Search Results - (( using optimization based algorithm ) OR ( knowledge implementation learning algorithm ))
Search alternatives:
- knowledge implementation »
- implementation learning »
- learning algorithm »
-
1
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. …”
Get full text
Get full text
Thesis -
2
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. …”
Get full text
Get full text
Conference or Workshop Item -
3
Coalition of genetic algorithms and artificial neural network for isolated spoken Malay speech recognition / Noraini Seman
Published 2012“…Genetic Algorithm (GA) based learning technique provides an alternative way that involves controlling the learning complexity by adjusting the number of weights of the ANN. …”
Get full text
Get full text
Book Section -
4
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. …”
Get full text
Get full text
Thesis -
5
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. …”
Get full text
Get full text
Get full text
Get full text
Article -
6
A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
Get full text
Get full text
Conference or Workshop Item -
7
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. …”
Get full text
Get full text
Get full text
Get full text
Proceeding Paper -
8
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. …”
Get full text
Get full text
Get full text
Article -
9
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. …”
Get full text
Get full text
Get full text
Article -
10
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. …”
Get full text
Get full text
Get full text
Article -
11
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. …”
Get full text
Get full text
Get full text
Article -
12
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. …”
Get full text
Get full text
Get full text
Article -
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. …”
Get full text
Get full text
Get full text
Article -
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. …”
Get full text
Get full text
Get full text
Article -
15
A Constrained Optimization based Extreme Learning Machine for noisy data regression
Published 2023Article -
16
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. …”
Get full text
Get full text
Get full text
Article -
17
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. …”
Get full text
Get full text
Get full text
Article -
18
Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
Get full text
Get full text
Get full text
Thesis -
19
Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
Get full text
Get full text
Get full text
Article -
20
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. …”
Get full text
Get full text
Thesis
