In this paper, new mutation strategies are proposed to improve the accuracy of the cost estimation by COCOMO's tuning parameters using the Internal adaption based mutation operator for differential evolution algorithm (IABMO Algorithm). The proposed method provides more promising solutions to take the lead evolution and helps DE abstain the circumstance of stability. The proposed algorithm applied software cost estimation and improve the performance of the initial phase for software engineering. This approach is used for precise prediction and reduces the error rate for the initial phase of software development phase projects. The software cost estimation based IABMO algorithm has been capable of a better for effort, MRE, MMRE, and prediction.
CITATION STYLE
Singh*, S. P., & Singh, Dr. D. K. (2020). Internal Adaption based Nature Inspired Algorithm for Application in Software Engineering. International Journal of Recent Technology and Engineering (IJRTE), 8(5), 4294–4301. https://doi.org/10.35940/ijrte.d9772.018520
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