Data in the experiment.

Data in the experiment.

<div><p>This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neur...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Montaser Abdelsattar (20606102) (author)
مؤلفون آخرون: Mohamed A. Ismeil (19066118) (author), Karim Menoufi (20606105) (author), Ahmed AbdelMoety (20606108) (author), Ahmed Emad-Eldeen (20606111) (author)
منشور في: 2025
الموضوعات:
Science Policy
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
mean absolute error
including feature scaling
convolutional neural network
comprehensive comparative analysis
artificial neural network
advanced computational approaches
study &# 8217
power output based
enhancing data consistency
predicting wind turbine
improved model performance
evaluating machine learning
following ml models
deep learning models
among dl models
best ml models
machine learning
deep learning
study presents
multivariate data
dl models
best performance
assessed based
wind speed
wind direction
xlink ">
xgboost ),
term memory
rnn ),
results show
previous benchmarks
preprocessing techniques
parameter tuning
optimizing hyperparameters
novelty lies
modeling non
mae ),
linear regression
linear dependencies
lightgbm ).
et achieved
environmental variables
dl algorithms
diverse range
directly comparing
cnn ),
000 observations
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