# Neural Networks using Genetic Algorithms

@article{Mahajan2013NeuralNU, title={Neural Networks using Genetic Algorithms}, author={Richa Mahajan and Gaganpreet Kaur}, journal={International Journal of Computer Applications}, year={2013}, volume={77}, pages={6-11} }

Combining neural network with evolutionary algorithms leads to evolutionary artificial neural network. Evolutionary algorithms like GA to train neural nets choose their structure or design related aspects like the functions of their neurons. Along basic concepts of neural networks and genetic algorithm this paper includes a flexible method for solving travelling salesman problem using genetic algorithm. This offers a solution which includes a genetic algorithm implementation in order to give a…

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## References

SHOWING 1-10 OF 19 REFERENCES

Genetic Algorithms and Neural Networks

- Computer Science
- 1995

The integration of genetic algorithms with neural networks is a rapidly expanding area building on the explosion of interest in the two technologies individually. In the early 1990’s, the revolution…

Training Feedforward Neural Networks Using Genetic Algorithms

- Computer ScienceIJCAI
- 1989

A set of experiments performed on data from a sonar image classification problem are described to illustrate the improvements gained by using a genetic algorithm rather than backpropagation and chronicle the evolution of the performance of the genetic algorithm as it added more and more domain-specific knowledge into it.

Genetic Algorithms in Engineering and Computer Science

- Computer Science
- 1996

This book alerts the existence of evolution based software - Genetic Algorithms and Evolution Strategies - used for the study of complex systems and difficult optimization problems unresolved until now and provides a bridge between artificial intelligence and scientific computing in order to increase the performance of evolution programs for solving real-life problems.

Genetic Algorithms and Neural Networks

- Computer ScienceNeural Networks in the Analysis and Design of Structures
- 1999

The chapter considers the ‘permutations’ problem and introduces the concept of ‘shift’, which is used to train a neural network as an alternative to back-propagation, and considers the implicit parallelism of the GA.

Methods of Combining Neural Networks and Genetic Algorithms

- Computer Science
- 1997

In the past decade, two areas of research which have become very popular are the fields of neural networks and genetic algorithms and a summary will be given of these combination methods.

A Genetic Algorithm for Solving Travelling Salesman Problem

- Computer Science
- 2011

Genetic Algorithm which is a very good local search algorithm is employed to solve the TSP by generating a preset number of random tours and then improving the population until a stop condition is satisfied and the best chromosome which are a tour is returned as the solution.

Travelling Salesman Problem using Genetic Algorithm

- Computer Science, Business
- 2012

A strategy to find the nearly optimized solution to these type of problems, using new crossover technique for genetic algorithm that generates high quality solution to the TSP is presented.

On genetic algorithms

- Computer ScienceCOLT '95
- 1995

C Culling is near optimal for this problem, highly noise tolerant, and the best known a~~roach in some regimes, and some new large deviation bounds on this submartingale enable us to determine the running time of the algorithm.

Design and testing of a genetic algorithm neural network in the assessment of gait patterns.

- Computer ScienceMedical engineering & physics
- 2000

Tunning parameters of evolutionary algorithm in Travelling Salesman Problem with profits and returns

- Computer Science
- 2010

A new evolutionary algorithm (EA) is presented which solves TSP with profits and returns (TSPwPR), this version of TSP is often applied in Intelligent Transport Systems, especially in Vehicle Routing Problem (VRP).