Machine-learning technique OECD: Organization for Economic Cooperation and Development, UN OPT: Occupied Palestinian Territories (part of Historic Palestine) PV: Photovoltaic (solar energy) SEA Protocol: Strategic Environmental Assessment Protocol SMHI: Swedish Meteorological and Hydrological Institute ...
Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 images Additionally, this study examined the effects of climatic factors and water quality parameters on the biomass abundance of algae. The findings suggest that ... Zhaojiang...
Machine learning can process massive amounts of data, extract valuable information, and automatically construct models to predict future trends [16]. In water resource management, such data enable a more comprehensive consideration of problems and the establishment of improved decision-making models [17...
this study aimed to map GWQ in the central plateau of Iran by validating machine learning algorithms (MLAs) using game theory (GT). On this basis, chemical parameters related to water quality, including K+, Na+, Mg2+, Ca2+, SO
deep learning (MDL) models were developed and rigorously validated using atmospherically corrected Landsat remote sensing reflectance data and synchronous water quality measurements for estimating long-term Chlorophyll-a (Chl-a), total phosphorus (TP), and total nitrogen (TN) in Lake Simcoe, Canada. ...
select article Three-dimensional augmentation for hyperspectral image data of water quality: An Integrated approach using machine learning and numerical models Research articleAbstract only Three-dimensional augmentation for hyperspectral image data of water quality: An Integrated approach using machine learning...
learning methods can help address data scarcity by filling temporal and spatial gaps and aid in formulating and testing hypotheses via identifying influential drivers of water quality. This Review highlights the strengths and limitations of deep learning methods relative to traditional approaches, and ...
The water quality index (WQI) has been used to identify threats to water quality and to support better water resource management. This study combines a machine learning algorithm, WQI, and remote sensing spectral indices (difference index, DI; ratio inde
Finally, we demonstrate that these proposed ML approaches have superior performance over traditional model-based methods by simulations using actual data collected from three lake experiments. 展开 关键词: Underwater acoustic communication (UAC) Harsh oceanic environment Adaptive modulation and coding (AMC...
Phosphorus Lake Mendota Model Machine learning Lake Long-term 1. Introduction Phosphorus (P) is a critical limiting nutrient for phytoplankton and microbes (Schindler et al., 2016) and thus is an important driver of water quality in many lakes and reservoirs (Wetzel 2001). Where lakes and reser...