Search Results - (( model validation drops algorithm ) OR ( parameters variation based algorithm ))*
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Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column
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
Mathematical modelling of mass transfer in multi-stage rotating disc contactor column
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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Monograph -
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Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…PSO based QFT control algorithm is proposed for pneumatic servo actuator system. …”
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4
Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study
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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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
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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ANALYSIS AND OPTIMIZATION OF HYDROCYCLONE GEOMETRY USING BOX-BEHNKEN AND MULTI-OBJECTIVE OPTIMIZATION ALGORITHM
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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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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8
Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…This research investigates the effect of moment of inertia on the performance of PSO algorithm utilizing the Weighted Transient Response Index (WTPJ) based fitness function in optimizing PID controller parameters to control a DC motor. …”
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9
Experimental and modeling evaluation of droplet size in immiscible liquid-liquid stirred vessel using various impeller designs
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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Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations
Published 2025thesis::master thesis -
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Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…This research investigates the effect of moment of inertia on the performance of PSO algorithm utilizing the Weighted Transient Response Index (WTRI) based fitness function in optimizing PID controller parameters to control a DC motor. …”
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Book Section -
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Musical instrument identification using Convolutional Neural Network (CNN) algorithm / Muhammad Nur Azri Irfan Abdul Rahman
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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15
Model-based hybrid variational level set method applied to lung cancer detection
Published 2024“…This algorithm simplifies the (Local Intensity Clustering) LIC model and devises a new energy functional based on the region-based pressure function. …”
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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems
Published 2024“…This paper explores the tuning of the Sigmoid Proportional-Integral-Derivative (SPID) controller using variations of the Smoothed Functional Algorithm (SFA) for the underactuated Multiple-Input Multiple-Output (MIMO) twin-rotor system. …”
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Conference or Workshop Item -
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An analysis of the parameter modifications in varieties of harmony search algorithm
Published 2014“…A Harmony Search (HS) algorithm is a population based-meta-heuristics approach that is superior in solving diversified and large scale optimization problems. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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Thesis
