An efficient algorithm based on artificial neural networks and particle swarm optimization for solution of nonlinear Troesch's problem.
Neha YadavAnupam YadavManoj KumarJoong Hoon KimPublished in: Neural Comput. Appl. (2017)
Keyphrases
- particle swarm optimization
- artificial neural networks
- optimal solution
- dynamic programming
- cost function
- learning algorithm
- solution quality
- particle swarm optimization algorithm
- particle swarm
- computational cost
- search space
- computational complexity
- nonlinear equations
- simulated annealing
- numerical integration
- segmentation algorithm
- detection algorithm
- closed form
- ant colony optimization
- global optimum
- piecewise linear
- recognition algorithm
- preprocessing
- levenberg marquardt
- matching algorithm
- mathematical model
- np hard
- computationally efficient
- worst case
- linear systems
- evolutionary strategy
- linear approximation
- greedy strategy
- improved algorithm
- solution space
- pso algorithm
- convex hull
- linear programming
- computational intelligence
- significant improvement
- feature space
- objective function