Evidence Based Decision Making using Neural Networks for Software App - Study and Developed EBDM for Predicting Software Reliability

Evidence Based Decision Making using Neural Networks for Software Applications The Bayesian Networks use Conditional Probability Tables for predicting the Cause and Effect Relationship. Bayesian Networks can be replaced by Neural networks which improves the effectiveness of expert knowledge by analysing the data sets. Neural Networks are created by connecting processing elements. Neural Networks replaces the Bayesian Networks because of its ability to solve a problem in software without defining and describing the method of solving such problems and even without any case of personal knowledge about the solved problems. This study focuses on predicting the reliability of any software project depending upon their project characteristics using Neural Networks.

Info autore

Dr.K.Karnavel received his M.Tech(CSE)and Ph.D from Anna University. Currently he is working at Anand Institute of Higher Technology, Chennai. He has published several papers in National and InternationalJournals/Conferences. He research area includes Software Testing, Software Quality, Computer Networks, Data Structures and Theory of Computation.

Dettagli sul prodotto

• Autori: Karnave Kuppusamy, Karnavel Kuppusamy, Anna Suganthi Suvisesharaj
• Editore: LAP Lambert Academic Publishing
• Lingue: Inglese, Tedesco
• Formato: Tascabile
• Pubblicazione: 01.01.2016
• EAN: 9783659819032
• ISBN: 978-3-659-81903-2
• Pagine: 84
• Dimensioni: 150 mm x 220 mm x 5 mm
• Peso: 144 g
• Categoria: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Software applicativo