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Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
The integration of large-scale wind power introduces issues in modern power systems
operations due to its strong randomness and volatility. These issues can be resolved via …
operations due to its strong randomness and volatility. These issues can be resolved via …
[HTML][HTML] An overview of performance evaluation metrics for short-term statistical wind power forecasting
Wind power forecasting has become an essential tool for energy trading and the operation
of the grid due to the increasing importance of wind energy. Therefore, estimating the …
of the grid due to the increasing importance of wind energy. Therefore, estimating the …
Predictions of steel price indices through machine learning for the regional northeast Chinese market
B **, X Xu - Neural Computing and Applications, 2024 - Springer
Projections of commodity prices have long been a significant source of dependence for
investors and the government. This study investigates the challenging topic of forecasting …
investors and the government. This study investigates the challenging topic of forecasting …
Machine learning predictions of regional steel price indices for east China
B **, X Xu - Ironmaking & Steelmaking, 2024 - journals.sagepub.com
From 1 January 2010 to 15 April 2021, this study examines the challenging task of daily
regional steel price index forecasting in the east Chinese market. We train our models using …
regional steel price index forecasting in the east Chinese market. We train our models using …
Forecast methods for time series data: A survey
Z Liu, Z Zhu, J Gao, C Xu - Ieee Access, 2021 - ieeexplore.ieee.org
Research on forecasting methods of time series data has become one of the hot spots. More
and more time series data are produced in various fields. It provides data for the research of …
and more time series data are produced in various fields. It provides data for the research of …
Deep learning based ensemble approach for probabilistic wind power forecasting
Due to the economic and environmental benefits, wind power is becoming one of the more
promising supplements for electric power generation. However, the uncertainty exhibited in …
promising supplements for electric power generation. However, the uncertainty exhibited in …
Forecasts of thermal coal prices through gaussian process regressions
B **, X Xu - Ironmaking & Steelmaking, 2024 - journals.sagepub.com
Given thermal coal's significance as a tactical energy source, price projections for the
commodity are crucial for investors and decision-makers alike. The goal of the current work …
commodity are crucial for investors and decision-makers alike. The goal of the current work …
Palladium price predictions via machine learning
B **, X Xu - Materials Circular Economy, 2024 - Springer
Predictions of prices for a wide variety of commodities have been relied upon by
governments and investors over the course of history. The purpose of this study is to …
governments and investors over the course of history. The purpose of this study is to …
Learning based short term wind speed forecasting models for smart grid applications: An extensive review and case study
This paper provides an extensive review of learning-based short-term forecasting models for
smart grid applications. In addition to this, the paper also explores forecasting models …
smart grid applications. In addition to this, the paper also explores forecasting models …
Machine learning price index forecasts of flat steel products
B **, X Xu - Mineral Economics, 2024 - Springer
Investors and authorities have always placed a high emphasis on commodity price
forecasting. In this study, the issue of daily price index forecasting for flat steel products on …
forecasting. In this study, the issue of daily price index forecasting for flat steel products on …