[HTML][HTML] Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review

SE Bibri, J Krogstie, A Kaboli, A Alahi - Environmental Science and …, 2024‏ - Elsevier
The recent advancements made in the realms of Artificial Intelligence (AI) and Artificial
Intelligence of Things (AIoT) have unveiled transformative prospects and opportunities to …

Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda

R Nishant, M Kennedy, J Corbett - International journal of information …, 2020‏ - Elsevier
Artificial intelligence (AI) will transform business practices and industries and has the
potential to address major societal problems, including sustainability. Degradation of the …

Artificial intelligence: a survey on evolution, models, applications and future trends

Y Lu - Journal of Management Analytics, 2019‏ - Taylor & Francis
Artificial intelligence (AI) is one of the core drivers of industrial development and a critical
factor in promoting the integration of emerging technologies, such as graphic processing …

A systematic literature review on lake water level prediction models

S Ozdemir, M Yaqub, SO Yildirim - Environmental Modelling & Software, 2023‏ - Elsevier
Global climate change has led to large fluctuations in lake levels in recent years as
meteorological and hydrological parameters have changed and water use has been …

[HTML][HTML] Hybridization of artificial intelligence models with nature inspired optimization algorithms for lake water level prediction and uncertainty analysis

M Ehteram, A Ferdowsi, M Faramarzpour… - Alexandria Engineering …, 2021‏ - Elsevier
In the present study, an improved adaptive neuro fuzzy inference system (ANFIS) and
multilayer perceptron (MLP) models are hybridized with a sunflower optimization (SO) …

A multi-source data-driven model of lake water level based on variational modal decomposition and external factors with optimized bi-directional long short-term …

R Tan, Y Hu, Z Wang - Environmental Modelling & Software, 2023‏ - Elsevier
An accurate prediction of lake water levels is of great significance to water resource
regulation, flood prevention and mitigation. However, water level fluctuations have been …

Lake water-level fluctuation forecasting using machine learning models: a systematic review

S Zhu, H Lu, M Ptak, J Dai, Q Ji - Environmental Science and Pollution …, 2020‏ - Springer
Lake water-level fluctuation is a complex and dynamic process, characterized by high
stochasticity and nonlinearity, and difficult to model and forecast. In recent years …

Delineation of isotopic and hydrochemical evolution of karstic aquifers with different cluster-based (HCA, KM, FCM and GKM) methods

E Eskandari, H Mohammadzadeh, H Nassery… - Journal of …, 2022‏ - Elsevier
In this work, a combination of isotopic and hydrogeochemical data of a karstic region was
clustered with four distinct clustering analysis (CA) methods to study water evolution in a …

Floodplain lake water level prediction with strong river-lake interaction using the ensemble learning LightGBM

M Gan, X Lai, Y Guo, Y Chen, S Pan… - Water Resources …, 2024‏ - Springer
Timely and accurate prediction of water levels is crucial for managing floodplain lakes with
important ecosystem services, especially for flood prevention. Floodplain lakes are …

Map** shoreline change using machine learning: a case study from the eastern Indian coast

L Kumar, MS Afzal, MM Afzal - Acta Geophysica, 2020‏ - Springer
The continuous shift of shoreline boundaries due to natural or anthropogenic events has
created the necessity to monitor the shoreline boundaries regularly. This study investigates …