Applications based on genetic neural network model of Lianyungang marine water quality optimization techniques and algorithms Technology
As a powerful global optimization approach, genetic algorithms(GA)can solve a variety of optimization problems in which the objective function is discontinuous, non-differentiable, or highly nonlinear, to produce high convergence speed and vast search space. In this thesis. Genetic algorithm and BP algorithm can be combined to achieve complementary advantages in order to help solve the problem better. Genetic neural network applied to the comprehensive evaluation of water quality without the need for building complex parameter equation, in the circumstance that without any simplification and assumption that can carry on non-linear mapping, models are of powerful self-learning ability, and the structure is simple and practical. To the greatest degree of exclusion of more traditional evaluation methods reflect human disturbances to the greatest degree of increase assessment objectivity, reliability, thus resulting water quality of the evaluation results more in line with the actual situation.
genetic neural network model marine water quality evaluation
CHEN Wenbin MA Weixing
Department of Chemical Engineering Huaihai Institute of Technology Lianyungang, China
国际会议
西安
英文
526-529
2010-08-07（万方平台首次上网日期，不代表论文的发表时间）