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Machine Learning-Driven Site Selection for Wind Farms in Poland

https://doi.org/10.2139/ssrn.5255229
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Multicriteria decision making in energy planning using a modified fuzzy TOPSIS methodology
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Forest bat activity declines with increasing wind speed in proximity of operating wind turbines
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Investigation of the importance of criteria in potential wind farm sites via machine learning algorithms
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A GIS-based multi-criteria evaluation for wind farm site selection. A regional scale application in Greece
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Developing and applying a GIS-assisted approach to locating wind farms in the UK
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Forecasting for Wind Farm Energy Output in South Australia: A Comparative Analysis of Physical Methods and Deep Learning Methods
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Response to noise from modern wind farms in The Netherlands
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The meaning and use of the area under a receiver operating characteristic (ROC) curve.
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A Coefficient of Agreement for Nominal Scales
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Wind speed prediction for site selection and reliable operation of wind power plants in coastal regions using machine learning algorithm variants
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A framework for studying the effects of offshore wind energy development on birds and bats in the Eastern United States
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A Heuristic Approach to Siting and Design Optimization of an Onshore Wind Farm Layout
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Energy and Acoustic Environmental Effective Approach for a Wind Farm Location
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A Review: Existing Methods for Solving Spatial Planning Problems for Wind Turbines in Poland
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Site Selection of Wind Farms in Poland: Combining Theory with Reality
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Legal Conditions for Investments in Renewable Energy in the Overburden Disposal Areas in Poland
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VISUAL IMPACT ASSESSMENT OF WIND TURBINES AND THEIR FARMS ON LANDSCAPE OF KRETINGA REGION (LITHUANIA) AND GROBINA TOWNSCAPE (LATVIA)
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Estimating hub-height wind speed based on a machine learning algorithm: implications for wind energy assessment
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GIS-based method for wind farm location multi-criteria analysis
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