[HTML][HTML] Ocean wave energy converters: Status and challenges
T Aderinto, H Li - Energies, 2018 - mdpi.com
Wave energy is substantial as a resource, and its potential to significantly contribute to the
existing energy mix has been identified. However, the commercial utilization of wave energy …
existing energy mix has been identified. However, the commercial utilization of wave energy …
Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition
Data-intelligent algorithms designed for forecasting significant height of coastal waves over
the relatively short time period in coastal zones can generate crucial information about …
the relatively short time period in coastal zones can generate crucial information about …
Dynamic ensemble deep echo state network for significant wave height forecasting
Forecasts of the wave heights can assist in the data-driven control of wave energy systems.
However, the dynamic properties and extreme fluctuations of the historical observations …
However, the dynamic properties and extreme fluctuations of the historical observations …
Wave height predictions in complex sea flows through soft-computing models: Case study of Persian Gulf
The present study case examined the capability of Artificial Neural Network (ANN), Adaptive
Neuro-Fuzzy Inference System (ANFIS), M5P, and Random Forest (RF) soft-computing …
Neuro-Fuzzy Inference System (ANFIS), M5P, and Random Forest (RF) soft-computing …
A two-layer feature selection method using genetic algorithm and elastic net
F Amini, G Hu - Expert Systems with Applications, 2021 - Elsevier
Feature selection, as a critical pre-processing step for machine learning, aims at determining
representative predictors from a high-dimensional feature space dataset to improve the …
representative predictors from a high-dimensional feature space dataset to improve the …
[HTML][HTML] A data-driven long-term metocean data forecasting approach for the design of marine renewable energy systems
Abstract The potential of Marine Renewable Energy (MRE) systems is usually evaluated
based on recent metocean data and assuming the stationarity of the MRE resource. Yet …
based on recent metocean data and assuming the stationarity of the MRE resource. Yet …
A novel hybrid model based on STL decomposition and one-dimensional convolutional neural networks with positional encoding for significant wave height forecast
S Yang, Z Deng, X Li, C Zheng, L Xi, J Zhuang… - Renewable Energy, 2021 - Elsevier
Reducing the dependence on fossil fuels and utilizing the renewable energy have become
essential due to the global resource exhaustion and unfriendly environmental impact from …
essential due to the global resource exhaustion and unfriendly environmental impact from …
Research on the driving factors and carbon emission reduction pathways of China's iron and steel industry under the vision of carbon neutrality
W Li, S Zhang, C Lu - Journal of Cleaner Production, 2022 - Elsevier
Under the vision of carbon neutrality, China's iron and steel industry (CISI) urgently needs to
achieve low-carbon development. To formulate effective and targeted emission reduction …
achieve low-carbon development. To formulate effective and targeted emission reduction …
A BP neural network model optimized by mind evolutionary algorithm for predicting the ocean wave heights
W Wang, R Tang, C Li, P Liu, L Luo - Ocean Engineering, 2018 - Elsevier
In the field of marine detection and warning, predicting the heights of ocean wave is a very
important project. In order to predict the ocean wave heights accurately and quickly, our …
important project. In order to predict the ocean wave heights accurately and quickly, our …
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 …