Phys.org22d
Harvest smarter, not harder: Machine learning meets tomato farming
used a handheld hyperspectral camera to collect data from 567 tomato fruits across five cultivars. Machine learning algorithms, including Random Forest and Artificial Neural Networks, were ...
Frontiers17d
Fruit size prediction of tomato cultivars using machine learning algorithms
We aimed to develop a method for early prediction of tomato fruit size at harvest with machine learning algorithm, and three machine learning models (Ridge Regression, Extra Tree Regrreion, CatBoost ...
IEEE26d
Diagnosis of Demagnetization Faults in PMSGs Based on Performance Evaluation of Machine Learning Algorithms Through Flux and Current Signals
Abstract: This study proposed an effective machine learning (ML)-based fault diagnosis method for ... transform (DWT), assessing their accuracy using ensemble, SVM, and KNN algorithms. In addition, we ...
IEEE8d
Prediction of False Data Injection Attacks in Smart Grid using AdaBoost, Deep Learning, and KNN
In this work, we are finding a better machine learning algorithm to predict false data injection attacks in smart Grid. We have taken the Smart Grid dataset from Kaggle. In our research, we used ...