Evaluation of Particle Swarm Optimization Factors Using Gray Situation Decision-Making Model

DOI

10.2991/icamia-15.2015.24How to use a DOI?

Keywords

para-tank model; particle swarm optimization; gray system theory; gray situation decision making

Abstract

This study investigates three factors of the acceleration equation, i.e., acceleration constants c1 and c2 and inertia weight w, which are then used as events in particle swarm optimization for parameter optimization in the para-tank model (PTM) during rainfall–runoff simulation. The values of 0.2, 0.5, and 0.8 are respectively used to create 27 groups of situation sets using the indices of the two decision-making objectives, root mean squared error and coefficient of efficiency, in order to analyze the systematic effectiveness. After comparing the comprehensive effect measures, an optimal decision is reached when the combined effectiveness was at the highest when c1 = 0.2, c2 = 0.8, and w = 0.2 and becomes the optimal parameter value for the PTM.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Po-Yuan Hsu
AU  - Yi-Lung Yeh
PY  - 2015/12
DA  - 2015/12
TI  - Evaluation of Particle Swarm Optimization Factors Using Gray Situation Decision-Making Model
BT  - Proceedings of the 2015 International Conference on Advanced Manufacturing and Industrial Application
PB  - Atlantis Press
SP  - 96
EP  - 99
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamia-15.2015.24
DO  - 10.2991/icamia-15.2015.24
ID  - Hsu2015/12
ER  -