An Improved Attention-based Bidirectional LSTM Model for Cyanobacterial Bloom Prediction
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12555-021-0802-9.pdf
Reference40 articles.
1. I. R. Falconer, M. D. Burch, D. A. Steffensen, M. Choice, and O. R. Coverdale, “Toxicity of the blue-green alga (cyanobacterium) microcystis aeruginosa in drinking water to growing pigs, as an animal model for human injury and risk assessment,” Environmental Toxicology and Water Quality, vol. 9, no. 2, pp. 131–139, 1994.
2. M. Kahru and B. G. Mitchell, “Ocean color reveals increased blooms in various parts of the world,” Eos, Transactions American Geophysical Union, vol. 89, no. 18, pp. 170–170, 2008.
3. C. A. Heil, P. M. Glibert, and C. Fan, “Prorocentrum minimum (pavillard) schiller: A review of a harmful algal bloom species of growing worldwide importance,” Harmful Algae, vol. 4, no. 3, pp. 449–470, 2005.
4. M. B. S. Svendsen, N. R. Andersen, P. J. Hansen, and J. F. Steffensen, “Effects of harmful algal blooms on fish: Insights from prymnesium parvum,” Fishes, vol. 3, no. 1, p. 11, 2018.
5. Y. Shimoda and G. B. Arhonditsis, “Phytoplankton functional type modelling: Running before we can walk? A critical evaluation of the current state of knowledge,” Ecological Modelling, vol. 320, pp. 29–43, 2016.
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Long-term trend forecast of chlorophyll-a concentration over eutrophic lakes based on time series decomposition and deep learning algorithm;Science of The Total Environment;2024-11
2. Deep learning for spatiotemporal forecasting in Earth system science: a review;International Journal of Digital Earth;2024-08-19
3. An ensemble model for accurate prediction of key water quality parameters in river based on deep learning methods;Journal of Environmental Management;2024-08
4. Comparative analysis of machine learning methods for prediction of chlorophyll-a in a river with different hydrology characteristics: A case study in Fuchun River, China;Journal of Environmental Management;2024-07
5. Novel Multi-flow Multi-scale Convolutional Neural Network Developed for Quality Prediction of Batch Processes to Fuse Data With Different Sampling Frequencies;International Journal of Control, Automation and Systems;2024-04-26
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3