Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review

S Zendehboudi, N Rezaei, A Lohi - Applied energy, 2018 - Elsevier
Mathematical modeling and simulation methods are important tools in studying various
processes in science and engineering. In the current review, we focus on the applications of …

Renewable energy: Present research and future scope of Artificial Intelligence

SK Jha, J Bilalovic, A Jha, N Patel, H Zhang - Renewable and Sustainable …, 2017 - Elsevier
The existence of sunlight, air and other resources on earth must be used in an appropriate
way for human welfare while still protecting the environment and its living creatures. The …

Short-term probabilistic prediction of significant wave height using bayesian model averaging: Case study of chabahar port, Iran

RM Adnan, T Sadeghifar, M Alizamir, MT Azad… - Ocean …, 2023 - Elsevier
Accurate predictions of significant wave heights are important for a number of maritime
applications, such as design of coastal and offshore structures. In the present study, an …

An improved sparrow search algorithm and CNN-BiLSTM neural network for predicting sea level height

X Li, S Zhou, F Wang, L Fu - Scientific reports, 2024 - nature.com
Accurate prediction of sea level height is critically important for the government in assessing
sea level risk in coastal areas. However, due to the nonlinear, time-varying and highly …

Predicting sea level rise using artificial intelligence: a review

NAABS Bahari, AN Ahmed, KL Chong, V Lai… - … Methods in Engineering, 2023 - Springer
Forecasting sea level is critical for coastal structure building and port operations. There are,
however, challenges in making these predictions, resulting from the complicated processes …

Predictive capability evaluation of RSM, ANFIS and ANN: a case of reduction of high free fatty acid of palm kernel oil via esterification process

E Betiku, VO Odude, NB Ishola, A Bamimore… - Energy conversion and …, 2016 - Elsevier
Response surface methodology (RSM), adaptive neuro-fuzzy inference system (ANFIS) and
artificial neural network (ANN) were tested in the modeling of acid pretreatment of palm …

Hybrid adaptive neuro-fuzzy models for water quality index estimation

ZM Yaseen, MM Ramal, L Diop, O Jaafar… - Water Resources …, 2018 - Springer
Soft computing models are known as an efficient tool for modelling temporal and spatial
variation of surface water quality variables and particularly in rivers. These model's …

[HTML][HTML] Readiness of artificial intelligence technology for managing energy demands from renewable sources

J Verma, L Sandys, A Matthews, S Goel - Engineering Applications of …, 2024 - Elsevier
The use of artificial intelligence (AI) has gained tremendous popularity in recent years, and it
has become ubiquitous for use in the energy sector. The newly emerging digitalised tools …

Efficient river water quality index prediction considering minimal number of inputs variables

F Othman, ME Alaaeldin, M Seyam… - Engineering …, 2020 - Taylor & Francis
Water Quality Index (WQI) is the most common determinant of the quality of the stream-flow.
According to the Department of Environment (DOE, Malaysia), WQI is chiefly affected by six …

RBFNN versus FFNN for daily river flow forecasting at Johor River, Malaysia

ZM Yaseen, A El-Shafie, HA Afan, M Hameed… - Neural Computing and …, 2016 - Springer
Streamflow forecasting can have a significant economic impact, as this can help in water
resources management and in providing protection from water scarcities and possible flood …