Search Results - "The, Jesse"

Spatiotemporal Air Pollution Forecasting in Houston-TX: A Case Study for Ozone Using Deep Graph Neural Networks by Oliveira Santos, Victor, Costa Rocha, Paulo Alexandre, Scott, John, Van Griensven Thé, Jesse, Gharabaghi, Bahram

“…The presence of pollutants in our atmosphere has become one of humanity’s greatest challenges. These pollutants, produced primarily by burning fossil fuels,…”
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Chlorophyll-a Estimation in 149 Tropical Semi-Arid Reservoirs Using Remote Sensing Data and Six Machine Learning Methods by Oliveira Santos, Victor, Guimarães, Bruna Monallize Duarte Moura, Neto, Iran Eduardo Lima, de Souza Filho, Francisco de Assis, Costa Rocha, Paulo Alexandre, Thé, Jesse Van Griensven, Gharabaghi, Bahram

“…It is crucial to monitor algal blooms in freshwater reservoirs through an examination of chlorophyll-a (Chla) concentrations, as they indicate the trophic…”
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Application of Quantum Neural Network for Solar Irradiance Forecasting: A Case Study Using the Folsom Dataset, California by Oliveira Santos, Victor, Marinho, Felipe Pinto, Costa Rocha, Paulo Alexandre, Thé, Jesse Van Griensven, Gharabaghi, Bahram

“…Merging machine learning with the power of quantum computing holds great potential for data-driven decision making and the development of powerful models for…”
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A New Graph-Based Deep Learning Model to Predict Flooding with Validation on a Case Study on the Humber River by Oliveira Santos, Victor, Costa Rocha, Paulo Alexandre, Scott, John, Thé, Jesse Van Griensven, Gharabaghi, Bahram

“…Floods are one of the most lethal natural disasters. It is crucial to forecast the timing and evolution of these events and create an advanced warning system…”
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Daily Streamflow Forecasting Using Networks of Real-Time Monitoring Stations and Hybrid Machine Learning Methods by Zhang, Yue, Zhou, Zimo, Deng, Ying, Pan, Daiwei, Van Griensven Thé, Jesse, Yang, Simon X., Gharabaghi, Bahram

“…Considering the increased risk of urban flooding and drought due to global climate change and rapid urbanization, the imperative for more accurate methods for…”
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Dissolved Oxygen Forecasting for Lake Erie’s Central Basin Using Hybrid Long Short-Term Memory and Gated Recurrent Unit Networks by Pan, Daiwei, Zhang, Yue, Deng, Ying, Van Griensven Thé, Jesse, Yang, Simon X., Gharabaghi, Bahram

“…Dissolved oxygen (DO) concentration is a pivotal determinant of water quality in freshwater lake ecosystems. However, rapid population growth and discharge of…”
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Deep Neural Network Modeling for CFD Simulations: Benchmarking the Fourier Neural Operator on the Lid-Driven Cavity Case by Costa Rocha, Paulo Alexandre, Johnston, Samuel Joseph, Oliveira Santos, Victor, Aliabadi, Amir A., Thé, Jesse Van Griensven, Gharabaghi, Bahram

“…In this work we present the development, testing and comparison of three different physics-informed deep learning paradigms, namely the ConvLSTM, CNN-LSTM and…”
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A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods by Thé, Jesse, Yu, Hesheng

“…Wind energy plays a vital role in the development sustainable energy due to its vast availability, commercially ready technology, low cost, and great…”
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Machine Learning Dynamic Ensemble Methods for Solar Irradiance and Wind Speed Predictions by Vidal Bezerra, Francisco Diego, Pinto Marinho, Felipe, Costa Rocha, Paulo Alexandre, Oliveira Santos, Victor, Van Griensven Thé, Jesse, Gharabaghi, Bahram

