Automated modelling of lakes from data and expert knowledge: evaluation of applications
- Authors: Nataša ATANASOVA
- Citation: Acta hydrotechnica, vol. 24, no. 40, pp. 21-43, 2006.
- Abstract: Ecological models of lakes are useful tools for a better understanding of the ecosystem behaviour, lake management, policy making, as well as testing and accepting engineering solutions. Setting such model is a difficult task due to the complexity of these ecosystems. Therefore it is reasonable to use as many approaches as possible to construct a reliable model of the observed domain. In this paper the evaluation of an automated modelling method, called Lagramge, that combines the two basic approaches, i.e. data-driven (inductive) approach and knowledge-driven (deductive) approach, is given. The method supports the introduction of domain knowledge in the procedure of equation discovery from measured data, where the domain modelling knowledge is introduced in a form of modelling knowledge library. Four applications of the method, i.e. Lake Glumsø, Lake Bled, Lake Kasumigaura, and Greifensee, comprise different modelling tasks for Lagramge, each of them resulting in a specific model of the observed domains. The models are evaluated in terms of their descriptive power and their performance (goodness of fit to the measurements). Although faced with some constraints, the method can be successfully used in complex domains. It can be used successfully for model discovery as well as for other scientific discoveries, such as identifying dynamic patterns in the observed system, i.e. dynamic structure of the ecosystem.
- Keywords: lakes, automated modelling, Lagramge, modelling knowledge library, conceptual modelling, data-driven modelling
- Full text: a40na.pdf