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 …
Feature selection in machine learning prediction systems for renewable energy applications
This paper focuses on feature selection problems that arise in renewable energy
applications. Feature selection is an important problem in machine learning, both in …
applications. Feature selection is an important problem in machine learning, both in …
A review of applications of artificial intelligent algorithms in wind farms
Wind farms are enormous and complex control systems. It is challenging and valuable to
control and optimize wind farms. Their applications are widely used in various industries …
control and optimize wind farms. Their applications are widely used in various industries …
Artificial intelligence based hybrid forecasting approaches for wind power generation: Progress, challenges and prospects
Globally, wind energy is growing rapidly and has received huge consideration to fulfill global
energy requirements. An accurate wind power forecasting is crucial to achieve a stable and …
energy requirements. An accurate wind power forecasting is crucial to achieve a stable and …
Hybrid binary coral reefs optimization algorithm with simulated annealing for feature selection in high-dimensional biomedical datasets
C Yan, J Ma, H Luo, A Patel - Chemometrics and Intelligent Laboratory …, 2019 - Elsevier
The last decades have witnessed accumulation in biomedical data. Though they can be
analyzed to enhance assessment of at-risk patients and improve the diagnosis, a major …
analyzed to enhance assessment of at-risk patients and improve the diagnosis, a major …
An overview of deterministic and probabilistic forecasting methods of wind energy
In recent years, a variety of wind forecasting models have been developed, prompting
necessity to review the abundant methods to gain insights of the state-of-the-art …
necessity to review the abundant methods to gain insights of the state-of-the-art …
New wind speed forecasting approaches using fast ensemble empirical model decomposition, genetic algorithm, Mind Evolutionary Algorithm and Artificial Neural …
H Liu, H Tian, X Liang, Y Li - Renewable Energy, 2015 - Elsevier
Wind speed high-precision prediction is one of the most important technical aspects to
protect the safety of wind power utilization. In this study, two new hybrid methods [FEEMD …
protect the safety of wind power utilization. In this study, two new hybrid methods [FEEMD …
Large-scale combined heat and power economic dispatch using a novel multi-player harmony search method
Combined heat and power (CHP) plants have the capability of supplying power and heat
energy altogether. The major aim of CHP economic dispatch (CHPED) is determining …
energy altogether. The major aim of CHP economic dispatch (CHPED) is determining …
A novel forecasting model based on a hybrid processing strategy and an optimized local linear fuzzy neural network to make wind power forecasting: A case study of …
As a crucial issue in the wind power industry, it is a tough and challenging task to predict the
wind power accurately because of its nonlinearity, non-stationary and chaos. In this paper …
wind power accurately because of its nonlinearity, non-stationary and chaos. In this paper …
Multi-task learning for the prediction of wind power ramp events with deep neural networks
Abstract In Machine Learning, the most common way to address a given problem is to
optimize an error measure by training a single model to solve the desired task. However …
optimize an error measure by training a single model to solve the desired task. However …