Analysis Design Software Development by Shivakumar Nagarajan (6 results)

Paperback. Condition: Brand New. 144 pages. 8.66x5.91x0.33 inches. In Stock.

Taschenbuch. Condition: Neu. Analysis and Design of Software Development Effort Estimation | Nagarajan Shivakumar (u. a.) | Taschenbuch | 144 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139887828 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book organized as follows: Chapter 1 describes the Software development process, need for effort estimation, and different approaches in algorithmic effort estimation techniques. chapter 2 presents literature survey of existing approaches available in the effort estimation, and provide a detailed report on the non-algorithmic combination of approaches to improve the estimation accuracy. Chapter 3 proposes a new effort estimation method based on fuzzy logic with function point size. The triangular fuzzy membership function is used with size parameter in function point. This model is compared with COCOMO model for its accuracy. Chapter 4 proposes Adaptive Neuro-fuzzy scheme proposed to integrate the concept of Artificial Neural network and fuzzy logic. Chapter 5 proposes particle swarm optimization and K means hybrid algorithm for clustering the data, and effort is estimated with neural network and analogy based estimation. Chapter 6 is a comparison of all the proposed models in four experiments. The metrics used are MRE, MAE, MBRE and MIBRE. The results show that both neuro-fuzzy and clustering algorithms are the best in estimating the software effort. 144 pp. Englisch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book organized as follows: Chapter 1 describes the Software development process, need for effort estimation, and different approaches in algorithmic effort estimation techniques. chapter 2 presents literature survey of existing approaches available in the effort estimation, and provide a detailed report on the non-algorithmic combination of approaches to improve the estimation accuracy. Chapter 3 proposes a new effort estimation method based on fuzzy logic with function point size. The triangular fuzzy membership function is used with size parameter in function point. This model is compared with COCOMO model for its accuracy. Chapter 4 proposes Adaptive Neuro-fuzzy scheme proposed to integrate the concept of Artificial Neural network and fuzzy logic. Chapter 5 proposes particle swarm optimization and K means hybrid algorithm for clustering the data, and effort is estimated with neural network and analogy based estimation. Chapter 6 is a comparison of all the proposed models in four experiments. The metrics used are MRE, MAE, MBRE and MIBRE. The results show that both neuro-fuzzy and clustering algorithms are the best in estimating the software effort.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Shivakumar NagarajanAn Assistant Professor at Thiagarajar College of Engineering and Ph. D in software Engineering, with research interest in Machine Learning, Deep Learning and Virtual Reality.The book organized as follows: Ch.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book organized as follows: Chapter 1 describes the Software development process, need for effort estimation, and different approaches in algorithmic effort estimation techniques. chapter 2 presents literature survey of existing approaches available in the effort estimation, and provide a detailed report on the non-algorithmic combination of approaches to improve the estimation accuracy. Chapter 3 proposes a new effort estimation method based on fuzzy logic with function point size. The triangular fuzzy membership function is used with size parameter in function point. This model is compared with COCOMO model for its accuracy. Chapter 4 proposes Adaptive Neuro-fuzzy scheme proposed to integrate the concept of Artificial Neural network and fuzzy logic. Chapter 5 proposes particle swarm optimization and K means hybrid algorithm for clustering the data, and effort is estimated with neural network and analogy based estimation. Chapter 6 is a comparison of all the proposed models in four experiments. The metrics used are MRE, MAE, MBRE and MIBRE. The results show that both neuro-fuzzy and clustering algorithms are the best in estimating the software effort.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 144 pp. Englisch.…