Search Results - ((evolutionary OR solutionary) OR evolution) ((classification techniques) OR (learning techniques))

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  1. 1
    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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  2. 2
    Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects

    Evolutionary Fuzzy ARTMAP Neural Networks for Classification of Semiconductor Defects by Zuwairie, Ibrahim, Tan, Shing Chiang, Watada, Junzo, Marzuki, Khalid

    Published 2014
    “…The classification results of the proposed evolutionary FAM neural networks are presented, compared, and analyzed using several classification metrics. …”
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  3. 3
    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm

    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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  4. 4
    An efficient anomaly intrusion detection method with evolutionary neural network

    An efficient anomaly intrusion detection method with evolutionary neural network by Sarvari, Samira

    Published 2020
    “…In recent years, detection methods based on machine learning techniques are widely deployed in order to improve the efficiency of anomaly-based detection. …”
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  5. 5
    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif

    Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

    Published 2014
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    Research Reports
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  6. 6
    Email spam classification based on deep learning methods: A review

    Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

    Published 2025
    “…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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  7. 7
    Artificial intelligence based technique for classification of incipient faults in power transformer based on dissolved gas analysis (DGA) method / Fathiah Zakaria

    Artificial intelligence based technique for classification of incipient faults in power transformer based on dissolved gas analysis (DGA) method / Fathiah Zakaria by Zakaria, Fathiah

    Published 2014
    “…This thesis presents the development of an Evolutionary Programming (EP) - Taguchi Method (TM) - Artificial Neural Network (ANN) based technique for the (DGA) method based on historical industrial data. …”
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  8. 8
    Comparing machine learning techniques to segmentize and classify tongue regions for traditional and complementary medicine (TCM) diagnosis

    Comparing machine learning techniques to segmentize and classify tongue regions for traditional and complementary medicine (TCM) diagnosis by Bong, Min Xuan

    Published 2025
    “…This project investigates the application of machine learning and deep learning techniques for automated tongue diagnosis in the context of Traditional Chinese Medicine (TCM). …”
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  9. 9
    A transparent classification model using a hybrid soft computing method

    A transparent classification model using a hybrid soft computing method by Ainon, R.N., Lahsasna, A., Wah, T.Y.

    Published 2009
    “…Accuracy and transparency are two important criteria that should be satisfied by any classification model. In this paper, a transparent and relatively accurate classifier is developed using a hybrid soft computing technique. …”
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  10. 10
    Object detection and classification using few-shot learning in smart agriculture: A scoping mini review

    Object detection and classification using few-shot learning in smart agriculture: A scoping mini review by Nitiyaa Ragu, Jason Teo

    Published 2022
    “…One of the techniques that is popular is Few-Shot Learning (FSL). …”
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  11. 11
    Stock market turning points rule-based prediction / Lersak Photong … [et al.]

    Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

    Published 2021
    “…Results show that the best feature selection is term frequency and trimming of the feature with a frequency greater than 95%. The best news classification approach is based on Deep Learning techniques that provide the most accurate classification. …”
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    Book Section
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  12. 12
    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis

    Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

    Published 2019
    “…The first improvement includes using Elite Opposition-Based Learning (EOBL) at initialization phase of WOA. The second improvement involves the incorporation of evolutionary operators from Differential Evolution algorithm at the end of each WOA iteration including mutation, crossover, and selection operators. …”
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  13. 13
    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…Differential evolution (DE) is a simple yet powerful population-based metaheuristic. …”
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  14. 14
    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle

    Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

    Published 2023
    “…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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  15. 15
    Classification with degree of importance of attributes for stock market data mining

    Classification with degree of importance of attributes for stock market data mining by Khokhar, Rashid Hafeez, Md. Sap, Mohd. Noor

    Published 2004
    “…We present another modification of fuzzy decision tree (FDT) classification techniques that aims to combine symbolic decision trees in data classification with approximate reasoning offered by fuzzy representation. …”
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  16. 16
    Deep learning detector for pests and plant disease recognition

    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…However, in this project, deep learning techniques are used in developing a model for diseases and pest detection in plants, and then train and test the model before eventually integrating the model into a mobile application. …”
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  17. 17
    A joint learning classification for intent detection and slot filling from classical to deep learning: a review

    A joint learning classification for intent detection and slot filling from classical to deep learning: a review by Muhammad Yusuf, Idris, Naomie, Salim, Anazida, Zainal, Sinarwati, Mohamad Suhaili

    Published 2025
    “…It discusses the limitations of classical models, which led to the rise of deep learning techniques, and introduces a new taxonomy for joint learning classifying joint learning architectures. …”
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  18. 18
    Training process reduction based on potential weights linear analysis to accelerate back propagation network.

    Training process reduction based on potential weights linear analysis to accelerate back propagation network. by Asadi, Roya, Mustapha, Norwati, Sulaiman, Md. Nasir

    Published 2009
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  19. 19
    Classification of Immunosignature Using Random Forests for Cancer Diagnosis

    Classification of Immunosignature Using Random Forests for Cancer Diagnosis by Zarzar, Mouayad, Razak, Eliza, Htike@Muhammad Yusof, Zaw Zaw, Yusof, Faridah

    Published 2015
    “…The fundamental target of data mining and machine learning is to achieve efficacious cancer classification mechanisms which provide considerable and trustworthy classification accuracy. …”
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    Proceeding Paper
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  20. 20
    Classification of plant health (capsicum frutescens) normalize differences vegetation index using image processing

    Classification of plant health (capsicum frutescens) normalize differences vegetation index using image processing by Nurin Awanis, Mohd Rudin, Suhaimi, Puteh, Jessnor Arif, Mat Jizat, Ismail, Mohd Khairuddin, Anwar P. P., Abdul Majeed, Mohd Azraai, Mohd Razman

    Published 2021
    “…The evolution of food manufacturer in global contribute in national income of the country. …”
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