Recurrent neural network for software failure prediction-Reference-Cited by-同舟云学术

Recurrent neural network for software failure prediction

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fourth International Conference on Engineering & MIS 2018 - ICEMIS '18
language:
Short-container-title:

Author:

Benaddy Mohamed¹,El Habil Brahim¹,El Meslouhi Othmane¹,Krit Salah-Ddine¹

Affiliation:

1. Department of Mathematics Computer Sciences and Management, Laboratory of Engineering Sciences and Energy, Ibn Zohr University, Ouarzazate, Morocco

Publisher

ACM Press

Reference40 articles.

1. S. Fernandez Bertolami H. Bunke A. Graves, M. Liwicki and J. Schmidhuber. May 2008. A Novel Connectionist System for Unconstrained Handwriting Recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 31, no. 5, pp. 855868 (May 2008).

2. Fatima El Jamiy James Higgins Brandon Wild Abd El Rahman El Said, Travis Desell. 2017. Optimizing Long Short-Term Memory Recurrent Neural Networks Using Ant Colony Optimization to Predict Turbine Engine Vibration. CoRR, vol. Abs/1710.03753. (2017).

3. Jimmy Lei Ba Diederik P. Kingma. 2015. Adam: A method for stochastic optimization. ArXiv preprint arXiv:1412.6980. Published as a conference paper at ICLR (2015).

4. Hazan E. Duchi, J. and Y. Singer. 2011. Adaptive subgradient methods for online learning and stochastic optimization. Journal of Machine Learning Research. (2011).

5. S. H. Ling F. H. F. Leung, H. K. Lam and P. K. S. Tam. 2003. Tuning of the structure and parameters of a neural network using an improved genetic algorithm. IEEE Transactions on Neural Networks vol. 14, no. 1, pp. 7988. (2003).

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A systematic mapping study on the employment of neural networks on software engineering projects: Where to go next?;Journal of Software: Evolution and Process;2021-11-02