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1
Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…Image preprocessing and image extraction are done by using MATLAB. The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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Thesis -
2
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
3
Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms
Published 2001“…The paper highlights a novel and robust method to control a robotic arm using an iterative learning technique embedded in an active force control strategy. …”
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4
A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction
Published 2018“…For this purpose, the suggested approach that makes a hybridizing the FA with the robust algorithm (RA), where RA is used to control the steps of randomness for the FA while optimizing the weights of the standard BPNN model. …”
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5
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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6
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…However, the most popular backpropagation algorithm which is based on Widrow-Hoff delta learning rule is not completely robust in the presence of outliers and this may cause false prediction of future values. …”
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Book Section -
7
Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar
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Research Reports -
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Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong
Published 2004“…The paper highlights a novel and robust method to control a robotic arm using iterative learning technique embedded in an active force control strategy. …”
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Article -
9
Robust incremental growing multi-experts network
Published 2006“…Moreover, various types of supervised learning algorithms can easily adopt LMLS, which is a parameter-free method.…”
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10
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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Thesis -
11
Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
13
Prediction of payment method in convenience stores using machine learning
Published 2023“…The Random Forest algorithm was employed due to its robustness in handling complex, high-dimensional data, and its ability to provide reliable predictions. …”
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Conference or Workshop Item -
14
Indoor occupancy detection using machine learning and environmental sensors / Akindele Segun Afolabi ... [et al.]
Published 2025“…In this paper, we experimentally determined the Machine Learning (ML) models that are most robust for use in indoor occupancy detection. …”
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15
Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…The PRSS algorithm is an adaptive search technique that can learn a high performance knowledge structure in reactive environments that provide information as an objective function. …”
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16
Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Moreover, the ability of initialization the hidden nodes parameters using density function and recursive algorithm will help WN-OSELM to perform useful generalization facility and modeling accuracy. …”
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17
Classification of Cognitive Frailty in Elderly People from Blood Samples using Machine Learning
Published 2021“…A total of 7 different classification algorithms were used to predict between 6 levels of CF, the Robust and Non-Robust groups, as well as the Robust and Frail with MCI groups. …”
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Conference or Workshop Item -
18
Robust Pornography Classification Solving the Image Size Variation Problem Based on Multi-Agent Learning
Published 2015“…This study proposed a pornography classifier using multi-agent learning as a combination of the Bayesian method using color features extracted from skin detection based on the YCbCr color space and the back-propagation neural network method using shape features also extracted from skin detection. …”
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19
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Thesis -
20
Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”
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