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Showing 1 - 20 results of 20 for search '(( data selection algorithm ) OR ( data collection algorithm ))~', query time: 0.09s Refine Results
  1. 1
    Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms

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

    Published 2022
    “…The outcomes revealed that these ML algorithms can be useful in predicting ground losses during wild blueberry harvesting in the selected fields.…”
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  2. 2
    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

    Published 2025
    “…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …”
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  3. 3
    Sentiment Mining of Arabic Twitter Data

    Sentiment Mining of Arabic Twitter Data by Ahmed, Soha Galalaldin Khider

    Published 2014
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  4. 4
    Particle swarm optimization algorithm: review and applications

    Particle swarm optimization algorithm: review and applications by Abualigah, Laith

    Published 2024
    “…The main procedure of the PSO algorithm is presented. Future researchers can use the collected data in this survey as baseline information on the PSO and PSO's applications.…”
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  5. 5
    A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm

    A Hybrid Approach for Predicting Critical Machining Conditions in Titanium Alloy Slot Milling Using Feature Selection and Binary Whale Optimization Algorithm by Amirsajjad Rahmani (17541453)

    Published 2023
    “…The SVM hyperparameters were optimized simultaneously with feature selection, and the model was tested with test data. …”
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  6. 6
    NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY

    NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

    Published 2022
    “…This study's dataset was sourced from the Kaggle machine learning repository, and it refers to data gathering from wearable IoT devices. The experimental outcomes demonstrate the proposed MCFS, NCA, and NSCP algorithms work more effectively than previous feature selection, clustering and classification algorithms, respectively, in terms of accuracy, sensitivity, specificity, precision, recall, f-measure and execution time. …”
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  7. 7
    UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks

    UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

    Published 2018
    “…Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of Unmanned Aerial Vehicles (UAVs) to collect data in dense wireless sensor networks (WSNs) using projection-based Compressive Data Gathering (CDG) as a novel solution methodology. …”
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  8. 8
    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data

    Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data by Arfan Ahmed (17541309)

    Published 2023
    “…Our experimental design included Data Collection, Feature Engineering, ML model selection/development, and reporting evaluation of metrics.…”
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  9. 9
    On sensor selection in mobile devices based on energy, application accuracy, and context metrics

    On sensor selection in mobile devices based on energy, application accuracy, and context metrics by Taleb, Sireen

    Published 2013
    “…Continuously collecting sensor data on mobile devices helps in capturing important contextual information related to the user location, activity, and surrounding environment. …”
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  10. 10
    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach

    EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach by Muhammad Adeel Asghar (6724982)

    Published 2019
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  11. 11
    An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation

    An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation by Abdul Rahman, Sawsan

    Published 2019
    “…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …”
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  12. 12
    An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM

    An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM by Al-Naffouri, T.Y.

    Published 0000
    “…The algorithm makes a collective use of the data and channel constraints inherent in the communication problem. …”
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  13. 13
    Uplink Noma in UAV-Assisted IoT Networks

    Uplink Noma in UAV-Assisted IoT Networks by Mrad, Ali

    Published 2022
    “…The first part of the thesis considers the problem of data collection from time-constrained IoT devices through deploying a UAV with uplink NOMA. …”
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  14. 14
    Video features with impact on user quality of experience

    Video features with impact on user quality of experience by Abbas, Nadine

    Published 2021
    “…We conduct experimental measurements and record videos with different frame rate, video resolution, transmission data rate, packet loss, delay and codec types. After collecting the QoE assessments, the supervised training data set is developed and imported into Rapid-Miner data mining tool. …”
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  15. 15
    Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test

    Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

    Published 2019
    “…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …”
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  16. 16
    A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass

    A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

    Published 2025
    “…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”
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  17. 17
    A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network

    A Digital DNA Sequencing Engine for Ransomware Analysis using a Machine Learning Network by KHAN, FIROZ

    Published 2020
    “…In the first phase, data preprocessing and feature selection technique is applied to the collected dataset. …”
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  18. 18
    Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying

    Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying by Tekli, Joe

    Published 2023
    “…We use a semantic-aware inverted index to allow semantic-aware search, result selection, and result ranking functionality. The semantically augmented XML data tree is processed for structural node clustering, based on semantic query concepts (i.e., key-concepts), in order to identify and rank candidate answer sub-trees containing related occurrences of query key-concepts. …”
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  19. 19
    Machine Learning Model for a Sustainable Drilling Process

    Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

    Published 2023
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  20. 20
    A Machine Learning Approach to Predicting Diabetes Complications

    A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

    Published 2021
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