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Paper published in a book (Scientific congresses, symposiums and conference proceedings)
Towards Modeling and Predicting the Resilience of Ecosystems
Sousa, Tiago
In pressIn Sousa, Tiago (Ed.) Towards Modeling and Predicting the Resilience of Ecosystems
Peer reviewed
 

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Keywords :
model-driven engineering; software engineering; artificial intelligence; ecosystem resilience
Abstract :
[en] Since the Stockholm Declaration on the human environment in 1972, there has been a growing recognition of the impact of human activities on Earth's ecosystems. This has created an increasing need for modeling and predicting the resilience of ecosystems, which is crucial not only for understanding ecosystem patterns and processes but also for addressing climate change and implementing effective conservation and management strategies. Despite the importance of this issue, the intrinsic complexity of ecosystems and the lack of sufficient data present considerable challenges. To address these challenges, we propose an approach that combines model-driven engineering and artificial intelligence. Specifically, we propose a formalization for modeling and verifying ecosystem requirements, a method for synthesizing heterogeneous ecosystem resilience data, and a product line of neural network architectures adaptable to diverse properties and types of ecosystem scenarios to study. Additionally, we propose a model-driven process specification detailing the different artifacts, stakeholder roles, tasks, and model transformations of the proposed approach. This paper outlines the problem and preliminary work, presents the proposed approach, which is the current focus of an ongoing Ph.D. thesis, and discusses the future research contributions.
Disciplines :
Computer science
Author, co-author :
Sousa, Tiago ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
External co-authors :
no
Language :
English
Title :
Towards Modeling and Predicting the Resilience of Ecosystems
Publication date :
In press
Event name :
ACM/IEEE 26th International Conference on Model-Driven Engineering Languages and Systems
Event organizer :
ACM SIGSOFT, IEEE TCSE
Event place :
Västerås, Sweden
Event date :
01-10-2023 to 06-10-2023
Audience :
International
Main work title :
Towards Modeling and Predicting the Resilience of Ecosystems
Author, co-author :
Pages :
7
Peer reviewed :
Peer reviewed
Focus Area :
Sustainable Development

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