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.
Highlights
The feasibility study of the risk management process comprises all the activities required to identify the risk that might have a potential impact on the IT project
The Performance Results for the Artificial Neural Network (ANN) for SE is : The R^2 score is 0.9158527748401523 The Mean Absolute Percent Error (MAPE) is 0.4680133846353399 % The Mean Absolute Error (MAE) is 0.004680133846353399 The Mean Squared Error (MSE) is 4.9158346309527624e-05 The Relative Root Mean Squared Error is 0.6841150375743394 %
ANN algorithm specially designed to run on technical variables in the purpose of predicting risk involved to undertake a project
Summary
The feasibility study of the risk management process comprises all the activities required to identify the risk that might have a potential impact on the IT project. To identify the risk involvement, various tools and techniques have been discovered, such as documentation review, information gathering, check list analysis, assumption analysis, diagramming techniques, and so on [9].The success of software and related product are of low margin in reality highlighting challenges during development of software products are one the primary reasons for the failure of the software products. The software development projects involve special attention especially when parameters continue changing at different stages of the development cycle. The main primarily parameters of project risks which affects the project process such as performance risk, schedule risk, and cost risk [9,11]. One more parameter user risk plays a vital role in the calculation of project risk [12]. Taking inspiration from [2,6,9,10,11] the new model is proposed and implemented to show that the proposed model gives 92% of Revised Manuscript Received on February 15, 2020. * Correspondence Author
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