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  1. 1
    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification

    A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

    Published 2010
    “…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
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  2. 2
    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks

    Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

    Published 2014
    “…Owing to a number of salient features which include the ability of learning incrementally and establishing nonlinear decision boundary with hyperboxes, the Fuzzy Min-Max (FMM) network is selected as the backbone for designing useful and usable pattern classification models in this research. …”
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  3. 3
    Parallel distributed genetic algorithm development based on microcontrollers framework

    Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

    Published 2023
    Conference paper
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  4. 4
    Modern fuzzy min max neural networks for pattern classification

    Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

    Published 2019
    “…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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  5. 5
    Quality of service management algorithms in WiMAX networks

    Quality of service management algorithms in WiMAX networks by Saidu, Ibrahim

    Published 2015
    “…Simulation have been extensively used to evaluate the proposed algorithm. Finally, Discrete Event Simulator (DES) is designed and developed in order to evaluate the performance of the proposed algorithms. …”
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  6. 6
    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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  7. 7
    Deterministic Automatic Test Pattern Generation for Built-In Self Test System

    Deterministic Automatic Test Pattern Generation for Built-In Self Test System by Mohammed Khalid, Muhammad Nazir

    Published 2006
    “…To illustrate that, the DATPG algorithm for digital combinational circuit using VHDL language is designed to generate the test patterns. …”
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  8. 8
    Digital beamforming implementation of switch-beam smart antenna system by using integrated digital signal processor and field-programmable gate array

    Digital beamforming implementation of switch-beam smart antenna system by using integrated digital signal processor and field-programmable gate array by Vakilian, Vida

    Published 2008
    “…Also, for more antenna radiation pattern optimization, the sidelobe cancellation is performed base on the chebyshev algorithm. …”
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  9. 9
    Automatic spinal deformity detection based on neural network

    Automatic spinal deformity detection based on neural network by Kim, Hyoungseop, Ishikawa, Seiji, Khalid, Marzuki, Otsuka, Yoshinori, Shimizu, Hisashi, Nakada, Yasuhiro, Shinomiya, Takasi, Viergever, Max A.

    Published 2003
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  10. 10
    Artificial neural network-salp-swarm algorithm for stock price prediction

    Artificial neural network-salp-swarm algorithm for stock price prediction by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan, Abdul Aziz

    Published 2024
    “…Before training, the dataset is normalized using the min-max normalization technique to reduce the influence of noise. …”
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  11. 11
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…The WeSuSFTS algorithm uses the min-max operator for fuzzy reasoning and average rule defuzzification which make the process simpler. …”
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  12. 12
    Antenna design using left-handed materials

    Antenna design using left-handed materials by Abd. Rahman, Tharek, Abdolee, Reza

    Published 2008
    “…After modeling, the algorithm is implemented in DSP by using C and Code Composer Studio. …”
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  13. 13
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…The modified algorithm uses the min-max operator for fuzzy reasoning and peak-point defuzzification which make the process simpler. …”
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  14. 14
    Embedded Artificial Intelligent (AI) To Navigate Cart Follower

    Embedded Artificial Intelligent (AI) To Navigate Cart Follower by Tang, Khai Luen

    Published 2018
    “…The set of parameters used in traingd are lr, max_fail, min_grad, goal, time, and epochs. …”
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  15. 15
    Antenna design using left-handed materials

    Antenna design using left-handed materials by Abd. Rahman, Tharek, Ngah, Razali, Ahmad, Mohd. Riduan, Abdolee, Reza, Leow, Chee Yen, I. A. Omer, Abdusamea, Osman Elsayed, Waiel Elsayed, Yusuf, Yusuf Ali, Pon, Lai Ly

    Published 2008
    “…After modeling, the algorithm is implemented in DSP by using C and Code Composer Studio. …”
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  16. 16
    Improving neural networks training using experiment design approach

    Improving neural networks training using experiment design approach by Chong, Wei Kean

    Published 2005
    “…This project involves the use of Neural Networks (NN) for function approximation. …”
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  17. 17
    A scene invariant convolutional neural network for visual crowd counting using fast-lane and sample selective methods

    A scene invariant convolutional neural network for visual crowd counting using fast-lane and sample selective methods by Teoh, Shen Khang

    Published 2023
    “…The proposed model is designed with single column architecture using single filter size and max pooling size. Fast lane connection and sample selective algorithms have been designed specifically to tackle the issue of vanishing gradient and enhance the quality of the model. …”
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  18. 18
    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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  19. 19
    The effect of pre-processing techniques and optimal parameters on BPNN for data classification

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
    “…The architecture of artificial neural network (ANN) laid the foundation as a powerful technique in handling problems such as pattern recognition and data analysis. It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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  20. 20
    Real time self-calibration algorithm of pressure sensor for robotic hand glove system

    Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

    Published 2019
    “…This study investigates the use of a novel Proposed Self-Calibration Algorithm (PSCA) of multi pressure sensors in real time on robotic hand glove system. …”
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