Search Results - (( evolution classification system algorithm ) OR ( program implementation matching algorithm ))

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    Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad by Muhamad, Kamarul Arifin

    Published 2002
    “…First experiment uses exact match, which is no method, is apply. Second experiment uses dynamic programmings apply with Wagner and Fischer algorithm.…”
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    Thesis
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    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
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    Conference or Workshop Item
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    Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

    Published 2020
    “…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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    Thesis
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    Selection of prospective workers using profile matching algorithm on crowdsourcing platform by Cucus, Ahmad, Aji, Luhur Bayu, Al Fahim, Mubarak Ali, Aminuddin, Afrig, Farida, Lilis Dwi

    Published 2022
    “…These criteria become variables that are used in the profile matching algorithm to find workers who best match the profiles offered. …”
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    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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    Thesis
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    An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players by Mohammad Zukuwwan, Zainol Abidin

    Published 2021
    “…The system can provide the team formation and players, and calculate the strength of the KFA team to justify its winning and loss of 2019 FA Cup and Malaysia Cup final matches respectively. This system can help coaches to solve problem regarding the strong team development with available players and motivate the use of decision technologies in sports able to match the results from the real world implementation.…”
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    Thesis
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    Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions by Adday, Ghaihab Hassan, K. Subramaniam, Shamala, Ahmad Zukarnain, Zuriati, Samian, Normalia

    Published 2022
    “…Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. …”
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    Article
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    Deep learning detector for pests and plant disease recognition by Ileladewa, Oluwatimilehin Adekunle

    Published 2020
    “…And developing a quick and accurate model could help in detecting pests and diseases in plants. Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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    Final Year Project / Dissertation / Thesis
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    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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    Conference or Workshop Item