An Adaptive Modeling Technique for Instream Fish Habitat Preference of Japanese Medaka (Oryzias Latipes)
-
- Fukuda Shinji
- Graduate School of Bioresource and Bioenvironmental Sciences
-
- Hiramatsu Kazuaki
- Faculty of Agriculture, Kyushu Unviersity
-
- Mori Makito
- Faculty of Agriculture, Kyushu Unviersity
-
- Shikasyo Shiomi
- Professor Emeritus of Kyushu University
Search this article
Abstract
It is widely known that habitat selections of riverine fish differ within and between rivers. In our past study, the preference intensity of Japanese Medaka (Oryzias latipes) to three environmental factors of water depth, current velocity and cover ratio was quantified on laboratory open-channel experiments for developing a general habitat preference model. A simplified fuzzy reasoning method was introduced in consideration of essential vagueness of fish behaviors. The fuzzy preference intensity model was then optimally searched with a simple genetic algorithm and was successfully verified by both labotory water tank experiments and on-the-spot examination. The results indicated that this general model showed agreement between predicted and observed spatial distribution of target fish, but the habitat preference models are still desired to be developed through field studies. In this study, we propose and adaptive modeling technique for instream fish habitat preference by conjugating the fish preference intensify model developed in laboratory experiments. The adaptive prediction model was also determined by simple genetic algorithm, which enabled us to model the habitat preference of instream resident fosh with insufficient data.
Journal
-
- Journal of the Faculty of Agriculture, Kyushu University
-
Journal of the Faculty of Agriculture, Kyushu University 50 (2), 363-373, 2005-10-01
Faculty of Agriculture, Kyushu University
- Tweet
Keywords
Details 詳細情報について
-
- CRID
- 1390853649613911808
-
- NII Article ID
- 110004030897
-
- NII Book ID
- AA00247166
-
- DOI
- 10.5109/4649
-
- HANDLE
- 2324/4649
-
- ISSN
- 00236152
-
- Text Lang
- en
-
- Data Source
-
- JaLC
- IRDB
- Crossref
- CiNii Articles