Using Genetic Algorithm and Particle Swarm Optimization BP Neural Network Algorithm to Improve Marine Oil Spill Prediction-Reference-Cited by-同舟云学术

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Using Genetic Algorithm and Particle Swarm Optimization BP Neural Network Algorithm to Improve Marine Oil Spill Prediction

Published:2022-08 Issue:8 Volume:233 Page:
ISSN:0049-6979
Container-title:Water, Air, & Soil Pollution
language:en
Short-container-title:Water Air Soil Pollut

Author:

Cheng Xueyan,Hu Xupeng,Li Zhenzhen,Geng Chuanhui,Liu Jiaxing,Liu Mei,Zhu Baikang,Li Qian,Chen Qingguo^ORCID

Funder

National Natural Science Foundation of China

Basic Public Welfare Research Program of Zhejiang Province

Zhejiang Key Laboratory of Safety Engineering and Technology

the Open Research Subject of Zhejiang Key Laboratory of Petrochemical Environmental Pollution Control

Fundamental Research Funds for Central Universities of the Central South University

Publisher

Springer Science and Business Media LLC

Subject

Pollution,Water Science and Technology,Ecological Modeling,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11270-022-05771-x.pdf

Reference54 articles.

1. Ahn, H., & Kim, K. J. (2009). Global optimization of case-based reasoning for breast cytology diagnosis. Expert Systems with Applications, 36(1), 724–734. https://doi.org/10.1016/j.eswa.2007.10.023

2. Ahn, H., Kim, K. J., & Han, I. (2006). Hybrid genetic algorithms and case-based reasoning systems for customer classification. Expert Systems, 23(3), 127–144. https://doi.org/10.1111/j.1468-0394.2006.00329

3. ASCE Task Committee. (1996). State-of-the-art review of modelling transport and fate of oil spills. Journal of Hydraulic Engineering, 122, 594–609. https://doi.org/10.1016/S0025-326X(18)30504-6/rf0010

4. Berry, A., Dabrowski, T., & Lyons, K. (2012). The oil spill model OILTRANS and its application to the Celtic Sea. Marine Pollution Bulletin, 64(11), 2489–2501. https://doi.org/10.1016/j.marpolbul.2012.07.036

5. Cantorna, D., Dafonte, C., Iglesias, A., & Arcay, B. (2019). Oil spill segmentation in SAR images using convolutional neural networks. A comparative analysis with clustering and logistic regression algorithms. Applied Soft Computing Journal, 84, 105716. https://doi.org/10.1016/j.asoc.2019.105716

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