chacune des 7 classes a été soumise à une analyse de corrélation canonique . L'objectif est ici de ,
Un seuil fixé 5.8. UN EXEMPLE D'APPLICATION à 0,1 a été choisi pour retenir le coefficient de corrélation entre les variables d'entrée et de sortie ,
9 -Les chemins les plus rapides versus l'état des arcs E/S Chemin le plus rapide Etat du svstème l-10 1-3-7-10(1) 1-3-8-10(1) 1-3-8-10(1) 1-3-8, pp.8-9 ,
9) est de rang 3 Cependant nous observons les rangs 1 et 3 pour I'arc (4,9) Nous observons que la corrélation est positive (+o,tt; pour le rang 3 et négative (-0,i3) pour Ie rang 1. Cela signifie que le chemin 2-3-8-10 est le plus rapide si ,
S) -3 ET r(3,8) : 3 ET r(4,8) : 3 ET r(1,3) : 3 ET r(2,3) : 3 } ALORS le chemin le plus rapide est ,
8) : 1 ET r(3,8) : 1 ET r(4,8) -1 ET r(1,3) -1 ET r, pp.3-4 ,
8) -1 ET r(3,8) : 1 ET r(4,8) : 1 } ALORS Ie chemin te ptus rapide est, p.10 ,
8) : 1 ET r(3,8) : 1 ET r(4,8) -1 ET r(1,3) : 1 } ALORS ie chemin le plus rapide est, p.10 ,
1 ET r(2,4) -1 ) ALORS Ie chemin le plus rapide est, p.10 ,
1 ET r(2,5) -1 ET r(5,9) -1 } ATORS Ie chemin le plus rapide est, p.10 ,
9) t IET r(1,5) -3 ET r(2,5) -3} ATORS Ie chemin le plus rapide est ,
5) : 1 ET r(2,5) : 1 ET r(5,9) : 1 ET r(4,9) : 1) ATORS le chemin le plus rapide est ,
9) -1 ET r(1,5) + | ET r(1,4) * 1) ALORS le chemin le plus rapide est ,
10 présente les flux d'entrée et les états initiaux des arcs utilisés pour la simulation ,
11 donne Ia résultat de Ia simulation, c'est-à-dire Ie chemin le plus rapide entre chaque couple ,
1-8.5 montrent les resultats de I'algorithme HRP-1' Nous voyons que, à la fin de cet algorithme, 109 sous-réseaux sont obtenus' Les résultats de l'algorithme HRP-2 sont presentés dans les tableaux 8.6-8'10 ,
10 Sous réseaux fournis par HRP-2 pour le réseau Parisien Sous réseaux Noeuds Noeuds externes Densité ,
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