Optimizing Effort and Cost Estimation: Model Implementation Using Artificial Neural Networks and Taguchi’s Orthogonal Vector Plans
摘要
Part 2 of this book consists of one large chapter focused on optimizing effort and cost estimation through Artificial Neural Networks (ANN) and Taguchi’s Orthogonal Vector Plans, which has been the main area of our exploration and research over the last decade. The chapter presents a novel methodology that enhances conventional models like COCOMO2000, COSMIC FFP, and UCP, improving their accuracy and efficiency. Through detailed analysis and comparisons, it demonstrates how AI-driven techniques and advanced optimization methods lead to more precise and scalable software project estimation.