Multivariate Time-Series Forecasting: A Review of Deep Learning Methods in Internet of Things Applications to Smart Cities
V Papastefanopoulos, P Linardatos… - Smart Cities, 2023 - mdpi.com
Smart cities are urban areas that utilize digital solutions to enhance the efficiency of
conventional networks and services for sustainable growth, optimized resource …
conventional networks and services for sustainable growth, optimized resource …
A hybrid model for water quality prediction based on an artificial neural network, wavelet transform, and long short-term memory
J Wu, Z Wang - Water, 2022 - mdpi.com
Clean water is an indispensable essential resource on which humans and other living
beings depend. Therefore, the establishment of a water quality prediction model to predict …
beings depend. Therefore, the establishment of a water quality prediction model to predict …
A review of hybrid soft computing and data pre-processing techniques to forecast freshwater quality's parameters: Current trends and future directions
ZS Khudhair, SL Zubaidi, S Ortega-Martorell… - Environments, 2022 - mdpi.com
Water quality has a significant influence on human health. As a result, water quality
parameter modelling is one of the most challenging problems in the water sector. Therefore …
parameter modelling is one of the most challenging problems in the water sector. Therefore …
Data science methods and tools for industry 4.0: A systematic literature review and taxonomy
The Fourth Industrial Revolution, also named Industry 4.0, is leveraging several modern
computing fields. Industry 4.0 comprises automated tasks in manufacturing facilities, which …
computing fields. Industry 4.0 comprises automated tasks in manufacturing facilities, which …
Large-scale prediction of stream water quality using an interpretable deep learning approach
Deep learning methods, which have strong capabilities for mapping highly nonlinear
relationships with acceptable calculation speed, have been increasingly applied for water …
relationships with acceptable calculation speed, have been increasingly applied for water …
A long-term water quality prediction method based on the temporal convolutional network in smart mariculture
Y Fu, Z Hu, Y Zhao, M Huang - Water, 2021 - mdpi.com
In smart mariculture, traditional methods are not only difficult to adapt to the complex,
dynamic and changeable environment in open waters, but also have many problems, such …
dynamic and changeable environment in open waters, but also have many problems, such …
Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay
Flow estimation provides valuable information to support decision making in controlling 30
floods, operating water resources, and mitigating water quality degradation (Alfieri et al., 31 …
floods, operating water resources, and mitigating water quality degradation (Alfieri et al., 31 …
Bat algorithm optimised extreme learning machine (Bat‐ELM): a novel approach for Daily River water temperature modelling
Here, the capability of the Bat algorithm optimised extreme learning machines ELM (Bat‐
ELM) is demonstrated for river water temperature (T w) modelling in the Orda River, Poland …
ELM) is demonstrated for river water temperature (T w) modelling in the Orda River, Poland …
Hybrid Technique to Improve the River Water Level Forecasting Using Artificial Neural Network‐Based Marine Predators Algorithm
SJ Mohammed, SL Zubaidi, N Al-Ansari… - Advances in Civil …, 2022 - Wiley Online Library
Water level (WL) forecasting has become a difficult undertaking due to spatiotemporal
fluctuations in climatic factors and complex physical processes. This paper proposes a novel …
fluctuations in climatic factors and complex physical processes. This paper proposes a novel …
Least square support vector machine-based variational mode decomposition: a new hybrid model for daily river water temperature modeling
Abstract Machines learning models have recently been proposed for predicting rivers water
temperature (T w) using only air temperature (T a). The proposed models relied on a …
temperature (T w) using only air temperature (T a). The proposed models relied on a …