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Showing 221 - 240 results of 722 for search '(( movement data algorithm ) OR ((( data using algorithm ) OR ( data learning algorithm ))))', query time: 0.16s Refine Results
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    Just-in-time defect prediction for mobile applications: using shallow or deep learning? by Raymon van Dinter (10521952)

    Published 2023
    “…In this research, we evaluate the performance of traditional machine learning algorithms and data sampling techniques for JITDP problems and compare the model performance with the performance of a DL-based prediction model. …”
  3. 223

    Investigating the Use of Machine Learning Models to Understand the Drugs Permeability Across Placenta by Vaisali Chandrasekar (16904526)

    Published 2023
    “…<p dir="ltr">Owing to limited drug testing possibilities in pregnant population, the development of computational algorithms is crucial to predict the fate of drugs in the placental barrier; it could serve as an alternative to animal testing. …”
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    Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms by Abdelouahed Hamdi (14158899)

    Published 2022
    “…There are different metrics for the calculation of the risk factor, among which the most important one is the Conditional Value at Risk (CVaR). On the other hand, Data Envelopment Analysis (DEA) can be used to form the optimal portfolio and evaluate its efficiency. …”
  6. 226

    Energy utilization assessment of a semi-closed greenhouse using data-driven model predictive control by Farhat Mahmood (15468854)

    Published 2021
    “…The proposed method consists of a multilayer perceptron model representing the greenhouse system integrated with an objective function and an optimization algorithm. The multilayer perceptron model is trained using historical data from the greenhouse with solar radiation, outside temperature, humidity difference, fan speed, HVAC control as the input parameters to predict the temperature. …”
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    From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors by Michael R. Giordano (9976173)

    Published 2021
    “…The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. …”
  9. 229

    Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study by Mutasim Baba, Fuad

    Published 2022
    “…It was found that the calibrated model achieved these metrics with RMSE of 0.3 ◦C, and MAD of 0.8 ◦C, and 85% of data points with an error less than 0.5 ◦C for a school building case.…”
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  10. 230

    Convergence of Photovoltaic Power Forecasting and Deep Learning: State-of-Art Review by Mohamed Massaoudi (16888710)

    Published 2021
    “…These technologies include federated learning, deep transfer learning, incremental learning, and big data DL. …”
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    Building power consumption datasets: Survey, taxonomy and future directions by Yassine Himeur (14158821)

    Published 2020
    “…Accordingly, a novel visualization strategy based on using power consumption micro-moments has been presented along with an example of deploying machine learning algorithms to classify the micro-moment classes and identify anomalous power usage.…”
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    Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

    Published 2025
    “…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …”
  19. 239

    Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE by SHWEDEH, FATEN

    Published 2018
    “…Classification is a Data Mining (DM) technique used for prediction. On the other hand, feature selection is the process of finding the best set of features that has the most impact on a specific target. …”
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