Application of four machine-learning methods to predict short-horizon wind energy
Renewable energy has garnered attention due to the need for sustainable energy sources.
Wind power has emerged as an alternative that has contributed to the transition towards …
Wind power has emerged as an alternative that has contributed to the transition towards …
[HTML][HTML] Intuitionistic fuzzy time series forecasting method based on dendrite neuron model and exponential smoothing
Methods based on artificial neural networks for intuitionistic fuzzy time series forecasting can
produce successful forecasting results. In the literature, exponential smoothing methods are …
produce successful forecasting results. In the literature, exponential smoothing methods are …
An innovative information accumulation multivariable grey model and its application in China's renewable energy generation forecasting
Y Ren, Y Wang, L Xia, D Wu - Expert Systems with Applications, 2024 - Elsevier
Reducing greenhouse gas emissions is urgent for the global community with rising climates.
Considering the importance of renewable energy in mitigating climate warming, forecasting …
Considering the importance of renewable energy in mitigating climate warming, forecasting …
Seasonal waste, geotherm, nuclear, wood net power generations forecasting using a novel hybrid grey model with seasonally buffered and time-varying effect
Seasonal volatility data is often disturbed by uncertain external shocks, making accurate
forecasting particularly strenuous. This paper proposes a progressive adaptive prediction …
forecasting particularly strenuous. This paper proposes a progressive adaptive prediction …
A new ensemble intuitionistic fuzzy-deep forecasting model: Consolidation of the IFRFs-bENR with LSTM
Among forecasting model families, the intuitionistic fuzzy-based forecasting model stands
out due to its comprehensive approach to uncertainty, considering possible degrees of …
out due to its comprehensive approach to uncertainty, considering possible degrees of …
An intelligent interval forecasting system based on fuzzy time series and error distribution characteristics for air quality index
H Yang, Y Gao, F Zhao, J Wang - Environmental Research, 2024 - Elsevier
Due to the emergency environment pollution problems, it is imperative to understand the air
quality and take effective measures for environmental governance. As a representative …
quality and take effective measures for environmental governance. As a representative …
Distance and similarity measures of Hesitant bi-fuzzy set and its applications in renewable energy systems
The concept of Hesitant bi-fuzzy set (HBFS) is an extension of dual hesitant fuzzy set, which
play an important role in minimizing uncertainty in an efficient way. Distance and Similarity …
play an important role in minimizing uncertainty in an efficient way. Distance and Similarity …
[HTML][HTML] Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer
Time series forecasting is crucial across various sectors, aiding stakeholders in making
informed decisions, planning for the short and long term, managing risks, optimizing profits …
informed decisions, planning for the short and long term, managing risks, optimizing profits …
Combination of Metaheuristic Algorithm and Artificial Neural Networks Model to Forecast Wind Energy
The transition to renewable energies, in particular wind power, is essential to meeting
environmental challenges and ensuring a sustainable future. Precise estimation of wind …
environmental challenges and ensuring a sustainable future. Precise estimation of wind …
Ratio Interval-Frequency Density with Modifications to the Weighted Fuzzy Time Series
E Vianita - JTAM (Jurnal Teori dan Aplikasi Matematika), 2024 - journal.ummat.ac.id
The improvement of plantation forecasting accuracy, particularly with regard to coffee
production, was an essential aspect of earth observations for the purpose of informing …
production, was an essential aspect of earth observations for the purpose of informing …