Search Results - (( model evaluation modified algorithm ) OR ( panel automation system algorithm ))*
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Integration Of Machine Vision In Industrial Robot For Automated Composite Panel Punching
Published 2018“…Position and rotation of panels are compared to three coordinate systems which are camera, workpiece and machining center. …”
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The implementation of fault management in distribution system using distribution automation system (DAS) in conjunction with SCADA
Published 2012“…Therefore, the implementation of proper fault management is highly important to be utilized such as by applying automation system in distribution system. Up to date, in Malaysia there is no automation technique being used for maintenance work in distribution system. …”
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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust, intelligent network of FDA control panels in real-time. …”
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Network-based real-time integrated Fire Detection and Alarm (FDA) system with building automation
Published 2017“…This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. …”
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Proceeding Paper -
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Implementation of hashed cryptography algorithm based on cryptography message syntax
Published 2019“…The important study in this research is an automated learning system for deep learning to enhance security. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Advanced solar tracking system with temperature control and real-time monitoring
Published 2025“…These algorithms dynamically control the servo motor, relay module, and LCD display, adapting the system based on environmental conditions. …”
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Book Section -
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M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Monograph -
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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Conference or Workshop Item -
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The new proposed method (MBPSO+MKN+GK) Gustafson- Kessel algorithm (GK)integrated with modified of Kohonen Network algorithm (MKN)and modified binary particle swarm optimization (MBPSO) was used to classify the credit scoring data. …”
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Modification of the CREAMS Nutrient submodel
Published 2011“…The CREAMS nutrient submodel was modified to improve the prediction, of the nitrogen loss from a flat agricultural field with a fluctuating water table.The CREAMS nutrient submodal was modified by incorporating a water function in the CREAMS denitrification algorithm.The capability of the CREAMS nutrient submodel and modified CREAMS nutrient submodel in predicting nitrogen loss was evaluated by using linear regression analysis, t-test on the slope and intercept of the regression equation, standard deviation of differences, absolute average differences, and percent error.Observed data from an experimental plot near Baton Rouge, Louisiana, USA were used in this study.The modified model underestimated the total nitrogen losses by 2% compared to 35% overestimation by the CREAMS model.Overall performance of the modified model in predicting nitrogen losses was satisfactory.…”
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Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting
Published 2021“…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of four main phases; data pre-processing, model development, model implementation and model evaluation. …”
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Parametric modelling of twin rotor system using chaotic fractal search algorithm
Published 2016“…Then, the modified Fractal Search algorithms are employed to optimise the parameters for an ARX model of twin rotor system in hovering mode. …”
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). This study aims to enhance the accuracy and efficiency of ozone level prediction models by selecting the most informative features from the dataset. …”
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Performance Analysis of ARMA based Magnetic Resonance Imaging (MRI) Reconstruction Algorithm
Published 2012“…Keywords: Autoregressive Model Algorithm (ARMA), Magnetic Resonance Imaging (MRI), Reconstruction …”
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Monograph -
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System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). This study aims to enhance the accuracy and efficiency of ozone level prediction models by selecting the most informative features from the dataset. …”
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