Open Science Research Excellence

Ryad Zemouri

Publications

1

Publications

1
9230
Recurrent Radial Basis Function Network for Failure Time Series Prediction
Abstract:
An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.
Keywords:
Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.