Search Results - Computing methodologies Machine learning Machine learning approaches Bio-inspired approaches

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  1. 1

    Hybridizing extreme learning machine and bio-inspired computing approaches for improved stock market forecasting by Gocken, Mustafa, Boru, Asli, Dosdogru, Ayse Tugba, Ozcalici, Mehmet

    Published: IEEE 01.09.2017
    “… In this context, bio-inspired computing approaches including evolutionary computation and swarm intelligence can be used to make more accurate calculations and forecasting results…”
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    Conference Proceeding
  2. 2

    Improved bio-inspired with machine learning computing approach for thyroid prediction by Kesavulu, Divya, R, Kannadasan

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 02.07.2025
    Published in Scientific reports (02.07.2025)
    “…-being. This study investigates the use of several machine learning (ML) and deep learning (DL) methods, such as random forest (RF…”
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    Journal Article
  3. 3
  4. 4

    Bio-inspired computing and Machine learning analytics for a future-oriented mental well-being by Chakraborty, Chinmay, Unhelkar, Bhuvan, Mahmoudi, Saïd

    ISSN: 2472-6303, 2472-6311, 2472-6311
    Published: United States Elsevier Inc 01.08.2025
    Published in SLAS technology (01.08.2025)
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    Journal Article
  5. 5

    Bio-inspired computing and Machine learning analytics for future-oriented mental well-being by Chakraborty, Chinmay, Unhelkar, Bhuvan, Mahmoudi, Saïd

    ISSN: 2472-6303, 2472-6311
    Published: United States Elsevier Inc 01.10.2025
    Published in SLAS technology (01.10.2025)
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    Journal Article
  6. 6

    Bio-inspired EEG signal computing using machine learning and fuzzy theory for decision making in future-oriented brain-controlled vehicles by Byeon, Haewon, Quraishi, Aadam, Khalaf, Mohammed I., MP, Sunil, Khan, Ihtiram Raza, Dutta, Ashit Kumar, Dasari, Rakeshnag, Yellu, Ramswaroop Reddy, Reegu, Faheem Ahmad, Bhatt, Mohammed Wasim

    ISSN: 2472-6303, 2472-6311, 2472-6311
    Published: United States Elsevier Inc 01.10.2024
    Published in SLAS technology (01.10.2024)
    “…One kind of autonomous vehicle that can take instructions from the driver by reading their electroencephalogram (EEG) signals using a Brain-Computer Interface…”
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    Journal Article
  7. 7

    Efficient Handoff Detection for Computation Offloading using Machine Learning and Bio-Inspired Optimization Techniques in Mobile Edge Computing by Joshi, Vaishali, Patil, Kishor

    ISSN: 2473-5655
    Published: IEEE 06.04.2024
    “…With the rise of smartphones and the Internet of Things (IoT), more and more calculations are being performed on mobile devices, which rapidly depletes their…”
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    Conference Proceeding
  8. 8

    Bio-Inspired Machine Learning Approach to Type 2 Diabetes Detection by Al-Tawil, Marwan, Mahafzah, Basel A., Al Tawil, Arar, Aljarah, Ibrahim

    ISSN: 2073-8994, 2073-8994
    Published: Basel MDPI AG 01.03.2023
    Published in Symmetry (Basel) (01.03.2023)
    “… This can be accomplished by analyzing medical datasets using data mining and machine-learning techniques…”
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    Journal Article
  9. 9

    insideOut: A Bio-Inspired Machine Learning Approach to Estimating Posture in Robots Driven by Compliant Tendons by Hagen, Daniel A., Marjaninejad, Ali, Loeb, Gerald E., Valero-Cuevas, Francisco J.

    ISSN: 1662-5218, 1662-5218
    Published: Switzerland Frontiers Research Foundation 11.10.2021
    Published in Frontiers in neurorobotics (11.10.2021)
    “… Here we propose a novel machine learning algorithm to accurately estimate joint posture during dynamic tasks by limited training of an artificial neural network (ANN…”
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    Journal Article
  10. 10

    Learning from errors: A bio-inspired approach for hypothesis-based machine learning by Gamrad, Dennis, Soffker, Dirk

    ISBN: 4907764308, 9784907764302
    Published: IEEE 01.08.2008
    “…This contribution present an approach extending existing learning strategies based on Situation-Operator-Modeling (SOM…”
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    Conference Proceeding
  11. 11

