Software Effort Estimation using Neuro Fuzzy Inference System: Past and Present
This addresses the challenge of poor effort estimation in software development projects, which is critical for resource allocation and project success, but the approach appears incremental as it builds on existing hybrid methods.
The paper tackles the problem of inaccurate software effort estimation, which often leads to project delays or failures, by analyzing the Neuro Fuzzy Inference System (NFIS) as a new approach that combines artificial neural networks and fuzzy logic to provide better estimates.
Most important reason for project failure is poor effort estimation. Software development effort estimation is needed for assigning appropriate team members for development, allocating resources for software development, binding etc. Inaccurate software estimation may lead to delay in project, over-budget or cancellation of the project. But the effort estimation models are not very efficient. In this paper, we are analyzing the new approach for estimation i.e. Neuro Fuzzy Inference System (NFIS). It is a mixture model that consolidates the components of artificial neural network with fuzzy logic for giving a better estimation.