JACIII Vol.19 No.2 pp. 212-216
doi: 10.20965/jaciii.2015.p0212


Basic Study on the Classification of Time Series Data Using a Frequency Integrated Spherical Hidden Markov Self Organizing Map

Gen Niina, Hiroshi Dozono, and Kazuhiro Muramatsu

Faculty of Science and Engineering, Saga University
1-Honjyo, Saga 840-8502, Japan

May 13, 2014
November 21, 2014
March 20, 2015
self organizing map, hidden markov model, stock price movements
The rapid progress in and the expanding complexity of information and technology systems have made data analysis increasingly relevant. Data having a variety of elements are complex, and making very difficult to evaluate a state of a model from observed data generated probabilistically by the model. To evaluate these hidden states, we propose Spherical-Self Organizing Map (S-SOM) with a Hidden Markov Model (HMM) that infers such hidden states.
Cite this article as:
G. Niina, H. Dozono, and K. Muramatsu, “Basic Study on the Classification of Time Series Data Using a Frequency Integrated Spherical Hidden Markov Self Organizing Map,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.2, pp. 212-216, 2015.
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