A New Method for Software Defect Prediction Based on Optimized Machine Learning Techniques

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Published: Jul 24, 2023
Keywords:
Neuro-Computing LM-ANN Local Minima

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SHAHO HASSEN
Graduate School of Natural and Applied Sciences, Department of Computer Engineering, Atilim University, Ankara, Turkey
Prof. Dr. Ali YAZICI
Department of Computer Engineering, Atilim University
Prof. Dr. Alok MISHRA
Department of Computer Engineering, Atilim University, Ankara, Turkey

Abstract

This thesis aimed to develop a robust neuro-computing model for software defect prediction, utilizing the Levenberg Marquardt Neural Network (LM-ANN) with a novel improved genetic algorithm as a heuristic model. The goal was to achieve higher accuracy and overcome local minima and convergence issues

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How to Cite
SHAHO HASSEN, Prof. Dr. Ali YAZICI, & Prof. Dr. Alok MISHRA. (2023). A New Method for Software Defect Prediction Based on Optimized Machine Learning Techniques. Eurasian Journal of Engineering and Technology, 20, 53–76. Retrieved from https://geniusjournals.org/index.php/ejet/article/view/4707
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Vol. 20 (2023): EJET
Section
Articles
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