[HTML][HTML] Uncertainties in the application of artificial neural networks in ocean engineering
NP Juan, C Matutano, VN Valdecantos - Ocean Engineering, 2023 - Elsevier
Abstract Artificial Neural Networks (ANNs) are becoming more popular to model ocean
engineering problems. With the development of Artificial Intelligence, data-driven models …
engineering problems. With the development of Artificial Intelligence, data-driven models …
Bayesian neural networks for uncertainty quantification in data-driven materials modeling
Modern machine learning (ML) techniques, in conjunction with simulation-based methods,
present remarkable potential for various scientific and engineering applications. Within the …
present remarkable potential for various scientific and engineering applications. Within the …
[HTML][HTML] A review of reservoir rock ty** methods in carbonate reservoirs: Relation between geological, seismic, and reservoir rock types
A Kadkhodaie-Ilkhchi… - Iranian Journal of Oil and …, 2018 - ijogst.put.ac.ir
Carbonate reservoirs rock ty** plays a pivotal role in the construction of reservoir static
models and volumetric calculations. The procedure for rock type determination starts with …
models and volumetric calculations. The procedure for rock type determination starts with …
A comprehensive assessment of water storage dynamics and hydroclimatic extremes in the Chao Phraya River Basin during 2002–2020
T Kinouchi, T Sayama - Journal of Hydrology, 2021 - Elsevier
A holistic assessment of the hydroclimatic extremes, which have caused tremendous
environmental, societal, and economic losses globally, is imperative for the highly …
environmental, societal, and economic losses globally, is imperative for the highly …
Using machine learning algorithms to predict groundwater levels in Indonesian tropical peatlands
Tropical peatlands play a vital role in the global carbon cycle as large carbon reservoirs and
substantial carbon sinks. Indonesia possesses the largest share (65%) of tropical peat …
substantial carbon sinks. Indonesia possesses the largest share (65%) of tropical peat …
Prediction of effluent quality parameters of a wastewater treatment plant using a supervised committee fuzzy logic model
Producing reclaimed water meeting water quality standards for agricultural and industrial
demands is a viable option to the Tabriz area, East Azerbaijan, Iran, due to water scarcity …
demands is a viable option to the Tabriz area, East Azerbaijan, Iran, due to water scarcity …
An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions
Hydrodynamic models are commonly used to understand flood risk and inform flood
management decisions. However, their high computational cost can impose practical limits …
management decisions. However, their high computational cost can impose practical limits …
Multi-model ensemble prediction of pan evaporation based on the Copula Bayesian Model Averaging approach
Pan evaporation (E p) is an efficient and practical tool for planning and managing water
resources, understanding the water balance in hydrological processes, and develo** …
resources, understanding the water balance in hydrological processes, and develo** …
Predicting and analysing the quality of water resources for industrial purposes using integrated data-intelligent algorithms
JC Egbueri - Groundwater for Sustainable Development, 2022 - Elsevier
The continuous increase in the rate of industrialization in develo** countries, in recent
times, calls for continuous industrial water quality assessment and prediction. This is to …
times, calls for continuous industrial water quality assessment and prediction. This is to …
Artificial neural network model for ozone concentration estimation and Monte Carlo analysis
M Gao, L Yin, J Ning - Atmospheric Environment, 2018 - Elsevier
Air pollution in urban atmosphere directly affects public-health; therefore, it is very essential
to predict air pollutant concentrations. Air quality is a complex function of emissions …
to predict air pollutant concentrations. Air quality is a complex function of emissions …