Development of a self-organizing neural network for estimating environmental factors characterizing a microbial community.
| Project/Area Number |
15K16066
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Soft computing
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| Research Institution | Ube National College of Technology |
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Principal Investigator |
Misawa Hideaki 宇部工業高等専門学校, 電気工学科, 准教授 (40636099)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| 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 / 自己組織化ネットワーク / 自己組織化マップ / 微生物群集解析 |
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| 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.
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Report
(4 results)
Research Products
(3 results)
