Development of Genetic Algorithm based Neural Network model for parameter estimation of Fast Breeder Reactor Subsystem
Subhra Rani Patra1, R. Jehadeesan2, S. Rajeswari3, S. A.V. Satya Murty4, M. Sai Baba5
1Subhra Rani Patra, Computer Division, EIRSG, Indira Gandhi Center for Atomic Research, Kalpakkam-603102, Tamil Nadu, India.
2R. Jehadeesan, Scientific Officer, F, at IGCAR, DAE, Kalpakkam, India.
3S. Rajeswari is Head of CSS, Computer Division, EIG,IGCAR, DAE, Kalpakkam, India.
4S. A.V. Satya Murty,Computer Division, EIRSG, Indira Gandhi Center for Atomic Research, Kalpakkam-603102, Tamil Nadu, India.
5M. Sai Baba, Computer Division, EIRSG, Indira Gandhi Center for Atomic Research, Kalpakkam-603102, Tamil Nadu, India.
Manuscript received on September 01, 2012. | Revised Manuscript received on September 02, 2012. | Manuscript published on September 05, 2012. | PP: 87-90 | Volume-2 Issue-4, September 2012. | Retrieval Number: D0891072412/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work provides the construction of Genetic Algorithm based Neural Network for parameter estimation of Fast Breeder Test Reactor (FBTR) Subsystem. The parameter estimated here is temperature of Intermediate Heat Exchanger of Fast Breeder Test Reactor. Genetic Algorithm based Neural Network is a global search algorithm having less probability of being trapped in local minimum problem as compared to Standard Back Propagation algorithm which is a local search algorithm. The various development stages of Genetic Algorithm based Neural Network such as the preparation of the training set, weight extraction from the genetic population, training of the neural network and validation phase etc have been described in detail
Keywords: Genetic Algorithm based Neural Network, Fast Breeder Test Reactor, Intermediate Heat Exchanger, Multi layer Perceptron