Search alternatives:
learning algorithm » learning algorithms (Expand Search)
robust algorithm » mould algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
data learning » deep learning (Expand Search)
develop » developed (Expand Search)
learning algorithm » learning algorithms (Expand Search)
robust algorithm » mould algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
data learning » deep learning (Expand Search)
develop » developed (Expand Search)
-
41
-
42
Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning
Published 2024Get full text
doctoralThesis -
43
-
44
-
45
Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
Get full text
article -
46
Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data
Published 2024“…The Experience API (xAPI) provides a comprehensive mechanism to document all types of learning interactions, storing this stream of data into the Learning Record Store (LRS). …”
Get full text
-
47
Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
Get full text
-
48
-
49
A Fast and Robust Gas Recognition Algorithm Based on Hybrid Convolutional and Recurrent Neural Network
Published 2019“…Featuring the capability of learning the correlations of time-series data, the proposed deep learning method is well-suited for extracting the valuable transient feature contained in the very beginning of the response curve. …”
-
50
The effects of data balancing approaches: A case study
Published 2023“…<p dir="ltr">Imbalanced datasets affect the performance of machine learning algorithms adversely. To cope with this problem, several resampling methods have been developed recently. …”
-
51
-
52
-
53
The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…However, the integration of quantum computing and machine learning poses several challenges. One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …”
-
54
Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…<p>Machine learning algorithms have been intensively applied to perform load forecasting to obtain better accuracies as compared to traditional statistical methods. …”
-
55
-
56
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Published 2021“…Machine learning (ML) algorithms are thus providing the necessary tools to augment the capabilities of SHM systems and provide intelligent solutions for the challenges of the past. …”
Get full text
article -
57
Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
Get full text
Get full text
-
58
-
59
-
60