Prediction of daily global solar radiation using different machine learning algorithms: Evaluation and comparison

Ü Ağbulut, AE Gürel, Y Biçen - Renewable and Sustainable Energy …, 2021 - Elsevier
The prediction of global solar radiation for the regions is of great importance in terms of
giving directions of solar energy conversion systems (design, modeling, and operation) …

Machine learning models to quantify and map daily global solar radiation and photovoltaic power

Y Feng, W Hao, H Li, N Cui, D Gong, L Gao - Renewable and Sustainable …, 2020 - Elsevier
Global solar radiation (R s) reaching Earth's surface is the primary information for the design
and application of solar energy-related systems. High-resolution R s measurements are …

Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms

H Bakır, Ü Ağbulut, AE Gürel, G Yıldız, U Güvenç… - Journal of Cleaner …, 2022 - Elsevier
The accelerating increment of greenhouse gas (GHG) concentration in the atmosphere
already reached an alarming level, and nowadays its adverse impacts on the living …

Forecasting of transportation-related energy demand and CO2 emissions in Turkey with different machine learning algorithms

Ü Ağbulut - Sustainable Production and Consumption, 2022 - Elsevier
Adverse impacts of the transportation sector on not only air quality but also economic growth
of a country are nowadays well-noticed, particularly by develo** countries. Today, the …

Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms

MS Bakay, Ü Ağbulut - Journal of Cleaner Production, 2021 - Elsevier
Today, the world's primary energy demand has been met by the burning of fossil-based fuels
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …

Evaluation of CatBoost method for prediction of reference evapotranspiration in humid regions

G Huang, L Wu, X Ma, W Zhang, J Fan, X Yu, W Zeng… - Journal of …, 2019 - Elsevier
Accurate estimation of reference evapotranspiration (ET 0) is critical for water resource
management and irrigation scheduling. This study evaluated the potential of a new machine …

Extreme gradient boosting and deep neural network based ensemble learning approach to forecast hourly solar irradiance

P Kumari, D Toshniwal - Journal of Cleaner Production, 2021 - Elsevier
Prediction of solar irradiance is an essential requirement for reliable planning and efficient
designing of solar energy systems. Thus, in present work, a new ensemble model, which …

Light Gradient Boosting Machine: An efficient soft computing model for estimating daily reference evapotranspiration with local and external meteorological data

J Fan, X Ma, L Wu, F Zhang, X Yu, W Zeng - Agricultural water management, 2019 - Elsevier
Accurate estimation of reference evapotranspiration (ETo) is required in many fields, eg
irrigation scheduling design, agricultural water management, crop growth modeling and …

A novel fractional time delayed grey model with Grey Wolf Optimizer and its applications in forecasting the natural gas and coal consumption in Chongqing China

X Ma, X Mei, W Wu, X Wu, B Zeng - Energy, 2019 - Elsevier
Introduction of the fractional order accumulation has made significant contributions to the
development of forecasting methods, and fractional grey models play a key role in such new …

Carbon-dioxide mitigation in the residential building sector: a household scale-based assessment

M Ma, X Ma, W Cai, W Cai - Energy Conversion and Management, 2019 - Elsevier
Carbon-dioxide mitigation in residential building sector (CMRBS) has become critical for
China in achieving its emission mitigation goal in the “Post Paris” period with the growing …