in the Exchange and Securities Organization, and the data extracted from the official system of the Exchange and Securities Organization of Iran (Cadal) were used. This research was conducted using the neural network method in a MATLAB program environment. Findings The range of changes of factors affecting the main index in the organization's financial planning (profit) and the most important factors affecting it were determined. The proposed framework was reviewed in three different sets of three various industries and had acceptable results. Therefore, the study results indicated that the proposed framework in this study could be used for other organizations present in the stock exchange and securities.

Keywords

  1. Akhmedov, Kh., )2016(, “Financial planning and business performance: Evidence from private sector of Uzbekistan”, European journal of business and management, ISSN 222-1905, Vol.18, No.9.

    Elman, J. L. (1990). Finding structure in time. Cognitive science, 14(2), 179-211.

    Kastiya, D., (2013), “Write up on strategic financial planning”, strategic financial management reg. No. 1111472 total word count- 1131, pp.8.

    Oral, C., Akkaya, G. C., (2015), “Cash flow at risk: A tool for financial planning”, 2nd global conference on business economics management and tourism, October 2014, prague, Czesh Republic.

    Ranganayaki, V., Deepa, S. N., (2016), “An Intelligent Ensemble Neural Network Model for Wind SpeedPrediction in Renewable Energy Systems”, the Scientific World JournalVolume 2016, Article ID 9293529, pageshttp:// dx.doi.org /10. 11 55/2016/9293529

    Wu, J.MT., Sun, L., Srivastava, G., Lin, J.CW. (2021). A ML-Based Stock Trading Model for Profit Predication. In: Fujita, H., Selamat, A., Lin, J.CW., Ali, M. (eds) Advances and Trends in Artificial Intelligence. From Theory to Practice. IEA/AIE 2021. Lecture Notes in Computer Science(), vol 12799. Springer, Cham. https://doi.org/10.1007/978-3-030-79463-7_47

    1. Qianyu, L. Dongping, Z. Xueying, C. Huaisen and Z. Xiaozhou, )2021("Enterprise Profit Forecast Model Based on Long Short-Term Memory Neural Network,«International Conference on Big Data Analysis and Computer Science (BDACS), 2021, pp. 62-65, doi: 10.1109/BDACS53596.2021.00021.

    Zarrin, S. & Daim, T. (2019). Strategic Technology Planning in Product-Service Systems with Embedded Customer Experience Requirements. Portland International Conference on Management of Engineering and Technology (PICMET), ISSN: 2159-5100.

    Audit Organization (2014). Principles and rules of accounting and auditing: accounting standards. Tehran: Publisher of Audit Organization. [in Persian]

    Bariklou, Alireza, (2016), "The status of profit guarantee condition", Law Quarterly, Faculty of Law and Political Sciences, Volume 38, Number 4. [in Persian]

    Hamidian, Mohsen, Mohammadzadeh Moghadam, Mohammad Baqer, Naqdi, Sajjad, Ismaili, Javad, (2017), "Prediction of profit sharing policy using univariate and multivariate neural network models", Investment Knowledge Quarterly, Volume 7, No. 26. [in Persian]

    Mashayekhi, Bita, Beirami, Haniyeh, Beirami, Hani, Akhlaghi, Sara Sadat, (2016), "Discovery of Profit Management Using Neural Networks" Journal of Financial Engineering and Securities Management, No. 11. [in Persian]

    Qaderi, Iqbal, Amini, Peyman, Mohammadi Malqarni, Attaullah and Noroosh, Iraj, (2017), "Investigating the accuracy of artificial neural networks and ant colony optimization algorithm in profit management forecasting", Financial Accounting Quarterly, Year 10, Number 39. [in Persian]

    Salehi, Mehdi and Farokhi Pilehvar, Laleh, (2017), "Prediction of profit management using neural network and decision tree", Financial Accounting and Auditing Research Quarterly, Year 10, Number 37. [in Persian]