e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

You can access and play with the graphs:

Discover all records
Home page

Title

A Preliminary Analysis for Improving Model Structure of Fuzzy Habitat Preference Model for Japanese Medaka (Oryzias latipes)

en
Abstract

The present study examined a preliminary analysis for improving model structure of fuzzy habitat preference model for Japanese medaka (Oryzias latipes) dwelling in agricultural canals in Japan. The present model employed a simplified fuzzy reasoning method for evaluating habitat preference of the fish based on the relationship with physical habitat characteristics observed in the field survey. The model parameter was optimized by using a simple genetic algorithm, in which number of fuzzy membership function was fixed. In the present analysis, number of fuzzy membership function was changed while the other methods were fixed as the original model. The model performance was evaluated based on mean square error between observed and predicted fish population density, and by using two different data sets. As a result, there was no clear tradeoff between number of fuzzy membership functions and prediction accuracy. By contrast, calibration and validation results showed a slight tendency of tradeoff. Further studies on clarifying the tradeoffs would be necessary for improving the model structure in an effective way.

en
Year
2009
en
Country
  • JP
Organization
  • Kyushu_Univ (JP)
Data keywords
  • reasoning
en
Agriculture keywords
  • agriculture
en
Data topic
  • big data
  • modeling
en
SO
PROCEEDINGS OF THE JOINT 2009 INTERNATIONAL FUZZY SYSTEMS ASSOCIATION WORLD CONGRESS AND 2009 EUROPEAN SOCIETY OF FUZZY LOGIC AND TECHNOLOGY CONFERENCE
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
    uid:/8KBQJ115
    Powered by Lodex 8.20.3
    logo commission europeenne
    e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
    Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.