Software estimation artificial neural networks - Zahid Hussain Wani - Bog

Software Estimation Artificial Neural Networks (SEANN) is a cutting-edge approach to estimating software development effort using artificial neural networks (ANNs). It leverages the power of machine learning and neural networks to predict the time, resources, and effort required to complete software development projects. SEANN is designed to address the challenges and complexities associated with software estimation, which traditionally relies on subjective judgment and expert opinion. By utilizing ANNs, SEANN can learn from historical data and identify patterns, relationships, and dependencies that impact software development effort. This enables more accurate and reliable estimations compared to traditional methods. The core of SEANN lies in its neural network architecture, which is inspired by the structure and functioning of the human brain. The network consists of interconnected nodes, or artificial neurons, organized into multiple layers. Each neuron receives input signals, performs computations, and produces an output signal that is passed on to the next layer. Through a process of training, the network adjusts the connections between neurons to optimize its performance and improve estimation accuracy.