Using Bayesian Network for Monetary Structure and Supply Researching

DOI

10.2991/etmhs-16.2016.130How to use a DOI?

Keywords

Monetary Supply; Monetary Structure; Bayesian Network

Abstract

In this paper, we use Bayesian network structure learning method, K2 and MCMC, to build a monetary network and for making the data more visible we also use Gephi to draw the net. In the end, we get 174 nodes and 1443 lines about the macroeconomic targets and find the main factors has influence on monetary structure and flowing amount.

Copyright

© 2016, 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  - Xu Zhang
AU  - Ruihai Zhu
AU  - Luo Jun Luo Jun
PY  - 2016/01
DA  - 2016/01
TI  - Using Bayesian Network for Monetary Structure and Supply Researching
BT  - Proceedings of the 2016 2nd International Conference on Education Technology, Management and Humanities Science
PB  - Atlantis Press
SP  - 582
EP  - 585
SN  - 2352-5398
UR  - https://doi.org/10.2991/etmhs-16.2016.130
DO  - 10.2991/etmhs-16.2016.130
ID  - Zhang2016/01
ER  -