A novel approach on behavior of sleepy lizards based on k-nearest neighbor algorithm

Lin Lin Tang; Jeng Shyang Pan; Xiaolv Guo; Shu Chuan Chu; John F. Roddick

doi:10.1007/978-3-319-02993-1_13

A novel approach on behavior of sleepy lizards based on k-nearest neighbor algorithm

Lin Lin Tang^*
, Jeng Shyang Pan
, Xiaolv Guo
, Shu Chuan Chu
, John F. Roddick

^*Corresponding author for this work

Harbin Institute of Technology Shenzhen
Flinders University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Scopus citations

Abstract

The K-Nearest Neighbor algorithm is one of the commonly used methods for classification in machine learning and computational intelligence. A new research method and its improvement for the sleepy lizards based on the K-Nearest Neighbor algorithm and the traditional social network algorithms are proposed in this chapter. The famous paired living habit of sleepy lizards is verified based on our proposed algorithm. In addition, some common population characteristics of the lizards are also introduced by using the traditional social net work algorithms. Good performance of the experimental results shows efficiency of the new research method.

Original language	English
Title of host publication	Social Networks
Subtitle of host publication	A Framework of Computational Intelligence
Publisher	Springer Verlag
Pages	287-311
Number of pages	25
ISBN (Print)	9783319029924
DOIs	https://doi.org/10.1007/978-3-319-02993-1_13
State	Published - 2014
Externally published	Yes

Publication series

Name	Studies in Computational Intelligence
Volume	526
ISSN (Print)	1860-949X

Keywords

Computational intelligence
K-Nearest neighbor (KNN) algorithm
Sleep lizard
Social network analysis (SNA)

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10.1007/978-3-319-02993-1_13

Cite this

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title = "A novel approach on behavior of sleepy lizards based on k-nearest neighbor algorithm",

abstract = "The K-Nearest Neighbor algorithm is one of the commonly used methods for classification in machine learning and computational intelligence. A new research method and its improvement for the sleepy lizards based on the K-Nearest Neighbor algorithm and the traditional social network algorithms are proposed in this chapter. The famous paired living habit of sleepy lizards is verified based on our proposed algorithm. In addition, some common population characteristics of the lizards are also introduced by using the traditional social net work algorithms. Good performance of the experimental results shows efficiency of the new research method.",

keywords = "Computational intelligence, K-Nearest neighbor (KNN) algorithm, Sleep lizard, Social network analysis (SNA)",

author = "Tang, \{Lin Lin\} and Pan, \{Jeng Shyang\} and Xiaolv Guo and Chu, \{Shu Chuan\} and Roddick, \{John F.\}",

year = "2014",

doi = "10.1007/978-3-319-02993-1\_13",

language = "英语",

isbn = "9783319029924",

series = "Studies in Computational Intelligence",

publisher = "Springer Verlag",

pages = "287--311",

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A novel approach on behavior of sleepy lizards based on k-nearest neighbor algorithm. / Tang, Lin Lin; Pan, Jeng Shyang; Guo, Xiaolv et al.
Social Networks: A Framework of Computational Intelligence. Springer Verlag, 2014. p. 287-311 (Studies in Computational Intelligence; Vol. 526).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - A novel approach on behavior of sleepy lizards based on k-nearest neighbor algorithm

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AU - Pan, Jeng Shyang

AU - Guo, Xiaolv

AU - Chu, Shu Chuan

AU - Roddick, John F.

PY - 2014

Y1 - 2014

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AB - The K-Nearest Neighbor algorithm is one of the commonly used methods for classification in machine learning and computational intelligence. A new research method and its improvement for the sleepy lizards based on the K-Nearest Neighbor algorithm and the traditional social network algorithms are proposed in this chapter. The famous paired living habit of sleepy lizards is verified based on our proposed algorithm. In addition, some common population characteristics of the lizards are also introduced by using the traditional social net work algorithms. Good performance of the experimental results shows efficiency of the new research method.

KW - Computational intelligence

KW - K-Nearest neighbor (KNN) algorithm

KW - Sleep lizard

KW - Social network analysis (SNA)

UR - https://www.scopus.com/pages/publications/84958546967

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BT - Social Networks

PB - Springer Verlag

ER -

A novel approach on behavior of sleepy lizards based on k-nearest neighbor algorithm

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