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Agile Cost Overhead Prioritization With ML For Effective Software Project Management
Abstract
Now a days, almost all industries who are working on software have a set process to use Agile as a software development method. Such software companies are practicing various kinds of agile versions (like-Scrum, XP, Kanban, etc.) When progressing on achieving organizational goals with Agile, there are quite significant challenges like planning difficulties, prioritizing the work, estimating costs, overhead costs, etc. These challenges are faced by management people - Budgeting, costing analysis and estimating things during different phases of the project execution are critical factors of project management. Hence, focusing on such factors which are helpful for the optimization of costs gains more importance. Alternatively, FAHP which is operated on the principle of ‘Fuzzy Set' theory. An AHP process happens to be a competent way to solve some complex decision-making problems. ML can become a crucial component of this entire ecosystem, if it's equipped with Fuzzy. The hybrid model combining fuzzy and ML can support in predicting the cost and prioritization effectively.
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