[HTML][HTML] A Method for Predicting Indoor CO2 Concentration in University Classrooms: An RF-TPE-LSTM Approach
Z Dai, Y Yuan, X Zhu, L Zhao - Applied Sciences, 2024 - mdpi.com
Classrooms play a pivotal role in students' learning, and maintaining optimal indoor air
quality is crucial for their well-being and academic performance. Elevated CO2 levels can …
quality is crucial for their well-being and academic performance. Elevated CO2 levels can …
The interplay between financial development, electricity consumption and foreign direct investment in the GCC countries: new insights from GMM panel VAR
H Saidi, GE Montasser, N Doytch - Energy Sources, Part B …, 2022 - Taylor & Francis
Over the past years, the economies of the Gulf Cooperation Countries (GCC) countries,
which hold a large of the world in oil and gas exports, have suffered from dramatic declines …
which hold a large of the world in oil and gas exports, have suffered from dramatic declines …
Game-theoretic modeling in regulating greenhouse gas emissions
O Maevsky, M Kovalchuk, Y Brodsky, V Stanytsina… - Heliyon, 2024 - cell.com
This research introduces an innovative framework for addressing the escalating issue of
greenhouse gas emissions through the integration of game theory with differential …
greenhouse gas emissions through the integration of game theory with differential …
Stock price forecasting using deep learning model
The successful prediction of future stock prices can give significant future profit. The financial
experts are divided over the possibility of correct prediction of future stock prices. A stronger …
experts are divided over the possibility of correct prediction of future stock prices. A stronger …
A Hybrid Neural Network‐Based Improved PSO Algorithm for Gas Turbine Emissions Prediction
In gas‐fired power plants, emissions may reduce turbine blade rotation, thus decreasing
power output. This study proposes a hybrid model integrating the Feed forward Neural …
power output. This study proposes a hybrid model integrating the Feed forward Neural …
Representing Multi-View Time-Series Graph Structures for Multivariate Long-Term Time-Series Forecasting
Z Wang, J Fan, H Wu, D Sun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Multivariate long-term time-series forecasting tasks are very challenging tasks in many real-
world application areas. Recently, researchers focus on designing robust and effective …
world application areas. Recently, researchers focus on designing robust and effective …
Eco4cast: Bridging predictive scheduling and cloud computing for reduction of carbon emissions for ML models training
We introduce eco4cast, 1 an open-source package aimed to reduce carbon footprint of
machine learning models via predictive cloud computing scheduling. The package is …
machine learning models via predictive cloud computing scheduling. The package is …
Evolving Dynamic Bayesian Networks for CO2 Emissions Forecasting in Multi-Source Power Generation Systems
Global warming is a significant challenge. Among the contributors, CO2 emission is the
foremost, and almost 40% of global emissions come from electricity generation. In this …
foremost, and almost 40% of global emissions come from electricity generation. In this …
[PDF][PDF] European Union 2030 Carbon Emission Target: The Case of Turkey. Sustainability 2023, 15, 13025
M Kayakus, M Terzioglu, D Erdogan, SA Zetter… - 2023 - academia.edu
Climate awareness caused by the threat of global warming is the number one agenda item
for developed and developing economies. Plans developed in this context, environmentally …
for developed and developing economies. Plans developed in this context, environmentally …
CO2 emission prediction from coal used in power plants: a machine learning-based approach
The utilization of fossil fuels has led to a significant rise in carbon dioxide (CO2) emission.
Among various sectors, the energy industry plays a substantial role in contributing to global …
Among various sectors, the energy industry plays a substantial role in contributing to global …