Specifications

Number of references: 24

Main heading: Mechanical properties

Controlled terms: Bending strength - Carbon carbon composites - Coal tar -

Coalescence - Compression molding - Scanning electron microscopy - Surface analysis

Uncontrolled terms: Coal tar pitch - Mass ratio - Mechanical tests - Medium

temperature - Mesocarbon microbeads - Nucleating agents - Optical microscopes -

Optical texture - Situ preparation - Thermal condensation

Classification code: 816.1 Processing of Plastics and Other Polymers - 801.3 Colloid

Chemistry - 741.1 Light/Optics - 951 Materials Science - 423 Non Mechanical

Properties and Tests of Building Materials - 415.4 Structural Materials Other Than Metal,

Plastics or Wood - 411.2 Coal Tar - 421 Strength of Building Materials; Mechanical

Properties

DOI: 10.1016/j.compositesb.2012.11.009

Database: Compendex

Accession number: 20125215845172

Title: Adaptive particle swarm optimization algorithm and its application

Authors: Feng, Lei1 ; Wei, Wei2/冯磊;魏嵬

Author affiliation:

1 Department of Information Engineering, Shaanxi Polytechnic Institute, Shaanxi, Xian'yang,

712000, China

2 School of Computer Science and Engineering, Xi'an University of Technology, Xi'an, 710048,

China

Corresponding author: Feng, L.

Source title: Journal of Software Engineering

Abbreviated source title: J. Softw. Eng.

Volume: 6

Issue: 3

Issue date: 2012

Publication year: 2012

Pages: 41-48

Language: English

ISSN: 18194311

E-ISSN: 21520941

Document type: Journal article (JA)

Publisher: Academic Journals Inc., 244, 5th avenue, No. 2218, New City, NY 10001,

United States

Abstract: The basic theories of Particle Swarm Optimization (PSO) is introduced and

illustrated with flowchart. In this study one of its improved algorithms Adaptive Particle Swarm

Optimization (APSO) is introduced. Characteristics of basic PSO algorithms are outlined. Some

methods of APSO at present were introduced and analyzed with their parameters. Limitation of

these APSO algorithms was analyzed. Pointed out that APSO algorithms can be improved with

adjustment of parameters and some other hybrid APSO are referred. Finally, pointed out