A review of computational modeling in wastewater treatment processes

MS Duarte, G Martins, P Oliveira, B Fernandes… - ACS Es&t …, 2023 - ACS Publications
Wastewater treatment companies are facing several challenges related to the optimization of
energy efficiency, meeting more restricted water quality standards, and resource recovery …

SDN orchestration to combat evolving cyber threats in Internet of Medical Things (IoMT)

S Liaqat, A Akhunzada, FS Shaikh, A Giannetsos… - Computer …, 2020 - Elsevier
Abstract Internet of Medical Things (IoMT) is now worth a billion dollar market. While offering
enormous benefit, the prevalent and open environment of IoMT ecosystem can be a …

Comparison of ARIMA and LSTM for prediction of hemorrhagic fever at different time scales in China

R Zhang, H Song, Q Chen, Y Wang, S Wang, Y Li - Plos one, 2022 - journals.plos.org
Objectives This study intends to build and compare two kinds of forecasting models at
different time scales for hemorrhagic fever incidence in China. Methods Autoregressive …

Short-term forecasting of land use change using recurrent neural network models

C Cao, S Dragićević, S Li - Sustainability, 2019 - mdpi.com
Land use change (LUC) is a dynamic process that significantly affects the environment, and
various approaches have been proposed to analyze and model LUC for sustainable land …

Urban traffic flow estimation system based on gated recurrent unit deep learning methodology for Internet of Vehicles

AHA Hussain, MA Taher, OA Mahmood… - IEEE …, 2023 - ieeexplore.ieee.org
Congestion in the world's traffic systems is a major issue that has far-reaching
repercussions, including wasted time and money due to longer commutes and more …

Long short-term memory networks for traffic flow forecasting: exploring input variables, time frames and multi-step approaches

B Fernandes, F Silva, H Alaiz-Moreton, P Novais… - …, 2020 - content.iospress.com
Traffic flow forecasting is an acknowledged time series problem whose solutions have been
essentially grounded on statistical-based models. Recent times came, however, with …

Benchmarking data augmentation techniques for tabular data

P Machado, B Fernandes, P Novais - International Conference on …, 2022 - Springer
Imbalanced learning and small-sized datasets are usual in machine learning problems,
even with the increased data availability provided by recent developments. The performance …

A deep learning approach to forecast the influent flow in wastewater treatment plants

P Oliveira, B Fernandes, F Aguiar, MA Pereira… - … conference on intelligent …, 2020 - Springer
For the management and operation of a Wastewater Treatment Plant (WWTP), the influent
flow is one of the most important variables. Hence, this paper presents an evaluation of …

Exploration of highway accidents temporal changes using traffic and climate big data

D Park, K Kwon, J Park - Proceedings of the Institution of Civil …, 2023 - icevirtuallibrary.com
Anthropogenic emissions of greenhouse gases accelerate global warming and contribute to
further temperature increases. Global warming increases the likelihood of a shift towards …

Traffic flow indicator: predicting jams in a city

J Vaz, N Datia, M Pato, JM Pires - 2022 26th International …, 2022 - ieeexplore.ieee.org
Road traffic inside cities is responsible for noise and pollution, that causes health problems,
fuel consumption and waste of time in jams. Mitigation solutions are usually used to soften …