Performance Enhancement of Data Classification using Selectively Cloned Genetic Algorithm for Neural Network

  title={Performance Enhancement of Data Classification using Selectively Cloned Genetic Algorithm for Neural Network},
  author={D. Kaur and Praneeth Nelapati},
  journal={Int. J. Comput. Intell. Syst.},
The paper demonstrates performance enhancement using selective cloning on evolutionary neural network over the conventional genetic algorithm and neural back propagation algorithm for data classification. Introduction of selective cloning improves the convergence rate of the genetic algorithm without compromising on the classification errors. The selective cloning is tested on five data sets. The Iris data problem is used as a bench-mark to compare the selective cloning technique with the… Expand


Data Pattern Recognition using Neural Network with Back-Propagation Training
Back propagation based on selective attention for fast convergence of training neural network
Classification techniques of neural networks using improved genetic algorithms
Schema theorem of real-coded nonlinear genetic algorithm
  • Zhihua Cui, J. Zeng
  • Computer Science
  • Proceedings. International Conference on Machine Learning and Cybernetics
  • 2002
A Novel Learning Algorithm of Back-Propagation Neural Network
  • B. Gong
  • Computer Science
  • 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009)
  • 2009
Backpropagation algorithm for logic oriented neural networks
  • T. Kamio, Shinichiro Tanaka, M. Morisue
  • Computer Science
  • Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium
  • 2000
Genetic algorithms: principles of natural selection applied to computation.
Improving the convergence of the back-propagation algorithm
Cellular Neural Networks-Based Genetic Algorithm for Optimizing the Behavior of an Unstructured Robot
Artificial Intelligence: A Guide to Intelligent Systems