“…This paper proposes to analyze the performance increase in the forecasting of solar irradiance and wind speed by implementing a dynamic ensemble architecture…”
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Health Cost Estimation of Traffic-Related Air Pollution and Assessing the Pollution Reduction Potential of Zero-Emission Vehicles in Toronto, Canada by Shamsi, Hamidreza, Munshed, Mohammad, Tran, Manh-Kien, Lee, Youngwoo, Walker, Sean, The, Jesse, Raahemifar, Kaamran, Fowler, Michael

“…Fossil fuel vehicles, emitting air toxics into the atmosphere, impose a heavy burden on the economy through additional health care expenses and ecological…”
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Validation and optimization of SST k-ω turbulence model for pollutant dispersion within a building array by Yu, Hesheng, Thé, Jesse

“…The prediction of the dispersion of air pollutants in urban areas is of great importance to public health, homeland security, and environmental protection…”
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A hybrid model for multi-step coal price forecasting using decomposition technique and deep learning algorithms by Zhang, Kefei, Cao, Hua, Thé, Jesse, Yu, Hesheng

“…•Propose a novel hybrid model for multi-step ahead daily coal price forecasting.•Decompose original data into multiple modes via variational mode…”
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Multi-step ahead forecasting of regional air quality using spatial-temporal deep neural networks: A case study of Huaihai Economic Zone by Zhang, Kefei, Thé, Jesse, Xie, Guangyuan, Yu, Hesheng

“…Air pollution has endangered both ecological environment and human health. Long-term prediction of air quality index (AQI) is an effective approach to early…”
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Accurate prediction of band gap of materials using stacking machine learning model by Wang, Teng, Zhang, Kefei, Thé, Jesse, Yu, Hesheng

“…[Display omitted] •An extensive dataset (E-AFLOW) containing 21,534 compounds with 206 dimensions is established for band gap prediction.•The stacking approach…”
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Forecasting air quality time series using deep learning by Freeman, Brian S., Taylor, Graham, Gharabaghi, Bahram, Thé, Jesse

“…This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies…”
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Multi-step forecast of PM2.5 and PM10 concentrations using convolutional neural network integrated with spatial–temporal attention and residual learning by Zhang, Kefei, Yang, Xiaolin, Cao, Hua, Thé, Jesse, Tan, Zhongchao, Yu, Hesheng

“…[Display omitted] •A forecasting system is proposed for multi-step ahead PM2.5 and PM10 forecasting.•Spatial-temporal attention favors extracting…”
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Multi-step carbon price forecasting using a hybrid model based on multivariate decomposition strategy and deep learning algorithms by Zhang, Kefei, Yang, Xiaolin, Wang, Teng, Thé, Jesse, Tan, Zhongchao, Yu, Hesheng

“…Accurate prediction of carbon price effectively ensures the stability of the carbon trading market and reduces carbon emissions. However, making accurate…”
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Ash determination of coal flotation concentrate by analyzing froth image using a novel hybrid model based on deep learning algorithms and attention mechanism by Yang, Xiaolin, Zhang, Kefei, Ni, Chao, Cao, Hua, Thé, Jesse, Xie, Guangyuan, Tan, Zhongchao, Yu, Hesheng

“…Flotation is an important separation method for coal preparation, where ash content is critical to coal product quality. However, the absence of fast and…”
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Multi-scale neural network for accurate determination of the ash content of coal flotation concentrate using froth images by Yang, Xiaolin, Zhang, Kefei, Thé, Jesse, Tan, Zhongchao, Yu, Hesheng

“…Flotation concentrate quality is strongly correlated with its froth. Therefore, froth images can be used to determine coal concentrate quality. Earlier studies…”
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Modeling SO2 absorption into water accompanied with reversible reaction in a hollow fiber membrane contactor by Yu, Hesheng, Thé, Jesse, Tan, Zhongchao, Feng, Xianshe

“…The authors developed an efficient flue gas desulfurization (FGD) process employing a hydrophobic polypropylene hollow fiber membrane contactor (HFMC) using…”
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