Search Results - (( based evaluation a algorithm ) OR ( inspired classification _ algorithm ))

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  1. 1

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…Several experiments were carried out by using different set of training and testing data-sets to evaluate the accuracy of the proposed model.As a result, the accuracy of the proposed model is considered excellent for academic leadership classification.For future work, in order to enhance the proposed bio-inspired classification model, a comparative study should be conducted using other established artificial immune system classification algorithms i.e. clonal selection and artificial immune network.…”
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  2. 2

    Dengue classification system using clonal selection algorithm / Karimah Mohd by Mohd, Karimah

    Published 2012
    “…One of AIS Algorithm is Clonal Selection Algorithm (CSA) is to classify dengue disease is a suitable to solve classification problem in this project . …”
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    Thesis
  3. 3

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…Lastly, (i) a single-based solution representation, (ii) a switchable mutation scheme, (iii) a vector-based estimation of the mutation factor, and (iv) an optional crossover strategy are proposed in the VDEO framework. …”
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  4. 4

    Empowering cloud providers: optimised locust-inspired algorithm for SLA violation mitigation in green cloud computing by Alsaaidah, Yousef A., Muhammed, Abdullah, Ala’anzy, Mohammed Alaa, Othman, Mohamed, Abdullah, Azizol

    Published 2025
    “…It enhances the locust-inspired algorithm by integrating SLA-awareness and adaptive host classification and is evaluated using real workload traces in the CloudSim toolkit. …”
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    Article
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    A new hybrid technique for nosologic segmentation of primary brain tumors / Shafaf Ibrahim by Ibrahim, Shafaf

    Published 2015
    “…For this purpose, an algorithm which hybridized the Intensity Based Analysis (IBA), Grey Level Co-occurrence Matrices (GLCM), Adaptive Network-based Fuzzy Inference System (ANFIS) and £article ~warm Optimization (PSO) Clustering Algorithm (CAPSOCA) is proposed. …”
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    Thesis
  7. 7

    Evaluation of K-fold value in breast cancer diagnosis technique using SVM and bio-inspired optimization algorithm (JA-ABC5) by Nadarajan, Ravindran, Sulaiman, Noorazliza

    Published 2023
    “…For practical classification performance analysis, a K-fold value of K5 is advised based on the Wisconsin dataset results. …”
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    A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

    Published 2019
    “…By evaluating the model on food dataset FOOD101, extracting of features take 80.23 seconds and classifying and training of incremental algorithm take 1253.36 seconds with 77.72% test accuracy. …”
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  11. 11

    Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

    Published 2019
    “…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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    Article
  12. 12

    Evaluation of heuristic-based MicroRNA marker selection techniques for classification of cancer by Razak, Eliza, Yusof, Faridah, Ahmad Raus, Raha

    Published 2016
    “…In this paper, we employed three marker selection algorithms to select relevant miRNAs that are directly responsible for cancer classification. …”
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    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…Experimental results revealed that the ideal combination is a feature selection model with the implementation of bio-inspired search algorithm that consistently obtains the optimal solution (i.e. less number of features with higher classification accuracy) on the selected dataset. …”
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  15. 15

    Optimization of attribute selection model using bio-inspired algorithms by Basir, Mohammad Aizat, Yusof, Yuhanis, Hussin, Mohamed Saifullah

    Published 2019
    “…The aim of this paper is to investigate the use of bio-inspired search algorithms in producing optimal attribute set. …”
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    Article
  16. 16

    CYCLOSTATIONARY FEATURES BASED LOW COMPLEXITY MUTLIRESOLUTION SPECTRUM SENSING FOR COGNITVE RADIO APPLICATIONS by Adoum, Bakhit Amine Adoum

    Published 2011
    “…In this thesis, we suggest a cyclostationary features based low complexity multi-resolution spectrum sensing for cognitive radio applications. …”
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  17. 17

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…However, none of the available works had proposed BFOA as a classification algorithm despite of its good performance. …”
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  18. 18

    BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

    Published 2011
    “…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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    Thesis
  19. 19

    Review of Nature Inspired Metaheuristic Algorithm Selection for Combinatorial t-way Testing by Muazu, A.A., Hashim, A.S., Sarlan, A.

    Published 2022
    “…Nature-inspired is one of the classifications of metaheuristic algorithm that are becoming more popular among researchers for the last decades. …”
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  20. 20

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
    “…The algorithm, which is a swarm-based algorithm inspired by the food foraging behavior of honey bees, was also employed to select the components making up the feature vectors to be presented to the SVM. …”
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