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  1. 1
    Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column

    Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column by Maan, Normah

    Published 2005
    “…Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later refined to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
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  2. 2
    Mathematical modelling of mass transfer in multi-stage rotating disc contactor column

    Mathematical modelling of mass transfer in multi-stage rotating disc contactor column by Arshad, Khairil Anuar, Talib, Jamalludin, Maan, Normah

    Published 2006
    “…Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later re¯ned to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
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  3. 3
    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study

    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

    Published 2010
    “…Three phase flow data have been collected from different geographical locations; especially from Middle-Eastern fields in order to construct, test, and validate the model. The data covered a wide range of variables such as oil rate (up to 25000 STB/D), water cut (up to 60%), angles of inclination (from -80 to 210), pipe length up to 26.0 km and pressure drop (from 10 to 250 psi). the model has been generated using the Back-propagation technique with Bayesian Regularization training algorithm for predicting pressure drop in pipelines under various angles of inclination. …”
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  4. 4
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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  5. 5
    ANALYSIS AND OPTIMIZATION OF HYDROCYCLONE GEOMETRY USING BOX-BEHNKEN AND MULTI-OBJECTIVE OPTIMIZATION ALGORITHM

    ANALYSIS AND OPTIMIZATION OF HYDROCYCLONE GEOMETRY USING BOX-BEHNKEN AND MULTI-OBJECTIVE OPTIMIZATION ALGORITHM by MOHD NOR, MOHD AZRI

    Published 2021
    “…Therefore, the objectives of this research are to investigate hydrocyclone geometrical parameters impact onto performance (pressure drop, flow split and separation efficiency) using Box-Behnken, analysis of multivariate analysis of variance of geometrical parameters against performances and investigate and validate the effectiveness of multi objective optimization algorithm. …”
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  6. 6
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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  7. 7
    Development and tuning of bacteria foraging optimization algorithm on cell formation in cellular manufacturing system

    Development and tuning of bacteria foraging optimization algorithm on cell formation in cellular manufacturing system by Nouri, Hossein, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Samin, Razali

    Published 2013
    “…This research work inquires the applications of designed experiments aided by multiple regression analysis for tuning of this emerging novel optimization algorithm parameters to the cell formation (CF) problem considering operation sequence. …”
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  8. 8
    Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs

    Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs by Afshar Ghotli, Reza, Abbasi, Mohammad Reza, Bagheri, AmirHossein, Abdul Raman, Abdul Aziz, Ibrahim, Shaliza, Bostanci, Huseyin

    Published 2019
    “…Adaptive neuro-fuzzy inference system based on fuzzy C–means (ANFIS-FCM) clustering algorithm was used to develop a model to predict drop sizes, and its validation and accuracy were examined by comparing the results to the experimental data. …”
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  9. 9
    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman

    Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman by Abdul Rahman, Muhammad Nur Azri Irfan

    Published 2025
    “…The motivation behind the project was to help automate the cumbersome task of validating instruments from images using Convolutional Neural Network (CNNs) algorithm to identify the musical instrument so that this task could be completed with higher accuracy. …”
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  10. 10
    Development of cell formation algorithm and model for cellular manufacturing system

    Development of cell formation algorithm and model for cellular manufacturing system by Nouri, Hossein

    Published 2011
    “…The CMS relies on the principle of grouping machines into machine cells and grouping machine parts into part families that is named cell formation. Cells are formed based on presuming fixed single route and parts demand (traditional cell formation) or fluctuation of parts demand (dynamic cell formation). …”
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  11. 11
    Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.]

    Spectrum aware clustering algorithm based on fuzzy logic for sensor based monitoring application / Noorhayati Mohamed Noor …[et al.] by Mohamed Noor, Noorhayati, Md Din, Norashidah, Kasiran, Zolidah, Khalid, Nor Azimah, Abdullah, Shapina

    Published 2020
    “…The cluster heads (CHs) are selected according to the channel availability, residual energy, communication cost and node distribution parameters. Fuzzy logic and weight based techniques combines the four parameters for the CH selection. …”
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  12. 12
    Development of a mathematical model for the prediction of chip formation instability and its verification by fuzzy logic with genetic algorithm

    Development of a mathematical model for the prediction of chip formation instability and its verification by fuzzy logic with genetic algorithm by Ullah Patwari, Mohammed Anayet, Amin, A. K. M. Nurul, Istihyaq , M.H., Faris, Waleed Fekry

    Published 2010
    “…In this technique, a mathematical model has been developed between the cutting parameters and the instability frequency of the chip serration based on response surface methodology and the model is verified by fuzzy logic with genetic algorithm.…”
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  13. 13
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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  14. 14
    A VOICE PRIORITY QUEUE (VPQ) SCHEDULER FOR VOIP OVER WLANs

    A VOICE PRIORITY QUEUE (VPQ) SCHEDULER FOR VOIP OVER WLANs by NISAR, KASHIF

    Published 2011
    “…We proposed a new Voice Priority Queue (VPQ) scheduling system model and algorithms to solve scheduling issues. …”
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  15. 15
    Experimental implementation controlled SPWM inverter based harmony search algorithm

    Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb, Mushtaq, Mansor, Muhamad, Razali, Ramdan, Daniyal, Hamdan, A. F. Yahaya, Jabbar

    Published 2017
    “…The proposed overall inverter design and the control algorithm are modelled using MATLAB environment (Simulink/m-file Code). …”
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  16. 16
    An enhanced cluster head selection algorithm for routing in mobile AD-HOC network

    An enhanced cluster head selection algorithm for routing in mobile AD-HOC network by Abdulsaheb, Ghaida Muttasher

    Published 2017
    “…The performance of ECRP algorithms was compared with other cluster based algorithms. …”
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  17. 17
    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network

    A new routing mechanism for energy-efficient in bluetooth mesh-low power nodes based on wireless sensor network by Almuslehi, Hussein Saad Mohammed

    Published 2023
    “…It evaluates system formation methods, hierarchical structures, and leader selection criteria, comparing various parameters to identify factors influencing node formation and routing. …”
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  18. 18
    Experimental implementation controlled SPWM inverter based harmony search algorithm

    Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb M., Mansor M., Razali R., Daniyal H., Yahaya J.A.F.

    Published 2023
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  19. 19
    An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control

    An Efficient Cluster Head Election Algorithm for Client Mesh Networks using Fuzzy Logic Control by Adekiigbe, Adebanjo, Ahmed, Abdulghani Ali, Sadiq, Ali Safa, Ghafoor, Kayhan Zrar, Kamalrulnizam, Abu Bakar

    Published 2017
    “…The algorithm applied fuzzy logic control to produce score value for each client nodes based on the three parameters for the cluster heads to be selected. …”
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  20. 20
    Optimisation of fed-batch fermentation process using deep reinforcement learning

    Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

    Published 2023
    “…At the same time, the total ethanol formation is 0.19 g/l and 0.03 g/l lower than the exponential feeding and genetic algorithm, respectively. …”
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