Software reliability: measurement, prediction, application (professional ed.)
Software reliability: measurement, prediction, application (professional ed.)
Prediction of Software Reliability Using Connectionist Models
IEEE Transactions on Software Engineering
Journal of Systems and Software
Handbook of software reliability engineering
Handbook of software reliability engineering
Self-Organizing Methods in Modeling: Gmdh Type Algorithms
Self-Organizing Methods in Modeling: Gmdh Type Algorithms
On the neural network approach in software reliability modeling
Journal of Systems and Software
Optimal software release scheduling based on artificial neural networks
Annals of Software Engineering
Applying Reliability Models More Effectively
IEEE Software
Application of neural networks for software quality prediction using object-oriented metrics
Journal of Systems and Software
On-line prediction of software reliability using an evolutionary connectionist model
Journal of Systems and Software
Software reliability forecasting by support vector machines with simulated annealing algorithms
Journal of Systems and Software
Journal of Systems and Software
Software Reliability Prediction Using Wavelet Neural Networks
ICCIMA '07 Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007) - Volume 01
Software reliability prediction by soft computing techniques
Journal of Systems and Software
Noise elimination with partitioning filter for software quality estimation
International Journal of Computer Applications in Technology
IEEE Transactions on Neural Networks
Data mining via rules extracted from GMDH: an application to predict churn in bank credit cards
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Hybrid intelligent systems for predicting software reliability
Applied Soft Computing
Application of Machine Learning Techniques to Predict Software Reliability
International Journal of Applied Evolutionary Computation
Kernel group method of data handling: application to regression problems
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
International Journal of Intelligent Systems Technologies and Applications
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The main purpose of this paper is to propose the use of Group Method of Data Handling (GMDH) to predict software reliability. The GMDH algorithm presented in this paper is a heuristic self-organization method. It establishes the input-output relationship of a complex system using multilayered perception type structure that is similar to a feed forward multilayer neural network. The effectiveness of GMDH is demonstrated on a dataset taken from literature. Its performance is compared with that of multiple linear regression (MLR), back propagation trained neural networks (BPNN), threshold accepting trained neural network (TANN), general regression neural network (GRNN), pi-sigma network (PSN), dynamic evolving neuro-fuzzy inference system (DENFIS), TreeNet, multivariate adaptive regression splines (MARS) and wavelet neural network (WNN) in terms of normalized root mean square error (NRMSE). Based on experiments conducted, it is found that GMDH predicted reliability with least error compared to other techniques. Hence, GMDH can be used a sound alternative to the existing techniques for software reliability prediction.