SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms
7 references·16 citing·48 second hop
Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms (2021)Forecasting of transportation-related ene…Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China (2020)Moving towards a sustainable …Carbon emission efficiency and spatial clustering analyses in China’s thermal power industry: Evidence from the provincial level (2017)Carbon emission efficiency an…A new metric of absolute percentage error for intermittent demand forecasts (2016)A new metric of absolute perc…Deep learning applications and challenges in big data analytics (2015)Deep learning applications an…A Bayesian regularized artificial neural network for stock market forecasting (2013)A Bayesian regularized artifi…Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model (2012)Forecasting of CO2 emissions,…Climate change 2007 - mitigation of climate change (2007)Climate change 2007 - mitigat…Machine learning in supply chain management: systematic literature review and future research agenda (2025)Machine learning in supply ch…An examination of daily CO2 emissions prediction through a comparative analysis of machine learning, deep learning, and statistical models (2025)An examination of daily CO2 e…Hybrid framework combining grey system model with Gaussian process and STL for CO 2 emissions forecasting in developed countries (2024)Hybrid framework combining gr…Forecasting Chinese provincial CO2 emissions: A universal and robust new-information-based grey model (2023)Forecasting Chinese provincia…Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector (2023)Forecast energy demand, CO2 e…An interpretable multi-stage forecasting framework for energy consumption and CO2 emissions for the transportation sector (2023)An interpretable multi-stage …Accurate forecasts and comparative analysis of Chinese CO2 emissions using a superior time-delay grey model (2023)Accurate forecasts and compar…Sustainable AI and Intergenerational Justice (2022)Sustainable AI and Intergener…Predicting CO2 Emission Footprint Using AI through Machine Learning (2022)Predicting CO2 Emission Footp…Machine learning-based time series models for effective CO2 emission prediction in India (2022)Machine learning-based time s…Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms (2022)Forecasting of future greenho…Estimating energy-related CO2 emissions using a novel multivariable fuzzy grey model with time-delay and interaction effect characteristics (2022)Estimating energy-related CO2…Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model (2022)Energy demand forecasting in …Demand forecasting based machine learning algorithms on customer information: an applied approach (2022)Demand forecasting based mach…An interpretable forecasting framework for energy consumption and CO2 emissions (2022)An interpretable forecasting …A Hybrid Model with Applying Machine Learning Algorithms and Optimization Model to Forecast Greenhouse Gas Emissions with Energy Market Data (2022)A Hybrid Model with Applying …Time Series Analysis: Forecasting and Control (1977)Statistical analysis of cointegration vectors (1988)Testing for a Unit Root in Time Series Regression (1988)How industrialization and urbanization process impacts on CO 2 emissions in China: Evidence from nonparametric additive regression models (2015)The investigation of environmental Kuznets curve hypothesis in the advanced economies: The role of energy prices (2015)Investigating the EKC hypothesis for China: the role of economic complexity on ecological footprint (2020)Financial time series forecasting using support vector machines (2003)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)A feature weighted support vector machine and K-nearest neighbor algorithm for stock market indices prediction (2017)Natural language based financial forecasting: a survey (2017)Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)Forecasting methods and applications (1993)Another look at measures of forecast accuracy (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Development of regression models to forecast the CO2 emissions from fossil fuels in the BRICS and MINT countries (2022)Forecast evaluation for data scientists: common pitfalls and best practices (2022)Measuring the efficiency of decision making units (1978)Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis (1984)Local Indicators of Spatial Association—LISA (1995)Regional disparity, spatial spillover effects of urbanisation and carbon emissions in China (2019)Does China's low-carbon city pilot intervention limit electricity consumption? An analysis of industrial energy efficiency using time-varying DID model (2023)Promoting or inhibiting? New-type urbanization and urban carbon emissions efficiency in China (2023)Statistical inference in vector autoregressions with possibly integrated processes (1995)Bounds testing approaches to the analysis of level relationships (2001)The Next Generation of the Penn World Table (2015)Investigating the EKC hypothesis with renewable energy consumption, human capital, globalization and trade openness for China: Evidence from augmented ARDL approach with a structural break (2020)The dynamic impact of natural resources, technological innovations and economic growth on ecological footprint: An advanced panel data estimation (2020)The linkages between natural resources, human capital, globalization, economic growth, financial development, and ecological footprint: The moderating role of technological innovations (2022)Investigations on the Theory of the Brownian Movement (1956)Global mismatch between greenhouse gas emissions and the burden of climate change (2016)RETRACTED: Net zero supply chain performance and industry 4.0 technologies: Past review and present introspective analysis for future research directions (2023)An Empirical Comparison of Machine Learning Models for Time Series Forecasting (2010)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Machine learning advances for time series forecasting (2021)Energy consumption, carbon dioxide emissions and economic growth: The case of Saudi Arabia (2014)Public-private partnerships investment in energy as new determinant of CO2 emissions: The role of technological innovations in China (2020)The impact of climate policy uncertainty on renewable and non-renewable energy demand in the United States (2022)Impact of the introduction of marketplace channel on e‐tailer's logistics service strategy (2023)Industrial carbon emission forecasting considering external factors based on linear and machine learning models (2023)China's future energy vision: Multi-scenario simulation based on energy consumption structure under dual carbon targets (2024)Why We Disagree about Climate Change (2009)The trouble with negative emissions (2016)Natural climate solutions (2017)Big Data technologies: A survey (2017)Machine learning on big data: Opportunities and challenges (2017)Machine Learning With Big Data: Challenges and Approaches (2017)
this work references cited by second hop

References

  • 2007Climate change 2007 - mitigation of climate change3,485 cited
  • 2015Deep learning applications and challenges in big data analytics2,597 cited
  • 2020Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China1,192 cited
  • 2016A new metric of absolute percentage error for intermittent demand forecasts1,150 cited
  • 2013A Bayesian regularized artificial neural network for stock market forecasting517 cited
  • 2012Forecasting of CO2 emissions, energy consumption and economic growth in China using an improved grey model361 cited
  • 2017Carbon emission efficiency and spatial clustering analyses in China’s thermal power industry: Evidence from the provincial level201 cited

Cited by

  • 2022Machine learning-based time series models for effective CO2 emission prediction in India206 cited
  • 2022Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms165 cited
  • 2022Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model147 cited
  • 2023Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector117 cited
  • 2022A Hybrid Model with Applying Machine Learning Algorithms and Optimization Model to Forecast Greenhouse Gas Emissions with Energy Market Data85 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

2022
Predicting CO2 Emission Footprint Using AI through Machine Learning
84 cited
  • 2022An interpretable forecasting framework for energy consumption and CO2 emissions80 cited
  • 2023An interpretable multi-stage forecasting framework for energy consumption and CO2 emissions for the transportation sector78 cited
  • 2022Demand forecasting based machine learning algorithms on customer information: an applied approach73 cited
  • 2025An examination of daily CO2 emissions prediction through a comparative analysis of machine learning, deep learning, and statistical models73 cited
  • 2023Forecasting Chinese provincial CO2 emissions: A universal and robust new-information-based grey model72 cited
  • 2024Hybrid framework combining grey system model with Gaussian process and STL for CO 2 emissions forecasting in developed countries57 cited
  • 2022Estimating energy-related CO2 emissions using a novel multivariable fuzzy grey model with time-delay and interaction effect characteristics54 cited
  • 2023Accurate forecasts and comparative analysis of Chinese CO2 emissions using a superior time-delay grey model50 cited
  • 2025Machine learning in supply chain management: systematic literature review and future research agenda40 cited
  • 2022Sustainable AI and Intergenerational Justice31 cited