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Hybrid VMD-CNN-GRU-based model for short-term forecasting of wind power considering spatio-temporal features
Z Zhao, S Yun, L Jia, J Guo, Y Meng, N He, X Li… - … Applications of Artificial …, 2023 - Elsevier
Accurate and reliable short-term forecasting of wind power is vital for balancing energy and
integrating wind power into a grid. A novel hybrid deep learning model is designed in this …
integrating wind power into a grid. A novel hybrid deep learning model is designed in this …
Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
Modelling impacts of climate change and anthropogenic activities on inflows and sediment loads of wetlands: Case study of the Anzali wetland
Understanding the effects of climate change and anthropogenic activities on the
hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective …
hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective …
[HTML][HTML] Gaussian process emulation of spatio-temporal outputs of a 2D inland flood model
The computational limitations of complex numerical models have led to adoption of
statistical emulators across a variety of problems in science and engineering disciplines to …
statistical emulators across a variety of problems in science and engineering disciplines to …
The prediction of WWTP influent characteristics: Good practices and challenges
M Andreides, P Dolejš, J Bartáček - Journal of Water Process Engineering, 2022 - Elsevier
The prediction of influent characteristics using state-of-the-art mathematical models can help
optimize wastewater treatment plants (WWTP) processes. However, WWTP operators lack …
optimize wastewater treatment plants (WWTP) processes. However, WWTP operators lack …
[HTML][HTML] Marine waters assessment using improved water quality model incorporating machine learning approaches
In marine ecosystems, both living and non-living organisms depend on “good” water quality.
It depends on a number of factors, and one of the most important is the quality of the water …
It depends on a number of factors, and one of the most important is the quality of the water …
Evaluation of groundwater quality for irrigation in deep aquifers using multiple graphical and indexing approaches supported with machine learning models and GIS …
Irrigation has made a significant contribution to supporting the population's expanding food
demands, as well as promoting economic growth in irrigated regions. The current …
demands, as well as promoting economic growth in irrigated regions. The current …
Enhanced wave overtop** simulation at vertical breakwaters using machine learning algorithms
Accurate prediction of wave overtop** at sea defences remains central to the protection of
lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased …
lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased …
Environmental risk assessment of wetland ecosystems using Bayesian belief networks
Wetlands are valuable natural capital and sensitive ecosystems facing significant risks from
anthropogenic and climatic stressors. An assessment of the environmental risk levels for …
anthropogenic and climatic stressors. An assessment of the environmental risk levels for …
Efficient data-driven machine learning models for scour depth predictions at slo** sea defences
Seawalls are critical defence infrastructures in coastal zones that protect hinterland areas
from storm surges, wave overtop** and soil erosion hazards. Scouring at the toe of sea …
from storm surges, wave overtop** and soil erosion hazards. Scouring at the toe of sea …