Determining the accuracy of budgets : a machine learning application for budget change pattern recognition

Yip, Kai Leung

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Date
2012
Citation:
Yip, K. L. (2012). Determining the accuracy of budgets : a machine learning application for budget change pattern recognition. (Unpublished document submitted in partial fulfilment of the requirements for the degree of Master of Computing). Unitec Institute of Technology. Retrieved from https://hdl.handle.net/10652/2036
Permanent link to Research Bank record:
https://hdl.handle.net/10652/2036
Abstract
With the aid of open-sourced database and software libraries, we developed a data mining software prototype for SME business intelligent budgeting planning. The experiment demonstrates the existence of the change pattern of financial variables for a certain SME industry group. A budget inaccuracy alarm system is developed. The system classifies a budget whether viable or inviable. As a result, SME businesses or non-profit organisations can make better decisions by improving forward looking financial analysis. This allows them to immediately develop contingency measures, revise the policy and get the business back on the right track. This has been a long-desired function needed by a business or a bank.
Keywords:
budget change pattern tecognition, budgeting, business planning, data mining, financial forecast, financial ratio, financial variable, government budget, intelligent budgeting, machine learning, small and medium-sized enterprises (SMEs), small businesses
ANZSRC Field of Research:
080109 Pattern Recognition and Data Mining
Degree:
Master of Computing, Unitec Institute of Technology
Supervisors:
Pang, Paul; Zhao, Xiaohui
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Author

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