Work place: Government college of Engineering, Tirunelveli, India
E-mail: praynlin25@gmail.com
Website:
Research Interests: Computer systems and computational processes, Neural Networks, Computer Architecture and Organization, Computer Networks, Data Structures and Algorithms
Biography
E.Praynlin: Research scholar in Department of Computer science and Engineering, Government college of Engineering, Tirunelveli. He has received his master’s degree in Applied Electronics from Noorul Islam University. He graduated from Anna university in Electronics and communication Engineering. His area of interest are software cost estimation and neural networks.
DOI: https://doi.org/10.5815/ijitcs.2013.09.11, Pub. Date: 8 Aug. 2013
Software Effort estimation involves the estimation of effort required to develop software. Cost overrun, schedule overrun occur in the software development due to the wrong estimate made during the initial stage of software development. Proper estimation is very essential for successful completion of software development. Lot of estimation techniques available to estimate the effort in which neural network based estimation technique play a prominent role. Back propagation Network is the most widely used architecture. ELMAN neural network a recurrent type network can be used on par with Back propagation Network. For a good predictor system the difference between estimated effort and actual effort should be as low as possible. Data from historic project of NASA is used for training and testing. The experimental Results confirm that Back propagation algorithm is efficient than Elman neural network.
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