Search Results - (( using optimization _ algorithm ) OR ( knowledge implementation learning algorithm ))
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1
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…These proves that without prior knowledge, the hybrid AI algorithm can self-learn. …”
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2
Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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3
Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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4
Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman
Published 2012“…However, due to the stochastic nature of this algorithm, the learning process can reach an optimal solution with much higher probability than many standard neural network techniques.…”
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Book Section -
5
Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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6
Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm
Published 2023“…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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7
Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…The global trend in the CCRA study shows that implementing machine learning and deep learning techniques is expanding rapidly. …”
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8
The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning
Published 2025“…The preliminary results using the K means Clustering Algorithm showed that the conceptual framework successfully grouped similar data points, facilitating the identification of skyline points. …”
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Proceeding Paper -
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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
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10
Bayesian Network Classifiers for Damage Detection in Engineering Material
Published 2007“…Changes in a system model should only induce local changes in a Bayesian network, where as system changes might require the design and training of an entirely new Neural network. The methodology used in the thesis to implement the Bayesian network for the damage detection provides a preliminary analysis used in proposing a novel fea- ture extraction algorithm (f-FFE: the f-folds feature extraction algorithm). …”
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11
Kernerlized Correlation Filters Parameters Optimization For Enhanced Visual Tracking
Published 2017“…Until now, there are still no perfect algorithm to track the target flawlessly. In order to improve the performance, the main idea proposed is implementing optimization technique on the selected parameters and obtain a better performance. …”
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Monograph -
12
Path Following Using A Learning Neural Network
Published 2004“…The implemented neural controller will in turn minimize a performance index, which includes the lateral and attitude angle errors ofvehicle models with respect to the paths. …”
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Final Year Project -
13
Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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14
Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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18
Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…A supervised learning algorithm implemented in standard backpropagation neural network gradient descent (GD), stochastic gradient descent (SGD) and Levenberg–Marquardt (LM) was constructed using TensorFlow with Spyder IDE in python language. …”
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Article -
20
Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Meanwhile, Spark Streaming effectively provides illustrious abstraction known as DStream, signifying an uninterrupted stream of data whereas Spark MLlib leverages algorithmic optimizations of MLlib and applies them in the proposed algorithms. …”
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Thesis
