Search Results - (( model validation drops algorithm ) OR ( _ presentation based algorithm ))
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1
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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2
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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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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4
Energy Management Strategies for Optimal Hybrid Microgrid Configuration in the Smart Village Context
Published 2018“…The hybrid energy management algorithm-based the PLC signal was developed using the MATLAB. …”
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5
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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VANET SECURITY FRAMEWORK FOR LOW LATENCY SAFETY APPLICATIONS
Published 2012“…In this study, the proposed framework methods are simulated using two propagation models, i.e. two ray ground model and Nakagami model for VANET environment (802.11p). …”
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7
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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8
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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10
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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11
Time-Uncertainty Analysis by Using Simulation in Project Scheduling Networks
Published 1999“…The merge event bias as one of the essential problems associated with PERT is discussed, along with models and approaches developed by other researchers, namely, Probabilistic Network Evaluation Technique (PNET algorithm), Modified PNET, Back-Forward Uncertainly Estimation procedure (BFUE) and concept based on the robust reliability idea. …”
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12
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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13
A VOICE PRIORITY QUEUE (VPQ) SCHEDULER FOR VOIP OVER WLANs
Published 2011“…We proposed a new Voice Priority Queue (VPQ) scheduling system model and algorithms to solve scheduling issues. …”
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14
Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2017“…The proposed overall inverter design and the control algorithm are modelled using MATLAB environment (Simulink/m-file Code). …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2023Article -
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Development of predictive modeling and deep learning classification of taxi trip tolls
Published 2022“…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS
Published 2023“…Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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Enhanced Handover Algorithm for Quality of Service Maintenance in an Extended Service Set Wi-Fi Network
Published 2025“…To validate the suggested approach, a simulation modelling was built using MATLAB to benchmark and analyse the results. …”
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19
Optimisation of distributed generation in electric power systems using fuzzy-genetic algorithm approach
Published 2011“…This model takes into account, the peculiarities of radial distribution networks, such as high R/X (resistance/reactance) ratio, voltage dependency and composite nature of loads.To solve the proposed models, Genetic algorithm (GA) is used as an optimisation technique. …”
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20
Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease
Published 2024“…The baseline LightGBM model with dropped missing values had an accuracy of 0.8333, sensitivity of 0.1081, precision of 0.3429, F1 score of 0.1644, and AUC of 0.6875. …”
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