Artificial Neural Network Model For Risk Impacts On Cash Flow Forecast

871 Words 4 Pages
An Artificial neural network model for risk impacts on cash flow forecast in construction industry
Key Words: Risk Factors, Risk Impacts, Model, Artificial Neural Network, Cash Flow Forecast
Area of Research
Cash flow forecasting is a vital contributing factor in construction industry where lead to the high rate of insolvencies. Risks involved with construction industry play significant role for the variation of forecasted and actual cash flow. Identification of risks and risk assessment are important to develop accurate cash flow forecast. Statistical, mathematical and simulation approaches were adapted to the identification of risk impact assessment. Though significant variation is still observed with actual and forecasted cash flow. So my Phd is focused in developing an artificial neural network model to assess the impact to cash flow forecast at the in progress stage of construction.
Research Topic
Prior studies were done to develop models to shortcut approach to cash flow forecasting based on project financial data and construction duration referred to as cost profile method (Kenley,2003). Three approaches were used in developing cost profile method; net cash flow, contract value data (value flow) and construction cost data (cost flow or cost commitment) by utilizing the three sides of the cash flow equation. Though significant deviation observed with actual and modeled forecast due to lack of addressing the risks impact inherent with construction industry. So in this…

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