An Application of Ant Colony Algorithm for Edge Feature Extraction in City Aerial Image for Building Recognition

In this paper, a new method for the optimization design of ant colony algorithm is used to extract the edge character of the model in the air of the image. The organization is as follows: the second part is a basic ant colony algorithm in the edge of the model feature extraction. The result of the advisory council on AIDS will be compared with the results analysis, and think this is smart operator most edge feature extraction operator. Contrast indicates that the algorithm can effectively edge feature extraction, especially the image.

Download Full-text

A Kind of Network Intrusion Detection Method Using Improved Support Vector Machine Based on Ant Colony Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.263-266.2995 ◽

2012 ◽

Vol 263-266 ◽

pp. 2995-2998

Author(s):

Xiaoqin Zhang ◽

Guo Jun Jia

Keyword(s):

Genetic Algorithm ◽

Support Vector Machine ◽

Feature Extraction ◽

Ant Colony Algorithm ◽

Small Sample ◽

Ant Colony ◽

Support Vector ◽

Algorithm Selection ◽

Data Set ◽

Network Intrusion

Support vector machine (SVM) is suitable for the classification problem which is of small sample, nonlinear, high dimension. SVM in data preprocessing phase, often use genetic algorithm for feature extraction, although it can improve the accuracy of classification. But in feature extraction stage the weak directivity of genetic algorithm impact the time and accuracy of the classification. The ant colony algorithm is used in genetic algorithm selection stage, which is better for the data pretreatment, so as to improve the classification speed and accuracy. The experiment in the KDD99 data set shows that this method is feasible.

Download Full-text

Application of ant colony algorithm in feature extraction

2006 6th World Congress on Intelligent Control and Automation ◽

10.1109/wcica.2006.1713971 ◽

2006 ◽

Cited By ~ 1

Author(s):

Ying Zhang ◽

Xue-Bo Chen

Keyword(s):

Feature Extraction ◽

Ant Colony Algorithm ◽

Ant Colony

Download Full-text

A Novel Feature Extraction Method Using Ant Colony Clustering Analysis

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.37-38.32 ◽

2010 ◽

Vol 37-38 ◽

pp. 32-35

Author(s):

De Bin Zhao ◽

Ji Hong Yan

Keyword(s):

Feature Extraction ◽

Clustering Analysis ◽

Extraction Method ◽

Ant Colony Algorithm ◽

Wavelet Packet ◽

Wavelet Packet Transform ◽

Ant Colony ◽

Vibration Signals ◽

Feature Extraction Method ◽

Ant Colony Clustering

A novel feature extraction method is presented by combining wavelet packet transform with ant colony clustering analysis in this paper. Vibration signals acquired from equipments are decomposed by wavelet packet transform, after which frequency bands of signals are clustered by ant colony algorithm, and each cluster as a set of data is analyzed in frequency-domain for extracting intrinsic features reflecting operating condition of machinery. Furthermore, the robust ant colony clustering algorithm is proposed by adjusting comparing probability dynamically. Finally, effectiveness and feasibility of the proposed method are verified by vibration signals acquired from a rotor test bed.

Download Full-text