    Prediction of EDMed micro-hole quality characteristics using hybrid bio-inspired machine learning-based predictive approaches by Rao, Thella Babu

    ISSN: 1955-2513, 1955-2505
    Published: Paris Springer Paris 01.04.2023
    “… In this investigation, predictive models based on bio-inspired intelligent hybrid machine learning algorithms are proposed for machining micro-holes with accurate dimensions on Inconel 718 superalloy by µEDM process…”
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    Journal Article
  12. 12

    A novel approach for human diseases prediction using nature inspired computing & machine learning approach by MunishKhanna, Singh, Law Kumar, Garg, Hitendra

    ISSN: 1573-7721, 1380-7501, 1573-7721
    Published: New York Springer US 01.02.2024
    Published in Multimedia tools and applications (01.02.2024)
    “…Globally, patients with diabetes, diabetic retinopathy, cancer, and heart disease are growing rapidly in developed and developing countries. As a result of…”
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    Journal Article
  13. 13

    Free vibration behaviour of bio-inspired helicoidal laminated composite panels of revolution under thermal conditions: Multi-output machine learning approach by Garg, Aman, Li, Li, Zheng, Weiguang, Belarbi, Mohamed-Ouejdi, Raman, Roshan

    ISSN: 0955-7997
    Published: Elsevier Ltd 15.12.2024
    “…The present work aims to study the free vibration behaviour of bio-inspired helicoidal laminated composite spherical, toroid, and conical shell panels using a single-output Support Vector Machine (SVM…”
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    Journal Article
  14. 14
  15. 15

    Nature-inspired computing and machine learning based classification approach for glaucoma in retinal fundus images by Singh, Law Kumar, Khanna, Munish, Thawkar, Shankar, Singh, Rekha

    ISSN: 1380-7501, 1573-7721
    Published: New York Springer US 01.11.2023
    Published in Multimedia tools and applications (01.11.2023)
    “… In addition, computer-assisted diagnosis (CAD) systems can be created to solve these obstacles by using machine learning approaches to classify retinal pictures as "healthy" or "infected…”
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    Journal Article
  16. 16

    Exploring the performance and emission characteristics of a dual fuel CI engine using microalgae biodiesel and diesel blend: a machine learning approach using ANN and response surface methodology by Tiwari, Chandrabhushan, Dwivedi, Gaurav, Verma, Tikendra Nath

    ISSN: 1573-2975, 1387-585X, 1573-2975
    Published: Dordrecht Springer Netherlands 01.09.2025
    “… The study employs a machine-learning (ML) approach, integrating artificial neural networks (ANN…”
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    Journal Article
  17. 17

    Large-scale classification of metagenomic samples: a comparative analysis of classical machine learning techniques vs a novel brain-inspired hyperdimensional computing approach by Joshi, Jayadev, Cumbo, Fabio, Blankenberg, Daniel

    ISSN: 2692-8205, 2692-8205
    Published: United States Cold Spring Harbor Laboratory 07.07.2025
    Published in bioRxiv (07.07.2025)
    “…Classical machine learning techniques have revolutionized bioinformatics, enabling researchers to extract knowledge from complex biological data…”
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    Journal Article Paper
  18. 18

    GENESYS: A novel evolutionary program synthesis tool with continuous optimization by Mandal, Shantanu, Anderson, Todd A, Turek, Javier, Gottschlich, Justin, Muzahid, Abdullah

    ISSN: 2836-8924, 2836-8924
    Published: 13.11.2025
    “… Most existing approaches formulate program synthesis as a search problem with discrete parameters…”
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    Journal Article
  19. 19

    PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search by Ahmad, Afzal, Xie, Zhiyao, Zhang, Wei

    Published: IEEE 09.07.2023
    “… This leads to GPU-memory bottlenecks that hamper the algorithm's scalability. To resolve these bottlenecks, we propose a perturbations-based evolutionary approach…”
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    Conference Proceeding
  20. 20

    UniGenCoder: Merging SEQ2SEQ and SEQ2TREE Paradigms for Unified Code Generation by Shao, Liangying, Yan, Yanfu, Poshyvanyk, Denys, Su, Jinsong

    ISSN: 2832-7632
    Published: IEEE 27.04.2025
    “…Deep learning-based code generation has completely transformed the way developers write programs today…”
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    Conference Proceeding