[HTML][HTML] Integrating Digital Twins and Artificial Intelligence Multi-Modal Transformers into Water Resource Management: Overview and Advanced Predictive …
Various Artificial Intelligence (AI) techniques in water resource management highlight the
current methodologies' strengths and limitations in forecasting, optimization, and control. We …
current methodologies' strengths and limitations in forecasting, optimization, and control. We …
How deep learning can help in regulating the subscription economy to ensure sustainable consumption and production patterns (12th Goal of SDGs)
In today's rapidly changing world, the importance of sustainable consumption cannot be
underestimated. Businesses are taking part in the subscription economy because of the …
underestimated. Businesses are taking part in the subscription economy because of the …
An empirical study of environmental data prediction in the United States Energy-Water Nexus
Y Jin, EJ Yang, J Fulton - IEEE access, 2021 - ieeexplore.ieee.org
Electricity generation systems are dependent on water availability and planning for future
water scarcity is currently hindered by limited data and predictive models. The Energy-Water …
water scarcity is currently hindered by limited data and predictive models. The Energy-Water …
SW Forecaster: An Intelligent Data-Driven Approach for Water Usage Demand Forecasting
Short-term water demand prediction is essential for optimizing residential and industrial
water management. Several studies have demonstrated the usefulness of water usage …
water management. Several studies have demonstrated the usefulness of water usage …
Water Pump Operation Optimization under Dynamic Market and Consumer Behaviour
In the face of growing energy and water consumption, the pumping costs of water supply
systems in high-rise buildings are on the rise. The state of practice uses statically configured …
systems in high-rise buildings are on the rise. The state of practice uses statically configured …
[PDF][PDF] Prediction of Water Consumption Using Machine Learning: Using machine learning techniques to predict hourly water consumption in sustainable smart city
E Kalashak - 2021 - hiof.brage.unit.no
Energy demand and consumption are increasing as the world's population grows. This
raises numerous challenges concerning resource constraints, given that the energy …
raises numerous challenges concerning resource constraints, given that the energy …
Wireless channel quality prediction using sparse gaussian conditional random fields
Accurate wireless channel quality prediction over 4G LTE networks continues to be an
important problem as future channel predictions are widely leveraged to meet the strict …
important problem as future channel predictions are widely leveraged to meet the strict …
DeepER: A Deep Learning based Emergency Resolution Time Prediction System
G Bejarano, A Kulkarni, X Luo… - … on Internet of Things …, 2020 - ieeexplore.ieee.org
Accurately predicting resolution time for emergency incidents is crucial for public safety and
smooth functioning of cities as it helps in planning resources that will be available for …
smooth functioning of cities as it helps in planning resources that will be available for …
Water Consumption Analysis and Prediction Using Deep Learning Approach
N Agize - 2024 - repository.smuc.edu.et
Water is one of humanity's most essential resources, and in order to ensure that the limited
quantity of water is used effectively, water supply facilities are required. The global …
quantity of water is used effectively, water supply facilities are required. The global …
Swift: A non-emergency response prediction system using sparse gaussian conditional random fields
Cities have limited resources that must be used efficiently to maintain their smooth
operation. To facilitate efficient resource allocation and management in cities, in this paper …
operation. To facilitate efficient resource allocation and management in cities, in this paper …