Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: For Artificial Neural Network application, its ights and structure optimization design is a key problem. The Mind Evolutionary Algorithm (MEA) is a new evolutionary algorithm which simulates the process of human mind evolution, it has the porful ability to find global optimum, and it also has much superiority for resolving the problem of numerical and non-numerical optimization. , a new typical MEA is presented based on the foundational MEA framework to optimize the neural network structure and ights, in which effective similartaxis and dissimilation operators of structure optimization are designed. Through similartaxis operators, the local optimum is found, then exceeding the restriction of local range through dissimilation operators, the global optimum is acquire in global solution space. Finally, simulation results show the effectiveness and correctness of the method.
['Tao Fan', 'Rui-Ping Wen']
I am writing a research paper on a idea MEA for Designing Neural Network Weights and Structure Optimization
[{"from": "human", "value": "I am writing a research paper on a idea MEA for Designing Neural Network Weights and Structure Optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: For Artificial Neural Network application, its ights and structure optimization design is a key problem. The Mind Evolutionary Algorithm (MEA) is a new evolutionary algorithm which simulates the process of human mind evolution, it has the porful ability to find global optimum, and it also has much superiority for resolving the problem of numerical and non-numerical optimization. , a new typical MEA is presented based on the foundational MEA framework to optimize the neural network structure and ights, in which effective similartaxis and dissimilation operators of structure optimization are designed. Through similartaxis operators, the local optimum is found, then exceeding the restriction of local range through dissimilation operators, the global optimum is acquire in global solution space. Finally, simulation results show the effectiveness and correctness of the method."}]