Application of Ant Colony Algorithm in Plant Leaves Classification Based on Infrared Spectroscopy Analysis

Abstract:

Intelligent classification is realized according to different components of featured information included in near infrared spectrum data of plants. The core of this theory is to research applications of ant colony algorithm in spectral analysis of plant leaves through theories and experiments. In aspect of theoretical exploration, the built-in function of clustering algorithm is used to compress and process data. In aspect of experimental research, the near infrared diffuse emission spectrum curves of the leaves of Cinnamomum camphora and Acer saccharum Marsh in two groups, which have 75 leaves respectively. Then, the obtained data are processed using ant colony algorithm and the same leaves can be classified as a class by ant colony clustering algorithm. Finally, the two groups of data are classified into two classes. Our results show the distinguishability can be 100%. Keywords:Near infrared spectroscopy; ant colony algorithm; clustering algorithm; signal processing

• Periodical: Key Engineering Materials (Volume 633)
• Pages: 503-506
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.633.503
• Online since: November 2014
• Authors: Mei Lin Gao Sun, Ping Wu, Kai Li, Zhen Hua Gen
• Keywords: Ant Colony Algorithm, Clustering Algorithm, Near Infrared Spectroscopy, Signal Processing

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