Development of a self-organizing neural network for estimating environmental factors characterizing a microbial community.

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K16066
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Soft computing
• Research Institution: Ube National College of Technology
• Principal Investigator: Misawa Hideaki 宇部工業高等専門学校, 電気工学科, 准教授 (40636099)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 自己組織化ニューラルネットワーク / 異種データ統合 / 環境要因 / 微生物群集

Outline of Final Research Achievements

The objective of this research was to develop a method for analyzing microbial community data based on an extended model of the self-organizing map. We developed a new learning algorithm for self-organizing maps including relational and higher-rank self-organizing maps to estimate common factors from two data sets. The proposed method was applied to artificial data sets and its performance was confirmed. In addition, the proposed method was applied to a real microbial community data set and the possibility of applying the proposed to real data sets was confirmed.

Free Research Field

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