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  1. 1
    Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks

    Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks by Sadiq, A., Yahya, N.

    Published 2021
    “…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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  2. 2
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…Multi-Verse Optimizer (MVO) is one of the most recent robust nature-inspired metaheuristic algorithm. It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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  3. 3
    An implementation of brain emotional learning based intelligent controller for AVR system

    An implementation of brain emotional learning based intelligent controller for AVR system by Saat, Shahrizal, Ghazali, Mohd Riduwan, Ahmad, Mohd Ashraf, Mustapha, Nik Mohd Zaitul Akmal, Tumari, Mohd Zaidi Mohd

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. PSO algorithm is used to tuned twelve BELBIC controller parameters in order to improve the time domain parameters such as overshoot percentage (OS%), rise time (tr), settling time (ts) and steady state error (Ess) of the step response for an AVR system in order to minimize value of objective function based on ZLG method. …”
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  4. 4
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…This research focuses on the use of binaryencoded genetic algorithm (GA) to implement efficient search strategies for the optimal architecture and training parameters of a multilayer feed-forward ANN. …”
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  5. 5
    An implementation of brain emotional learning based intelligent Controller for AVR system

    An implementation of brain emotional learning based intelligent Controller for AVR system by Shahrizal, Saat, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Nik Mohd Zaitul Akmal, Mustapha, Mohd Zaidi, Mohd Tumari

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. PSO algorithm is used to tuned twelve BELBIC controller parameters in order to improve the time domain parameters such as overshoot percentage (OS%), rise time (tr), settling time (ts) and steady state error (Ess) of the step response for an AVR system in order to minimize value of objective function based on ZLG method. …”
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  6. 6
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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  7. 7
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There have two most uses activation function namely tansig and logsig. …”
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  8. 8
    SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR

    SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR by FUNG , CHUN TING

    Published 2005
    “…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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  9. 9
    Nomadic people optimizer (NPO) for large-scale optimization problems

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
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  10. 10
    Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques

    Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques by Anifowose, Fatai Adesina

    Published 2015
    “…The algorithms were implemented with optimized tuning parameters and validated with real-life porosity and permeability datasets obtained from diverse and heterogeneous petroleum reservoirs after they have passed on testing them with a benchmark dataset from the UCI Machine Learning Repository. …”
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  11. 11
    An optimized ensemble for predicting reservoir rock properties in petroleum industry

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…A lot of researches have been done to predict the reservoir parameters using well log data through applying various methods. …”
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  12. 12
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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  13. 13
    Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptation algorithm.

    Multi-agent reinforcement learning for Bai ethnic traditional dwelling protection in Dali : cultural identity-oriented community relationship optimization and urbanization adaptati... by Xiaohua, Qian, Neilson Ilan, Mersat, Haslina, Hashim, Bemen Wong, Win Keong

    Published 2025
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  14. 14
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  15. 15
    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy

    Artificial neural network algorithm for predicting the surface roughness in end milling of Inconel 718 alloy by Hossain, Mohammad Ishtiyaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  16. 16
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…These rule sets was implemented in the MYEmotion using MATLAB environment. …”
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  17. 17
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. …”
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  18. 18
    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique

    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

    Published 2016
    “…The IncFRNN algorithm updates the training set by employing a heuristic update method to maintain representative objects and eliminate rarely used objects. …”
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  19. 19
    Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML)

    Monitoring water quality in Pusu river using Internet of Things (IoT) and Machine Learning (ML) by Kabbashi, Nassereldeen Ahmed, Hasan, Tahsin Fuad, Alam, Md Zahangir, Saleh, Tanveer, Hassan Abdalla Hashim, Aisha

    Published 2024
    “…Machine learning (ML) tools will be employed to analyze and simulate these data, enabling the prediction of future water quality parameters. …”
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  20. 20
    Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani

    Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani by Che Ani, Adi Izhar

    Published 2023
    “…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
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