[HTML][HTML] Towards a smart water city: A comprehensive review of applications, data requirements, and communication technologies for integrated management

M Oberascher, W Rauch, R Sitzenfrei - Sustainable Cities and Society, 2022 - Elsevier
Smart cities are an innovate concept for managing urban cities to enhance sustainability and
increase quality of life for citizens. Although urban water infrastructure (UWI) performs …

Urban drought challenge to 2030 sustainable development goals

X Zhang, N Chen, H Sheng, C Ip, L Yang… - Science of the Total …, 2019 - Elsevier
In the first two decades of the 21st century, 79 global big cities have suffered extensively
from drought disaster. Meanwhile, climate change has magnified urban drought in both …

[HTML][HTML] Bitcoin price prediction using machine learning: An approach to sample dimension engineering

Z Chen, C Li, W Sun - Journal of Computational and Applied Mathematics, 2020 - Elsevier
After the boom and bust of cryptocurrencies' prices in recent years, Bitcoin has been
increasingly regarded as an investment asset. Because of its highly volatile nature, there is a …

Data analytics in the supply chain management: Review of machine learning applications in demand forecasting

A Aamer, LP Eka Yani… - Operations and Supply …, 2020 - journal.oscm-forum.org
In today's fast-paced global economy coupled with the availability of mobile internet and
social networks, several business models have been disrupted. This disruption brings a …

Short term water demand forecast modelling using artificial intelligence for smart water management

M Kavya, A Mathew, PR Shekar, P Sarwesh - Sustainable Cities and …, 2023 - Elsevier
Water is an important resource for life and its existence. Water demand is increasing with
increasing economic growth and population, while the water availability is continually …

Industrial 6G-IoT and machine learning-supported intelligent sensing framework for indicator control strategy in sewage treatment process

Z Guo, Y Shen, C Chakraborty… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
In context of 6G mobile computing, the combination of Industrial Internet of Things (IoT) and
machine learning extends intelligent sensing ability to improve industrial operation …

Deep learning with long short-term memory neural networks combining wavelet transform and principal component analysis for daily urban water demand forecasting

B Du, Q Zhou, J Guo, S Guo, L Wang - Expert Systems with Applications, 2021 - Elsevier
A reliable and accurate urban water demand forecasting plays a significant role in building
intelligent water supplying system and smart city. Due to the high frequency noise and …

Short-term water demand forecast based on deep learning method

G Guo, S Liu, Y Wu, J Li, R Zhou… - Journal of Water …, 2018 - ascelibrary.org
Short-time water demand forecasting is essential for optimal control in a water distribution
system (WDS). Current methods (eg, time-series models and conventional artificial neural …

A new dynamic firefly algorithm for demand estimation of water resources

H Wang, W Wang, Z Cui, X Zhou, J Zhao, Y Li - Information Sciences, 2018 - Elsevier
Firefly algorithm (FA) is an effective optimization technique based on swarm intelligence,
which has been successfully applied to various practical engineering problems. In this …

Novel approach for burst detection in water distribution systems based on graph neural networks

A Zanfei, A Menapace, BM Brentan, M Righetti… - Sustainable Cities and …, 2022 - Elsevier
Sustainable management of water resources is a key challenge for the well-being and
security of current and future society worldwide. In this regard, water utilities have to ensure …