Artificial Neural Network Hyperparameters Optimization: A Survey.

ZS Kadhim, HS Abdullah… - International Journal of …, 2022 - search.ebscohost.com
Abstract Machine-learning (ML) methods often utilized in applications like computer vision,
recommendation systems, natural language processing (NLP), as well as user behavior …

A short-term water demand forecasting model using multivariate long short-term memory with meteorological data

A Zanfei, BM Brentan, A Menapace… - Journal of …, 2022 - iwaponline.com
Sustainable management of water resources is a key challenge nowadays and in the future.
Water distribution systems have to ensure fresh water for all users in an increasing demand …

An ensemble neural network model to forecast drinking water consumption

A Zanfei, A Menapace, F Granata… - Journal of Water …, 2022 - ascelibrary.org
A reliable short-term forecasting model is fundamental to managing a water distribution
system properly. This study addresses the problem of the efficient development of a deep …

[HTML][HTML] A comparison of artificial intelligence models for predicting phosphate removal efficiency from wastewater using the electrocoagulation process

MG Shirkoohi, RD Tyagi, PA Vanrolleghem… - Digital Chemical …, 2022 - Elsevier
In this study, artificial intelligence (AI) models including adaptive neuro-fuzzy inference
systems (ANFIS), artificial neural networks (ANN), and support vector regression (SVR) were …

Forecasting daily electricity consumption in Thailand using regression, artificial neural network, support vector machine, and hybrid models

W Pannakkong, T Harncharnchai, J Buddhakulsomsiri - Energies, 2022 - mdpi.com
This article involves forecasting daily electricity consumption in Thailand. Electricity
consumption data are provided by the Electricity Generating Authority of Thailand, the …

Data mining techniques in psychotherapy: applications for studying therapeutic alliance

NS Mosavi, E Ribeiro, A Sampaio, MF Santos - Scientific Reports, 2023 - nature.com
Therapeutic Alliance (TA) has been consistently reported as a robust predictor of therapy
outcomes and is one of the most investigated therapy relational factors. Research on …

How does missing data imputation affect the forecasting of urban water demand?

A Zanfei, A Menapace, BM Brentan… - Journal of Water …, 2022 - ascelibrary.org
Nowadays, drinking water demand forecasting has become fundamental to efficiently
manage water distribution systems. With the growth of accessible data and the increase of …

An artificial intelligence approach for managing water demand in water supply systems

A Zanfei, A Menapace, M Righetti - IOP Conference Series: Earth …, 2023 - iopscience.iop.org
Water demand management is essential for water utilities, which have the critical task of
supplying drinking water from water sources to end-users through the distribution network …

Ecological design with the use of selected inventive methods including AI-based

E Dostatni, D Mikołajewski, J Dorożyński, I Rojek - Applied Sciences, 2022 - mdpi.com
Featured Application Potential application of the work concerns AI-supported eco-design of
a novel family of products. Abstract Creative thinking is an inherent process in the creation of …

[HTML][HTML] Graph neural networks for sensor placement: A proof of concept towards a digital twin of water distribution systems

A Menapace, A Zanfei, M Herrera, B Brentan - Water, 2024 - mdpi.com
Urban water management faces new challenges due to the rise of digital solutions and
abundant data, leading to the development of data-centric tools for decision-making in …