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Automatic Pattern Forecasting from Banking Financial Data

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Md Jayedul Haque, Khairul Mottakin, Nazmun Nahar

Md Jayedul Haque, Khairul Mottakin and Nazmun Nahar. Automatic Pattern Forecasting from Banking Financial Data. International Journal of Computer Applications 182(8):13-19, August 2018. BibTeX

	author = {Md Jayedul Haque and Khairul Mottakin and Nazmun Nahar},
	title = {Automatic Pattern Forecasting from Banking Financial Data},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2018},
	volume = {182},
	number = {8},
	month = {Aug},
	year = {2018},
	issn = {0975-8887},
	pages = {13-19},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2018917632},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


A very famous adage of Adam Smith, “All money is a matter of belief”. It is, of course, the beginning of the first use of money was observed when the supply of demanded product was available in the hands of others. It can also be said that the introduction of money has introduced us to a system called business. Initially, this system gave rise to the internal economy but later it spread to the whole world. But in the whole world there is a new system emerged for the flow of economy which is known as bank to everyone. And through this bank, a country may be importing or exporting every day. Only the economy of a country is considered good when export is more than import. Due to everyone's attention of better economy, export can be increased and import can be optimized. So, to solve this problem statistics can help us greatly. As Statistics, has been using in determining the existing position of per capita income, unemployment, population growth rate, housing, schooling medical facilities and so on.

In this study not only statistics but also machine learning tools were used to analyze and forecast the financial banking data specifically import data. Basically, import data is known to a country as an economic data. So when it can predict about imports, then deciding how much of the export will be good for economics can easily be determined. In this paper it has been worked with import data of Bangladesh Bank for analysis and forecast the import of Bangladesh, based on collected data to strengthen the economic condition.


  1. Boone and Kurtz, “Contemporary Business,” 16th edition.
  2. A. Ganesh-Kumar, Sanjay K. Prasad and Hemant Pullabhotla, “Supply and Demand for Cereals in Bangladesh, 2010–2030,” June 2012.
  3. M.A.A. Hasin, S. Ghosh, M.A. Shareef, “An ANN Approach to Demand Forecasting in Retail Trade in Bangladesh”, International Journal of Trade, Economics and Finance, vol. 2, no. 2, April 2011.
  4. G. Atsalakis, C.I. Ucenic, C. H. Skiadas, “Forecasting Unemployment Rate Using a Neural Network with Fuzzy Inference System,” ICAP, 2007.
  5. L.M. Liu, S. Bhattacharyya, S.L. Sclove, R. Chen, W. J. Lattyak, “Data Mining on Time Series: An Illustration Using Fast-Food Restaurant Franchise Data”, Computational Statistics & Data Analysis, vol. 37, pp. 455-476, 2001.
  6. P.C. Chang, Y.W. Wang, C.H. Liu, “The Development of a Weighted Evolving Fuzzy Neural Network for PCB Sales Forecasting”, Expert Systems with Applications, vol.32, pp. 86- 96, 2007.
  7. Z.L. Sun, T.M. Choi, K.F. AU, Y. Yu, “Sales Forecasting Using Extreme Learning Machine With Applications In Fashion Retailing”, Decision Support Systems, vol. 46, pp. 411-419, December 2008.
  8. Y. Yu, T. Choi, C. Hui, “An Intelligent Fast Sales Forecasting Model for Fashion Products”, Expert System with Applications, vol. 38, pp. 7373-7379, 2011.
  9. S.H. Ling, “Genetic Algorithm and Variable Neural Networks: Theory and Application”, Lambert Academic Publishing, 2010.
  10. K.F. Au, T.M. Choi, Y. Yu, “Fashion Retail Forecasting by Evolutionary Neural Networks”, International Journal of Production Economics, vol. 114, pp.615-630, 2008.
  11. R.S. Gutierrez, A. Solis, S. Mukhopadhyay, “Lumpy Demand Forecasting Using Neural Networks”, International Journal of Production Economics, vol. 111, pp. 409-420, 2008.
  12. P. Doganis, A. Alexandridis, P. Patrinos, H. Sarimveis, “Time Series Sales Forecasting For Short Shelf-Life Food Products Based On Artificial Neural Networks And Evolutionary Computing”, Journal Of Food Engineering, vol. 75, pp. 196-204, 2006.
  13. L. Aburto, R. Weber, “Improved supply chain management based on hybrid demand forecasts”, Applied Soft Computing, 2007.
  14. Nahida Sultana Ebney Ayaj Rana, and Rashed Al Mahmud Titumir “Export, Import, Remittance and FDI: Recent Trends,” Bangladesh Economic Update vol. 5, No. 4, April 2014.
  15. Valentino Piana (2001). IMPORTS. [Online]. Available:
  16. Henrique Steinherz Hippert, Carlos Eduardo Pedreira, and Reinaldo Castro Souza, Neural Networks for Short-Term Load Forecasting: A Review and Evaluation, IEEE Transactions on Power Systems, Vol. 16, February 2001.
  17. Michael Todaro and Stephen C. Smith, "Economic Development" (11th ed.)., Pearson Education and Addison-Wesley (2011).
  18. Sen, A (1983). "Development: Which Way Now?". Economic Journal. 93 (372): 745–62. doi:10.2307/2232744.
  19. Hirschman, A. O. (1981). The Rise and Decline of Development Economics. Essays in Trespassing: Economics to Politics to Beyond. pp. 1–24.
  20. Hoggson, N. F. (1926) Banking Through the Ages, New York, Dodd, Mead & Company.
  21. Goldthwaite, R. A. Banks, Places and Entrepreneurs in Renaissance Florence, (1995)
  22. Boland, Vincent (2009-06-12). "Modern dilemma for world's oldest bank". Financial Times. Retrieved 23 February 2010.
  23. Peeples, Matthew A. “R Script for K-Means Cluster Analysis”, 2011. Electronic document,, [accessed January 27, 2018.]


Financial Informatics, Economics, Statistics, Imports and Exports, Machine Learning.