… calculator, we gathered data regarding CO2eq emissions of different grid locations and …
For instance, in Figure 1, we show the distribution and variation in carbon emissions depending …

… The study applies the long short-term memory (LSTM) method, a novel machine learning (…
on CO 2 emissions; correspondingly, this study builds a model for CO 2 emission reduction. …

… to propose a new machine learning-based downscaling … first attempt to use a machine
learning-based downscaling method that … conservation and forecast carbon emissions, and could …

… city-level carbon emissions by using multi-dimensional data and machine learning, which can
… : (1) Machine-learning models were built to train carbon emission estimation models at the …

… machine-learning (ML) algorithms in predicting China’s building-related carbon emissions.
… parameters influencing building-related CO 2 emissions: urbanisation, R&D, population size, …

… to predict CO 2 emissions in China. Among these methods, machine learning algorithms
have … potential influencing factors and predicting carbon emissions. Linear regression models …

… monitor equivalent carbon emissions in this paper we introduced the eco2AI tool. The eco2AI
is an open-source library capable of tracking equivalent carbon emissions while training or …

… COVID-19 using seven different machine learning methods and proposed implications for …
machine learning method was more robust towards forecasting accuracy for carbon emission …

… methodology to predict carbon dioxide emissions based on … the clustering, prediction
machine learning techniques, and … map to predict carbon dioxide emissions considering a set of …

… and prediction of carbon emissions due to … of machine learning applied to carbon emission
prediction is studied in detail by means of paper retrieval. It was found that machine learning …