Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Sequential particle swarm optimization (S-PSO) is a modification of PSO suitable for high-dimensional optimization problems. S-PSO iteratively optimizes the objective function over randomly selected subspaces of the parameter search space instead of the entire parameter space at once as in standard PSO. This approach is advantageous since fer particles are needed to solve the lor-dimension subproblems. S-PSO is applied to the distributed sonar sensor placement problem, where not only the dimensionality issue arises, but also the computational complexity of the objective function increases with the problem size. Simulations show that S-PSO outperforms standard PSO both in terms of convergence and computational efficiency.
['Patrick N. Ngatchou', 'Warren L. J. Fox', 'Mohamed A. El-Sharkawi']
I am writing a research paper on a idea Distributed sensor placement with sequential particle swarm optimization
[{"from": "human", "value": "I am writing a research paper on a idea Distributed sensor placement with sequential particle swarm optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Sequential particle swarm optimization (S-PSO) is a modification of PSO suitable for high-dimensional optimization problems. S-PSO iteratively optimizes the objective function over randomly selected subspaces of the parameter search space instead of the entire parameter space at once as in standard PSO. This approach is advantageous since fer particles are needed to solve the lor-dimension subproblems. S-PSO is applied to the distributed sonar sensor placement problem, where not only the dimensionality issue arises, but also the computational complexity of the objective function increases with the problem size. Simulations show that S-PSO outperforms standard PSO both in terms of convergence and computational efficiency."}]