Search Results - (( java adaptation optimization algorithm ) OR ( using auto process algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
Development of auto-tracking mobile robot
Published 2018“…In order to improve the accuracy of identification of object in different illumination and background conditions, the implementation of HSI color model is used in image processing algorithm. In this project HSI-based color filtering algorithm were used for object identification. …”
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Conference or Workshop Item -
3
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm.…”
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Book Section -
4
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The identification process of NARX/NARMA/NARMAX involves structure selection and parameter estimation, which can be simultaneously performed using the widely accepted Orthogonal Least Squares (OLS) algorithm. …”
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Thesis -
5
Improvement of Auto-Tracking Mobile Robot based on HSI Color Model
Published 2018“…In order to improve the accuracy of identification of object in different illumination and background conditions, the implementation of HSI color model is used in image processing algorithm. In this project HSI-based color enhancement algorithm were used for object identification. …”
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Article -
6
Implementation of Frequency Drift for Identification of Solar Radio Burst Type II
Published 2016“…The value of frequency drift was used as the main idea in this auto classify algorithm because it can easily implemented using MATLAB. …”
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Article -
7
Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters
Published 2011“…This paper presents an improved version of K-means algorithm with auto-generate an initial number of clusters (k) and a new approach of defining initial Centroid for effective and efficient clustering process. …”
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Article -
8
Implementation of Frequency Drift for Identification of Solar Radio Burst Type II
Published 2016“…The value of frequency drift was used as the main idea in this auto classify algorithm because it can easily implemented using MATLAB. …”
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Article -
9
Intelligent auto tracking in 3D space by image processing
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Proceeding Paper -
10
An artificial neural network hybrid with wavelet transform for short-term wind speed forecasting: A preliminary case study
Published 2023Conference Paper -
11
Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting
Published 2014“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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Book Section -
12
Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons
Published 2018“…The rolling mechanism method is applied to smooth out the dataset based on the antecedent values of the model inputs before being applied to the GM algorithm. The optimization of the input datasets selection was performed using auto-correlation (ACF) and partial auto-correlation (PACF) functions. …”
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Article -
13
Earthquake prediction model based on geomagnetic field data using automated machine learning
Published 2024“…The results showed that practical EQ prediction models could be achievable even for complex systems like lithospheric and seismo-induced geomagnetic processes by employing AutoML. © 2024 IEEE.…”
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Article -
14
Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting
Published 2014“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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Book Section -
15
Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting
Published 2014“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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Book Section -
16
AUTO-MANAGE PARKING SYSTEM (AMPS)
Published 2019“…The system able to recognize characters on number plate by using Automatic Number Plate Recognition (ANPR) technology which implement optical character recognition (OCR) algorithm to process the characters from images. …”
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Final Year Project -
17
Hybridization on Ensemble Kalman Filter and Non-Linear Auto-Regressive Neural Network for Financial Forecasting
Published 2014“…In this study, a novel hybrid model, called UKF-NARX, consists of unscented kalman filter and non-linear auto-regressive network with exogenous input trained with bayesian regulation algorithm is modelled for chaotic financial forecasting. …”
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Citation Index Journal -
18
A student learning style auto-detection model in a learning management system
Published 2023“…Future studies include the use of machine learning algorithms such as decision trees to auto-detect student learning styles in learning management systems.…”
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Article -
19
Text Summarization System with Bayesian Theorem on Oil & Gas Drilling Topic
Published 2007“…Human-made summary are used as the ideal or reference summary in evaluating both performance; the Text Summarization system and the Word Auto Summarizer. …”
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Final Year Project -
20
Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior
Published 2023“…All the machine learning algorithms from TPOT and AutoModel are considerable powerful to generate good accuracy level (between 70â��93 of AUC) in classifying both cases of whistleblowing and non-whistleblowing on the hold-out samples from the testing process. …”
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