Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms حسب Humna Khan (17541972)

"…When comparing the actual and anticipated ground loss, the SVR performed best (R² = 0.79–0.93) as compared to the other two algorithms i.e., LR (R² = 0.73 to 0.92), and RF (R² = 0.53 to 0.89) for the three fields. …"

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب Usman Ali (6586886)

"…Extracted vegetation indices were evaluated on three ML algorithms, namely, random forest (RF), k-nearest neighbour (K-NN), and k dimensional-tree (KD-Tree). …"

A novel hybrid methodology for fault diagnosis of wind energy conversion systems حسب Khaled Dhibi (16891524)

"…Therefore, a hybrid feature selection based diagnosis technique, that can preserve the advantages of wrapper and filter algorithms as well as RF model, is proposed. In the first phase, the neighborhood component analysis (NCA) filter algorithm is used to reduce and select only the pertinent features from the original raw data. …"

Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain حسب Farshad Rahimi Ghashghaei (20880995)

"…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. This research aims to use the complementary strengths of DQN and PPO algorithms to develop robust and adaptive control policies for noisy and uncertain quantum systems. …"

Sentiment Analysis of the Emirati Dialect text using Ensemble Stacking Deep Learning Models حسب AL SHAMSI, ARWA AHMED

"…For the basic machine learning algorithms, LR, NB, SVM, RF, DT, MLP, AdaBoost, GBoost, and an ensemble model of machine learning classifiers were used. …"
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