Wind Speed Predictability Accuracy with Height Using LiDAR Based Measurements and Artificial Neural Networks-Reference-Cited by-同舟云学术

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Wind Speed Predictability Accuracy with Height Using LiDAR Based Measurements and Artificial Neural Networks

Published:2021-05-06 Issue:8 Volume:35 Page:605-622
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Mohandes M.¹,Rehman S.²,Nuha H.³,Islam M.S.¹,Schulze F.H.⁴

Affiliation:

1. Department of Electrical Engineering, King Fahd University of Petroleum & Minerals, Dhahran-Saudi Arabia

2. Center for Engineering Research, Research Institute, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia

3. School of Computing, Telkom University, Bandung, Indonesia

4. Managing Director, CESI Middle East, UAE

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2021.1922850

Reference43 articles.

1. Short-term wind speed forecasting by spectral analysis from long-term observations with missing values

2. Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean

3. Stochastic generation of hourly mean wind speed data

4. The effect of diurnal profile and seasonal wind regime on sizing grid-connected and off-grid wind power plants

5. Short-term wind power forecasting in Portugal by neural networks and wavelet transform

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2. Monitoring and Prediction of Water Levels in Telkom University Techno Lake Based on the Internet of Things using the Linear Regression Approach;2023 International Conference on Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD);2023-11-13

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5. Methods and Applications of 3D Ground Crop Analysis Using LiDAR Technology: A Survey;Sensors;2023-08-16

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