Modélisation et simulation des systèmes distribués par automates cellulaires (application en écologie)

Le travail réalisé dans cette thèse concerne la modélisation, l'analyse et la simulation par les automates cellulaires de certaines classes de systèmes à paramètres répartis. Les notions d'étalabilité, d'identification et d'estimation de paramètres y sont traités. Une application en écologie à une dynamique de végétation y est développée. Plusieurs simulations ont été effectuées en utilisant aussi bien des logiciels de calcul formel que des programmes spécifiques écrits essentiellement en C++PERPIGNAN-BU Sciences (661362101) / SudocSudocFranceF

Cellular automata and controllability problem

International audienc

Analyse et contrôle par automates cellulaires

International audienc

OpenAIRE Research Graph Dump

Manghi P, Atzori C, Bardi A, et al. OpenAIRE Research Graph Dump. OpenAIRE; 2021.The OpenAIRE Research Graph is exported as several dumps, so you can download the parts you are interested into. publication_[part].tar: metadata records about research literature (includes types of publications listed here) dataset.tar: metadata records about research data (includes the subtypes listed here)  software.tar: metadata records about research software (includes the subtypes listed here) otherresearchproduct.tar: metadata records about research products that cannot be classified as research literature, data or software (includes types of products listed here) organization.tar: metadata records about organizations involved in the research life-cycle, such as universities, research organizations, funders., datasource.tar: metadata records about providers whose content is available in the OpenAIRE Research Graph. They includes institutional and thematic repositories, journals, aggregators, funders' databases. project.tar: metadata records about projects funded by a given funder. relation_[part].tar: metadata records about relations between entities in the graph. communities_infrastructures.tar: metadata records about research communities and research infrastructures Each file is a tar archive containing gz files, each with one json per line. Each json is compliant to the schema available at http://doi.org/10.5281/zenodo.4723403. Learn more about the OpenAIRE Research Graph at https://graph.openaire.eu. Discover the content of the graph on OpenAIRE EXPLORE and our API for developers. Version 3.

OpenAIRE Covid-19 publications, datasets, software and projects metadata.

Bardi A, Kuchma I, Pavone G, et al. OpenAIRE Covid-19 publications, datasets, software and projects metadata. OpenAIRE; 2021.This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the [OpenAIRE COVID-19 Gateway](https://covid-19.openaire.eu/), identified via full-text mining and inference techniques applied to the [OpenAIRE Research Graph](https://graph.openaire.eu). The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a tar archive containing gzip files with one json per line. Each json is compliant to the schema available at [https://doi.org/10.5281/zenodo.4723499](https://doi.org/10.5281/zenodo.4723499). &nbsp;</p

OpenAIRE Covid-19 publications, datasets, software and projects metadata

Bardi A, Kuchma I, Brobov E, et al. OpenAIRE Covid-19 publications, datasets, software and projects metadata. Zenodo; 2020.This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the OpenAIRE COVID-19 Gateway (https://covid-19.openaire.eu/), identified via full-text mining and inference techniques applied to the OpenAIRE Research Graph (https://explore.openaire.eu/). The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a gzip file containing one json per line. Each json is compliant to the schema available at https://doi.org/10.5281/zenodo.3974226