Dongting Lake Algal Bloom Forecasting: Robustness and Accuracy Analysis of Deep Learning Models DOI
Yuxin Liu, Bin Yang, Kun Xie

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 485, P. 136804 - 136804

Published: Dec. 5, 2024

Language: Английский

Predicting Chlorophyll-a Concentrations in the World’s Largest Lakes Using Kolmogorov-Arnold Networks DOI
Mohammad Javad Saravani, Roohollah Noori, Changhyun Jun

et al.

Environmental Science & Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 16, 2025

Accurate prediction of chlorophyll-a (Chl-a) concentrations, a key indicator eutrophication, is essential for the sustainable management lake ecosystems. This study evaluated performance Kolmogorov-Arnold Networks (KANs) along with three neural network models (MLP-NN, LSTM, and GRU) traditional machine learning tools (RF, SVR, GPR) predicting time-series Chl-a concentrations in large lakes. Monthly remote-sensed data derived from Aqua-MODIS spanning September 2002 to April 2024 were used. The based on their forecasting capabilities March August 2024. KAN consistently outperformed others both test forecast (unseen data) phases demonstrated superior accuracy capturing trends, dynamic fluctuations, peak concentrations. Statistical evaluation using ranking metrics critical difference diagrams confirmed KAN's robust across diverse sites, further emphasizing its predictive power. Our findings suggest that KAN, which leverages KA representation theorem, offers improved handling nonlinearity long-term dependencies data, outperforming grounded universal approximation theorem algorithms.

Language: Английский

Citations

9
Artificial intelligence for life sciences: A comprehensive guide and future trends DOI

Ming Luo,

Wenyu Yang, Long Bai

et al.

The Innovation Life, Journal Year: 2024, Volume and Issue: unknown, P. 100105 - 100105

Published: Jan. 1, 2024

<p>Artificial intelligence has had a profound impact on life sciences. This review discusses the application, challenges, and future development directions of artificial in various branches sciences, including zoology, plant science, microbiology, biochemistry, molecular biology, cell developmental genetics, neuroscience, psychology, pharmacology, clinical medicine, biomaterials, ecology, environmental science. It elaborates important roles aspects such as behavior monitoring, population dynamic prediction, microorganism identification, disease detection. At same time, it points out challenges faced by application data quality, black-box problems, ethical concerns. The are prospected from technological innovation interdisciplinary cooperation. integration Bio-Technologies (BT) Information-Technologies (IT) will transform biomedical research into AI for Science paradigm.</p>

Language: Английский

Citations

7
Synergistic effect of horizontal transfer of antibiotic resistance genes between bacteria exposed to microplastics and per/polyfluoroalkyl substances: an explanation from theoretical methods DOI
Bingjia Xiao,

Qikun Pu,

Gaolei Ding

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: unknown, P. 138208 - 138208

Published: April 1, 2025

Language: Английский

Citations

0
Assessment of water ecological health in shallow lakes: A new framework based on water resource-environment-ecology DOI

Yanru Tao,

Qiujin Xu,

Mingke Luo

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 174, P. 113498 - 113498

Published: April 20, 2025

Language: Английский

Citations

0
Long-term spatiotemporal mapping in lacustrine environment by remote sensing:Review with case study, challenges, and future directions DOI

Lai Lai,

Yuchen Liu, Yuchao Zhang

et al.

Water Research, Journal Year: 2024, Volume and Issue: 267, P. 122457 - 122457

Published: Sept. 16, 2024

Language: Английский

Citations

3
Novel methodology for prediction of missing values in River flow based on convolution neural networks: Principles and application in Iran country DOI
Saeed Farzin, Mahdi Valikhan Anaraki, Mojtaba Kadkhodazadeh

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2025, Volume and Issue: unknown, P. 103875 - 103875

Published: Jan. 1, 2025

Language: Английский

Citations

0
Transformer Networks and Loss with Punishment for Optimized Management of Urban Water Supply System DOI
Yuqi Wang, Hongcheng Wang,

J. Chen

et al.

ACS ES&T Water, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 26, 2025

Language: Английский

Citations

0
Electrochemical biosensor based on strand displacement reaction for on-site detection of Skeletonema costatum DOI
Yaling Liu, Yibo Zhang,

Changrui Ye

et al.

Microchimica Acta, Journal Year: 2025, Volume and Issue: 192(3)

Published: Feb. 13, 2025

Language: Английский

Citations

0
Snapshot computed tomographic microscopic imaging spectrometer and its video-level tracking of poisonous Microcystis aeruginosa cells in mixed algae DOI
Shuo Li,

Yifan Si,

Anqi Joyce Yang

et al.

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Journal Year: 2024, Volume and Issue: 326, P. 125178 - 125178

Published: Sept. 20, 2024

Language: Английский

Citations

1
Dongting Lake Algal Bloom Forecasting: Robustness and Accuracy Analysis of Deep Learning Models DOI
Yuxin Liu, Bin Yang, Kun Xie

et al.

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 485, P. 136804 - 136804

Published: Dec. 5, 2024

Language: Английский

Citations

0