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Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS
Mohamed Hamlich,
Mohammed Ramdani
Issue:
Volume 5, Issue 3-1, May 2016
Pages:
1-4
Received:
10 October 2015
Accepted:
12 October 2015
Published:
18 June 2016
Abstract: Several studies have sought to identify the parameters that determine the outcome of balloon dilation in pulmonary atresia with ventricular septum. However, none of these studies was based on the ant colony algorithm. In this paper we focus on the implementation of an algorithm based on ant colonies: Fuzzy Ant-Miner. This method uses the concepts of fuzzy logic to extract rules from the training data. These rules are exploited using a Mamdani fuzzy inference system for classification and prediction. The results obtained by this method in the form of fuzzy rules are easy to interpret, and close to human reasoning.
Abstract: Several studies have sought to identify the parameters that determine the outcome of balloon dilation in pulmonary atresia with ventricular septum. However, none of these studies was based on the ant colony algorithm. In this paper we focus on the implementation of an algorithm based on ant colonies: Fuzzy Ant-Miner. This method uses the concepts o...
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New Approach to Modeling the Direct Torque Control Applied to the Asynchronous Machine, Reduction of Undulations on the Torque
Hamid Yantour,
Janah Saadi,
Ahmed Khoumsi
Issue:
Volume 5, Issue 3-1, May 2016
Pages:
5-22
Received:
4 December 2015
Accepted:
5 January 2016
Published:
18 June 2016
Abstract: In this paper, we study the Direct Torque Control (DTC) of an Induction Motor coupled to an Inverter (Inv-IM). DTC permits to control directly the stator flux and the torque by selecting the appropriate inverter state. DTC has been introduced because it presents several advantages in comparison to other techniques such as voltage/frequency control, vector control and field control. In this paper, we first model the DTC of Inv-IM as a hybrid system (HS). Then, we abstract the continuous dynamics of the HS in terms of discrete events. We thus obtain a discrete event model of the HS. And finally, we use Supervisory Control Theory of DES to drive Inv-IM to a desired working point.
Abstract: In this paper, we study the Direct Torque Control (DTC) of an Induction Motor coupled to an Inverter (Inv-IM). DTC permits to control directly the stator flux and the torque by selecting the appropriate inverter state. DTC has been introduced because it presents several advantages in comparison to other techniques such as voltage/frequency control,...
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Applying the SAC Algorithm to Extract the Cardiologic Indicators of an Athlete's Level
Mohamed Hamlich,
Mohammed Ramdani
Issue:
Volume 5, Issue 3-1, May 2016
Pages:
23-27
Received:
19 December 2015
Accepted:
21 December 2015
Published:
18 June 2016
Abstract: The objective of this paper is to identify the parameters that determine the level (high or low) of an athlete. The developed method is based on the algorithms of ant colonies. In this paper We will focus on the application of an algorithm named: SAC “Scout Ant for Clustering”. This method is an extension of existing data clustering algorithms (ACO) based on ant colonies. The clusters’ separation test was improved by using the probabilities determined in step search of the best path between all instances. The SAC method treated any data sets (heterogeneous attributes: continuous and nominal) and represents each cluster by its prototype. This is determined for each cluster and it is the closest instance to all elements of the cluster. This method will be applied to cardiological data, which are taken on athletes.
Abstract: The objective of this paper is to identify the parameters that determine the level (high or low) of an athlete. The developed method is based on the algorithms of ant colonies. In this paper We will focus on the application of an algorithm named: SAC “Scout Ant for Clustering”. This method is an extension of existing data clustering algorithms (ACO...
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A New Edge Detection Using Decomposition Model
Saloua Senhaji,
Abdellah Aarab
Issue:
Volume 5, Issue 3-1, May 2016
Pages:
28-31
Received:
19 December 2015
Accepted:
25 December 2015
Published:
30 June 2016
Abstract: Edge detection is one of the most commonly used operations in image analysis, and there are more algorithms in the literature for enhancing and detecting edges. Natural images contain both textured and untextured regions, so the cues of contour and texture are exploited simultaneously. In this paper, we present a new edge detection method for natural images using decomposition model. The main idea is to decompose image in to two image components (geometric and texture) obtained by the PDE. The edge detection is performed not on the original image but on its geometric components. Experimental results on a wide range of images are shown.
Abstract: Edge detection is one of the most commonly used operations in image analysis, and there are more algorithms in the literature for enhancing and detecting edges. Natural images contain both textured and untextured regions, so the cues of contour and texture are exploited simultaneously. In this paper, we present a new edge detection method for natur...
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