Software reliability reckoning by applying neural network algorithm-Reference-Cited by-同舟云学术

Software reliability reckoning by applying neural network algorithm

Published:2022-07-04 Issue:5 Volume:43 Page:1061-1071
ISSN:0252-2667
Container-title:Journal of Information and Optimization Sciences
language:en
Short-container-title:Journal of Information and Optimization Sciences

Author:

Pattnaik Saumendra¹,Laha Suprava Ranjan¹,Pattanayak Binod Kumar¹,Mohanty Ricky²,Alnabhan Mohammad³,Mohanty Mihir Narayan⁴

Affiliation:

1. Department of Computer Science and Engineering, Institute of Technical Education and Research (ITER), Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

2. School of Information System, Asian School of Business Management University, Bhubaneswar, Odisha, India

3. Department of Computer Science, Princess Sumaya University for Technology (PSUT), Amman, Jordan

4. Department of Electronics and Communication Engineering, Institute of Technical Education and Research (ITER), Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

Publisher

Taru Publications

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/02522667.2022.2094544

Reference24 articles.

1. Aljahdali, Sultan, and Narayan C. Debnath. “Improved Software Reliability Prediction through Fuzzy Logic Modeling.” (2004).

2. Banga, Manu, Abhay Bansal, and Archana Singh. “Implementation of Machine Learning Techniques in Software Reliability: A framework.” 2019 International Conference on Automation, Computational and Technology Management (ICACTM).IEEE, 2019.

3. Enhancing Reliability of Analog Neural Network Processors

4. An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications

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