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  1. 1
    Pattern Classification of Human Epithelial Images

    Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

    Published 2016
    “…This project shows an important role to diagnosis autoimmune disorder which is by a comparative analysis on the most appropriate clustering technique for the segmentation and also to develop algorithm for positivity classification. …”
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  2. 2
    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation

    Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation by Kamaruddin, Shafie, Bahari, Muhammad Syahril, Pham, Duc Truong, Mohd Amin Hamzas, Mohd Fidzwan, Zakaria, S

    Published 2019
    “…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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  3. 3
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…The Neuro-Fuzzy hybridization scheme has become of research interest in pattern classification over the past decade. The present paper proposes a hybrid Modified Adaptive Fuzzy Inference Engine (MAFIE) for pattern classification. …”
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  4. 4
    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction

    An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction by Shah, Habib

    Published 2014
    “…Furthermore, here these algorithms used to train the MLP on two tasks; the seismic event's prediction and Boolean function classification. …”
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  5. 5
    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition

    The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition by M. A., Ameedeen, Marhaini, M. S.

    Published 2016
    “…This research is mainly focused on creating a new algorithm based on classification technique to calculate food calorie intake in real-time. …”
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  6. 6
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. …”
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  7. 7
    Protein Conformantional Search Using Bees Algorithm

    Protein Conformantional Search Using Bees Algorithm by Bahamish, Hesham Awadh A., Abdullah, Rosni, Salam, Rosalina Abdul

    Published 2008
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  8. 8
    An Algorithm for Fingerprint Classification Using Template Matching Technique

    An Algorithm for Fingerprint Classification Using Template Matching Technique by Al-Kaissi, Ahmed Wathik Naji

    Published 2002
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  9. 9
    Pattern Recognition for Human Diseases Classification in Spectral Analysis

    Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

    Published 2022
    “…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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  10. 10
    Hybrid ACO and SVM algorithm for pattern classification

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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  11. 11
    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach

    Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

    Published 2009
    “…The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distribution. …”
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  12. 12
    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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  13. 13
    Application of Bee Colony Optimization (BCO) in NP-Hard Problems

    Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

    Published 2011
    “…This report presents the first stage of an ongoing research which is the problem solving of highly complex tasks using Bee-Inspired algorithms. Bee-Inspired algorithms are partially referring to the nature of bee swarm behaviour. …”
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  14. 14
    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems

    Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems by Rahimi, Amir Masoud, Ramezani-Khansari, Ehsan

    Published 2021
    “…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. …”
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  15. 15
    Construction of Cryptographically Strong S-Boxes Inspired by Bee Waggle Dance

    Construction of Cryptographically Strong S-Boxes Inspired by Bee Waggle Dance by Isa H., Jamil N., Z�aba M.R.

    Published 2023
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  16. 16
    Incremental continuous ant colony optimization for tuning support vector machine’s parameters

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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  17. 17
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  18. 18
    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah

    Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

    Published 2009
    “…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. The study involves the development of Artificial Bee Colony (ABC) algorithm to implement loss minimization in a distribution system. …”
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  19. 19
    Automatic classification of medical x-ray images

    Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

    Published 2013
    “…Image representation is one of the major aspects of automatic classification algorithms. In this paper, different feature extraction techniques have been utilized to represent medical X-ray images. …”
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  20. 20
    Neural network paradigm for classification of defects on PCB

    Neural network paradigm for classification of defects on PCB by Heriansyah, Rudi, Syed Al-Attas, Syed Abdul Rahman, Zabidi, Muhammad Mun'im Ahmad

    Published 2003
    “…The algorithms to segment the image into basic primitive patterns, enclosing the primitive patterns, patterns assignment, patterns normalization, and classification have been developed based on binary morphological image processing and Learning Vector Quantization (LVQ) neural network. …”
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