[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 …

Bayesian neural networks for uncertainty quantification in data-driven materials modeling

A Olivier, MD Shields, L Graham-Brady - Computer methods in applied …, 2021 - Elsevier
Modern machine learning (ML) techniques, in conjunction with simulation-based methods,
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 …

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 …

Using machine learning algorithms to predict groundwater levels in Indonesian tropical peatlands

IS Hikouei, KN Eshleman, BH Saharjo… - Science of The Total …, 2023 - Elsevier
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 …

Prediction of effluent quality parameters of a wastewater treatment plant using a supervised committee fuzzy logic model

AA Nadiri, S Shokri, FTC Tsai… - Journal of cleaner …, 2018 - Elsevier
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 …

An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions

H Chu, W Wu, QJ Wang, R Nathan, J Wei - Environmental Modelling & …, 2020 - Elsevier
Hydrodynamic models are commonly used to understand flood risk and inform flood
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

A Seifi, M Ehteram, F Soroush, AT Haghighi - Engineering Applications of …, 2022 - Elsevier
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** …

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 …

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 …