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

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 485, С. 136804 - 136804

Опубликована: Дек. 5, 2024

Язык: Английский

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

и другие.

Environmental Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 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.

Язык: Английский

Процитировано

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

Ming Luo,

Wenyu Yang, Long Bai

и другие.

The Innovation Life, Год журнала: 2024, Номер unknown, С. 100105 - 100105

Опубликована: Янв. 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>

Язык: Английский

Процитировано

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

и другие.

Journal of Hazardous Materials, Год журнала: 2025, Номер unknown, С. 138208 - 138208

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

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

и другие.

Water Research, Год журнала: 2024, Номер 267, С. 122457 - 122457

Опубликована: Сен. 16, 2024

Язык: Английский

Процитировано

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

и другие.

Physics and Chemistry of the Earth Parts A/B/C, Год журнала: 2025, Номер unknown, С. 103875 - 103875

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

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

J. Chen

и другие.

ACS ES&T Water, Год журнала: 2025, Номер unknown

Опубликована: Янв. 26, 2025

Язык: Английский

Процитировано

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

Changrui Ye

и другие.

Microchimica Acta, Год журнала: 2025, Номер 192(3)

Опубликована: Фев. 13, 2025

Язык: Английский

Процитировано

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

и другие.

Ecological Indicators, Год журнала: 2025, Номер 174, С. 113498 - 113498

Опубликована: Апрель 20, 2025

Язык: Английский

Процитировано

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

и другие.

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Год журнала: 2024, Номер 326, С. 125178 - 125178

Опубликована: Сен. 20, 2024

Язык: Английский

Процитировано

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

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 485, С. 136804 - 136804

Опубликована: Дек. 5, 2024

Язык: Английский

Процитировано

0