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, Leur distribution et leur échantillonnage, par exemple un échantillonnage uniforme discret de 10 valeurs

, On définit également les sorties

, On définit ensuite le plan expérimental initial pour l'analyse de vulnérabilité sans adaptation, dont on spécifie sa nature

, On choisit la nature des scripts de simulation (par exemple OpenMOLE)

, On choisit le type de surface de réponse à construire (actuellement uniquement par des scripts R), par exemple régression linéaire

, On choisit l'indice de vulnérabilité, par exemple Luers

, De façon à mieux expliciter les étapes, nous allons faire l'analyse de vulnérabilité d'un modèle de pairie appliqué à des simulations de 30 ans, avec une fauche par an. Nous nous intéresserons à l'analyse de vulnérabilité sans adaptation

L. Eclipse, Créer un projet vide (File New Project ; Choisir General Project

, Créer un nouveau projet pour l'analyse de vulnérabilité : FileNew Other. Choisir dans, vol.7

. Sélectionner-le-noeud, Cliquer sur ModelAgro. Clic droit "Show Properties View

, Nous allons maintenant définir les entrées et les sorties du modèle, à savoir la date de fauche en entrée et les valeurs de rendement sur 30 ans en sortie. Se placer le modèle

, Puis on lui choisira une nature (au sens type informatique : int, double, string, file), ici un entier : Clic droit New Child Type Int. On pourra également lui affecter une valeur minimale et maximale

, Autrement dit, on cherche à définir quel est l'ensemble des valeurs que peut prendre cette entrée ainsi que la probabilité associée, on choisira une distribution Uniforme discrète (i.e. juste un certain nombre défini de valeurs et chaque valeur est équiprobable) : en partant du type Int, clic droit new Sibling Discret Uniform (Figure 63)

, H29<37, vol.2, issue.3

, est-à-dire le nombre de valeur que peut prendre "Fauche1", ainsi que le minimum et le maximum pour l'échantillonnage. Noter que le domaine parcouru par l'échantillonnage doit être inclus dans le domaine possible des valeurs défini dans le Type Int. Le domaine possible des valeurs servira pour l'analyse de vulnérabilité avec adaptation, tandis que le domaine de l'échantillonnage sert pour l'analyse de vulnérabilité sans adaptation. Pour notre exemple on choisira max =160, min =169 et 10 niveaux. Faites un clic droit valider et observer le report d'un problème sur la définition du minimum et du maximum (Figure 64). Il faut en effet nécessairement que min soit inférieur ou égal à max. De manière générale, au cours de la saisie ou à la fin, on peut vérifier la validité de la saisie via le menu contextuel "Validate" qui va vérifier qu'il ne manque aucun élément, De même que pour tous les éléments de l'analyse de vulnérabilité, on renseigne les propriétés demandées dans l'onglet "Properties

, Inverser les valeurs du minimum et du maximum, puis sélectionner le modèle agro

, Ajouter une sortie : clic droit New Child Output. Nous l'appellerons "Rendement" et lui affecterons une taille de 30 éléments

. Replacez-vous-sur-le-noeud, Clic droit New Child Initial Design Of Experiment. Nous le nommerons "Doe1". Nous allons maintenant définir la nature du design (Figure 65, Choisissons un plan factoriel complet : New Child Full Factorial

, H29=3 2>*(>*, pp.2-3

. Enfin, Les valeurs des indices seront affichées à l'écran, mais seront également écrite dans un fichier "log.txt". Noter également que certaines alertes, comme par exemple l'impossibilité de discrétiser la variable fauche1 en cette étape n'ayant pas encore été suffisamment testée et mise en oeuvre préalablement, son implémentation s'est limitée à la création des classes associées, une fenêtre permet de choisir les fichiers de résultats sur lesquels on souhaite calculer les indices, vol.70