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processing algorithm » processing algorithms (Expand Search)
testing algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
data testing » data using (Expand Search)
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161
A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation
Published 2023“…Due to the lack of public frameworks, we create a dataset that emulates real-life scenarios to train and test the neural network. Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …”
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masterThesis -
162
A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …”
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163
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164
Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…Moreover, the paper conducted a comparative study of the readily available algorithms for occupancy detection to determine the optimal method in regards to training time and testing accuracy. …”
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165
An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study
Published 2024“…It was tested using historical data, and the next step will to involve usability testing with end users.…”
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166
Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”
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167
Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 2024“…The proposed algorithm is evaluated on the 68-bus system and the Northeastern United States 25k-bus synthetic test system with credible contingencies using the PowerWorld simulator. …”
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Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks
Published 2023“…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …”
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170
An Artificial Intelligence Approach for Predictive Maintenance in Electronic Toll Collection System
Published 2019“…Historical data of Dubai Toll Collection System is utilized to investigate multiple machine learning algorithms. …”
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171
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173
Using machine learning for disease detection. (c2013)
Published 2016“…Classification has three main components: the classification algorithm, the pre-classified data (training data) and the un-classified data (testing data). …”
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174
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175
Recursive Parameter Identification Of A Class Of Nonlinear Systems From Noisy Measurements
Published 2020“…The model structure is made up of two linear dynamic elements separated by a nonlinear static one. The nonlinear element is assumed to be of the polynomial type with known order; The identification is based on input/output data where the output is contaminated with measurement noise. …”
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176
A geometric-primitives-based compression scheme for testingsystems-on-a-chip
Published 2001“…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data…”
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177
A novel few shot learning derived architecture for long-term HbA1c prediction
Published 2024“…Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …”
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178
Applications of fast fourier transform in the integrity evaluation of deep foundations
Published 2016“…The method is developed and validated using experimental data, and is based on applying the fast Fourier transform mapping algorithm on data obtained from cross-hole sonic logging. …”
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Lung nodule classification utilizing support vector machines
Published 2002“…The SVM classifier is trained with features extracted from 30 nodule images and 20 non-nodule images, and is tested with features out of 16 nodule/non-nodule images. …”
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