摘要: |
针对基于传统BP神经网络的海水水质评价模型存在易陷入局部极小等问题,提出了一种新的利用头脑风暴优化算法(BSO)优化BP神经网络的海水水质评价模型(BSO-BP)。该模型引入具有全局寻优特点的头脑风暴优化算法,用于模拟人类提出创造性思维解决问题的过程,具有强大的全局搜索和局部搜索的能力,同时利用BP神经网络所具有良好的非线性映射能力、学习适应能力和容错性,最大程度上考虑到海洋水质评价因素的非线性和非平稳的关系,得到BP神经网络的各层权值、阈值的最优解,使得海水水质评价结果准确合理。并以胶州湾海域的12个监测站位的监测数据作为评价样本进行水质评价,实验结果表明该评价模型能够克服局部极小问题,评价结果准确性较高,并具有一定的实用性。 |
关键词: 海洋环境科学 头脑风暴优化算法 BP神经网络 海水水质评价 |
DOI:10.3969/J.ISSN.2095-4972.2020.01.008 |
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基金项目:青岛市创新创业领军人才资助项目(15-07-03-0030); 农业部水产养殖数字农业建设试点资助项目(2017-A2131-130209-K0104-00) |
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Research on seawater quality evaluation model based on brain storm optimization algorithm and BP neural network |
LI Hai-tao,SHAO Ze-dong |
(College of Information Science and Technology,Qingdao University of Science and Technology,Qingdao 266000, China) |
Abstract: |
Aiming at the problem that the seawater quality assessment model based on traditional BP neural network falls easily into local minimum, a new seawater quality assessment model (BSO-BP) used BP neural network optimized by brainstorm optimization algorithm (BSO) is proposed. The model introduces a brainstorming optimization algorithm with global optimization features, which is used to simulate the process of human beings to solve problems with creative thinking. It has powerful global and local search capabilities of BP neural network with good nonlinear mapping ability. Taken advantage of learning adaptability and fault tolerance, and taken into account the nonlinear and nonstationary relationship of marine water quality assessment factors to the greatest extent, the optimal solution of the weight and threshold of each layer of BP neural network is obtained for much accurate and reasonable result in seawater quality assessment. The monitoring data from 12 stations in the Jiaozhou Bay is used for water quality evaluation. The experimental results show that the evaluation model can overcome local minimum problem, and the evaluation results are highly accurate and have certain practicability. |
Key words: marine environmental science brain storm optimization algorithm BP neural network seawater quality evaluation |