Short –term Predication of Risk Management Integrating Artificial Neural Network (ANN)
Malaya Nayak1, Tariq Abdullah2

1Malaya Nayak*, University of Derby, Derby, United Kingdom.
2Tariq Abullah, University of Derby, Derby, United Kingdom.
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 2828-2833 | Volume-9 Issue-3, February 2020. | Retrieval Number:  C5974029320/2020©BEIESP | DOI: 10.35940/ijeat.C5974.029320
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Abstract: The IT industry has boomed in the past few years with an ever increasing number of risk management applications being developed. There are inherent risks in software development projects and failure to deliver software projects within deadline or failure to develop software according to specifications can be costly. The software risks may occur during the project process. The management process of software risks consists the risk refinement, risk identification, risk monitoring, risk maintenance, risk estimation and risk mitigation. Neural Network has ability to stimulate hidden pattern recognition skill. The primary study of this paper is to focus on various risk management models and how risk tools may help in mitigating software risks during the project development. With the application of Neural Network, We propose short term risk management model which can predict the risk involvement with the upcoming project risks, analyzing from the previous projects causing serious loss in the IT project in terms of values on certain risk factors. Neural Network model can also ability to evaluate the assessment of risks in software development and acts as an effective instrument in analysis and minimizing risks that enable continuous improvement in software processes and products.
Keywords: Cost risk, Schedule risk, Performance risk, User risk, Complexity Risk, Artificial Neural Network (ANN).