Search Results - (((( self learning algorithm ) OR ( pattern using algorithm ))) OR ( patterns acs algorithm ))
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1
Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Self-Organizing Feature (SOM) was used to visualize and identify the relationship and pattern between factors affecting mortality after ACS. …”
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2
An artificial neural network model for multi dimension reduction and data structure exploration, Proceedings of International Conference of Soft Computing and Pattern Recognition (...
Published 2009“…SOM, being a prominent unsupervised learning algorithm, is often used for multivariate data visualization. …”
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3
The application of voltage sags pattern to locate a faulted section in distribution network
Published 2010“…This paper proposes an alternative automated fault location algorithm to locate a faulted section in distribution network using only voltage sag data monitored at the primary substation. …”
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4
Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing
Published 2015“…The algorithms are ACS(GA), ACS+GA, ACS(TS), and ACS+TS. …”
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5
An improved ACS algorithm for data clustering
Published 2020“…To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms.…”
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6
BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK
Published 2011“…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
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7
Xilinx (FPGA) design for single phase DC-AC matrix converter with sinusoidal pulse width modulation (SPWM) / Mohd Raduan Md Adam
Published 2003“…One sine waveform with one carrier waveforms is used to generate the PWM. The PWM pattern proposes occupies less FPGA block cell hence more space could be used for other control algorithm. …”
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An efficient fuzzy clustering algorithm for mining user session clusters on web log data
Published 2021“…The utilization of data that is assembled by Web Usage Mining gives the organizations the capacity to deliver results more compelling to their organizations and expanding of sales. Client access patterns can be mined from web access log information using Web Usage Mining (WUM) techniques. …”
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10
Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm
Published 2015“…This study aimed to determine the spatiotemporal pattern of the water quality data and identifying the sources of pollution in the Klang River Basin. The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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11
Multilevel learning in Kohonen SOM network for classification problems
Published 2006“…Classification is one of the most active research and application areas of neural networks. Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
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12
APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN
Published 2011“…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
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13
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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14
Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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15
Immune network algorithm in monthly streamflow prediction at Johor river
Published 2014“…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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16
Facial image retrieval on semantic features using adaptive mean genetic algorithm
Published 2019“…Finally, the features are selected using Adaptive Mean Genetic Algorithm (AMGA). In this study, the average PSNR value obtained after applying Wiener filter was 45.29. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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18
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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20
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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