Machine learning in agroecology: From simulation models to co-existence rules - Couverture souple

Trajanov, Aneta

 
9783845471334: Machine learning in agroecology: From simulation models to co-existence rules
Couverture souple
ISBN 10 : 3845471336 ISBN 13 : 9783845471334
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

Simulation models are a widely used tool for modelling systems for which it is hard to obtain real data. However, the simulation models are usually complex and it is not an easy task to induce new knowledge and find relationships and dependencies among different parts of the simulation model. Previous attempts to analyze the outputs from simulation models were mainly focused on speeding up the simulation process. In this monograph we are proposing a methodology for analyzing results of complex simulation models. The methodology combines simulation outputs, background knowledge, and machine learning, to obtain new and interesting knowledge about a certain problem of interest. We apply our methodology to three different simulation models that simulate the co-existence between genetically-modified and conventional crops at different levels. The induced machine learning models provide us with new co-existence knowledge about the positive and negative influences on the co-existence between genetically-modified and conventional crops. The results encourage us to try the same methodology on different types of simulation models and different scientific areas.

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Présentation de l'éditeur

Simulation models are a widely used tool for modelling systems for which it is hard to obtain real data. However, the simulation models are usually complex and it is not an easy task to induce new knowledge and find relationships and dependencies among different parts of the simulation model. Previous attempts to analyze the outputs from simulation models were mainly focused on speeding up the simulation process. In this monograph we are proposing a methodology for analyzing results of complex simulation models. The methodology combines simulation outputs, background knowledge, and machine learning, to obtain new and interesting knowledge about a certain problem of interest. We apply our methodology to three different simulation models that simulate the co-existence between genetically-modified and conventional crops at different levels. The induced machine learning models provide us with new co-existence knowledge about the positive and negative influences on the co-existence between genetically-modified and conventional crops. The results encourage us to try the same methodology on different types of simulation models and different scientific areas.

Biographie de l'auteur

After completing her B.Sc. degree in computer science, Aneta Trajanov joined the Department of Knowledge Technologies at Jozef Stefan Institute in Ljubljana, Slovenia, as a research assistant. Her research interests are in analyzing the results of complex ecological simulation models with machine learning, for which she got a PhD degree.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3845471336
ISBN 13 
9783845471334
Reliure
Broché
Nombre de pages
140
Coordonnées du fabricant
non disponible
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