A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO

Xueping Zhang; Yawei Liu; Jiayao Wang; Haohua Du

doi:10.1007/978-3-642-13498-2_61

A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO

Xueping Zhang^*
, Yawei Liu
, Jiayao Wang
, Haohua Du

^*Corresponding author for this work

School of Cyber Science and Technology

Henan University of Technology
Fuzhou University
Information Engineering University

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

1 Scopus citations

Abstract

Spatial Clustering with Obstacles Constraints (SCOC) has been a new topic in Spatial Data Mining (SDM). Spatial Obstructed Distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose a novel Spatial Obstructed Distance using Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear Particle Swarm Optimization (PNPSO) based on Grid model to obtain obstructed distance, which is named PNPGSOD, it is not only simple and easy to actualize, but also convergent rapidly, the experimental results are provided to verify the effectiveness and practicability.

Original language	English
Title of host publication	Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings
Pages	468-475
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-13498-2_61
State	Published - 2010
Event	1st International Conference on Advances in Swarm Intelligence, ICSI 2010 - Beijing, China Duration: 12 Jun 2010 → 15 Jun 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6146 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	1st International Conference on Advances in Swarm Intelligence, ICSI 2010
Country/Territory	China
City	Beijing
Period	12/06/10 → 15/06/10

Keywords

Dynamic Nonlinear
Dynamic Piecewise Linear Chaotic Map
Grid model
Particle Swarm Optimization
Spatial Obstructed Distance

Access to Document

10.1007/978-3-642-13498-2_61

Cite this

Zhang, X., Liu, Y., Wang, J., & Du, H. (2010). A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO. In Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings (PART 2 ed., pp. 468-475). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6146 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-13498-2_61

Zhang, Xueping ; Liu, Yawei ; Wang, Jiayao et al. / A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO. Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings. PART 2. ed. 2010. pp. 468-475 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{540dfcc79e4e4423b1bffb344f24cc63,

title = "A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO",

abstract = "Spatial Clustering with Obstacles Constraints (SCOC) has been a new topic in Spatial Data Mining (SDM). Spatial Obstructed Distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose a novel Spatial Obstructed Distance using Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear Particle Swarm Optimization (PNPSO) based on Grid model to obtain obstructed distance, which is named PNPGSOD, it is not only simple and easy to actualize, but also convergent rapidly, the experimental results are provided to verify the effectiveness and practicability.",

keywords = "Dynamic Nonlinear, Dynamic Piecewise Linear Chaotic Map, Grid model, Particle Swarm Optimization, Spatial Obstructed Distance",

author = "Xueping Zhang and Yawei Liu and Jiayao Wang and Haohua Du",

year = "2010",

doi = "10.1007/978-3-642-13498-2\_61",

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booktitle = "Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings",

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Zhang, X, Liu, Y, Wang, J & Du, H 2010, A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO. in Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6146 LNCS, pp. 468-475, 1st International Conference on Advances in Swarm Intelligence, ICSI 2010, Beijing, China, 12/06/10. https://doi.org/10.1007/978-3-642-13498-2_61

A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO. / Zhang, Xueping; Liu, Yawei; Wang, Jiayao et al.
Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings. PART 2. ed. 2010. p. 468-475 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6146 LNCS, No. PART 2).

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

TY - GEN

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AU - Zhang, Xueping

AU - Liu, Yawei

AU - Wang, Jiayao

AU - Du, Haohua

PY - 2010

Y1 - 2010

N2 - Spatial Clustering with Obstacles Constraints (SCOC) has been a new topic in Spatial Data Mining (SDM). Spatial Obstructed Distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose a novel Spatial Obstructed Distance using Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear Particle Swarm Optimization (PNPSO) based on Grid model to obtain obstructed distance, which is named PNPGSOD, it is not only simple and easy to actualize, but also convergent rapidly, the experimental results are provided to verify the effectiveness and practicability.

AB - Spatial Clustering with Obstacles Constraints (SCOC) has been a new topic in Spatial Data Mining (SDM). Spatial Obstructed Distance (SOD) is the key to SCOC. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. In this paper, we propose a novel Spatial Obstructed Distance using Dynamic Piecewise Linear Chaotic Map and Dynamic Nonlinear Particle Swarm Optimization (PNPSO) based on Grid model to obtain obstructed distance, which is named PNPGSOD, it is not only simple and easy to actualize, but also convergent rapidly, the experimental results are provided to verify the effectiveness and practicability.

KW - Dynamic Nonlinear

KW - Dynamic Piecewise Linear Chaotic Map

KW - Grid model

KW - Particle Swarm Optimization

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Zhang X, Liu Y, Wang J, Du H. A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO. In Advances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings. PART 2 ed. 2010. p. 468-475. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-13498-2_61

A novel spatial obstructed distance by dynamic piecewise linear chaotic map and dynamic nonlinear PSO

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