Paper Title
An Analysis of BPA and ANN Applications used in Enhancement of Software Reliability
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An Analysis of BPA and ANN Applications used in Enhancement of Software Reliability
Abstract
Neural networks are a computational metaphor inspired studies of the brain and nervous system in biological organisms. They are highly idealized mathematical models of how understand the essence of these simple nervous systems. Reliability in the general engineering sense, is the probability. It gives component or system in a define environment will operate correctly for a specified period of time. An important issue in developing such software systems is to produce high quality software system that satisfies user requirements. Software reliability models specify some reasonable form for this distribution, and are fitted to data from a software project. Once a model demonstrates a good fit to the available data, it can be used to determine the current reliability of the software, and predict the reliability of the software at future times.The description and demonstration of the several types of neural networks are given, applications of neural networks like ANNs in medicine are described, and the detailed historical backgrounds are provided. The relationship between the artificial and the actual thing is also thoroughly investigated and explained. Finally, the involved mathematical models are shown and explained.
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How To Cite (APA)
Ms. Mahima & Dr, Mukesh Singla (October-2022). An Analysis of BPA and ANN Applications used in Enhancement of Software Reliability. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(10), 373-381. https://ijnrd.org/papers/IJNRD2210174.pdf
Issue
Volume 7 Issue 10, October-2022
Pages : 373-381
Other Publication Details
Paper Reg. ID: IJNRD_183701
Published Paper Id: IJNRD2210174
Downloads: 000122254
Research Area: Engineering
Author Type: Indian Author
Country: -, -, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2210174.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2210174
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