Tamtam Proceedings - lamsin

More documents

Recommendations

Info

110 Ellaia et al.4. Results and Concluding RemarksThe current trend in global optimization research is the combination of techniques obtainedfrom diverse penalty function methods, in order to develop more reduced gradientmethod. The RPRGA follows the above concept, by trying nonlinear programming problemof model formulation.In Morocco, the ONEP has spent in 2003 about 290 millions of DH as bill of energy tosatisfy needs of people to drinking water,this cost is always getting higher. To limit theeffect of this increasing on water production, many projects of optimization waere donefor example used commercial programs LINGO see Ref. [2] these solutions are takeninitial value in Fortran code of RPRGA for numerical applications in order to give theresults more optimal see Ref. [4].5. References[1] A. ABOUSSALEH , “Minimisation de coût de l’énergie de pompage cas du Canal haut servicedes Doukkala. ”, PFE de l’IAV-Maroc.Dec.1998.[2] Y. BEGGAR AND Y.TILAOUI, “Conception d’une Application pour l’Optimisation du Coûtd’Energie Electrique d’un Complexe d’Eau Potable. ”, PFE, EMI-Morocco. 2004.[3] R. ELLAIA AND A. ELMOUATASIM, “Random Perturbation of Reduced Gradient MethodFor Global Optimization. ”, MCO’04: <strong>Proceedings</strong> of the Fifth International Conference onComputer Sciences, Metz, France.[4] R. ELLAIA, A. ELMOUATASIM AND D.OUAZAR, “ Random Perturbation of Reduced GradientMethod for Solving Complex Drinking Water Problems. ”, Working paper, LERMA, 2004.[5] A. ELMOUATASIM AND ALI MOHAMED IBRAHIM, “Penalty Function Approach for 0-1Programming Problems. ”, To appear in Journal of Basic Applied Science (Libya) 2002.[6] R. GE AND C. HUANG, “A Continuous Approach to Nonlinear Integer Programming. ”, AppliedMathematics and Computation 34:39-60 (1989). genetic algorithms.[7] D.P. LOUCKS, J.R. STEDINGER AND D.A. HAITH, “Water resource Systems Planning andAnalysis. ”, Prentice-Hall 1981. BEM.”,TAMTAM –Tunis– 2005
IVEquations DifférentiellesDifferential Equations111
Page 5 and 6:
PréfaceOrganiser la seconde éditi
Page 7:
Comité d’organisationMohamed Abd
Page 11 and 12:
SOMMAIRE / CONTENTSI Conférences I
Page 13 and 14:
Equilibre dans un système dynamiqu
Page 15 and 16:
Arlequin method: Practical impacts
Page 17 and 18:
Application de la méthode de Gauss
Page 19:
Conférences InvitéesInvited Prese
Page 22 and 23:
4 Amara et al.1. IntroductionWe are
Page 24 and 25:
6 Amara et al.2.2. The nonlinear Na
Page 26 and 27:
8 Amara et al.4. Numerical resultsW
Page 28 and 29:
10 Auger et al.1. Introduction :Dan
Page 30 and 31:
12 Auger et al.La condition de stab
Page 32 and 33:
14 Auger et al.3.1. Taux de migrati
Page 34 and 35:
16 Auger et al.L’équilibre rapid
Page 36 and 37:
18 Auger et al.[7] BRAVO DE LA PARR
Page 38 and 39:
Quelques aspects mathématiques etn
Page 40 and 41:
22 El Alaoui Talibi M.- Modèle d
Page 42 and 43:
24 El Alaoui Talibi M.[3] M. Chamba
Page 44 and 45:
26 Habbal1. IntroductionAngiogenesi
Page 46 and 47:
28 HabbalThe pressure drop denoted
Page 48 and 49:
30 Habbaltheorem 1 There exists a N
Page 50 and 51:
32 HabbalFigure 2. Second Nash loop
Page 52 and 53:
34 Hauray et al.1. IntroductionWe a
Page 54 and 55:
36 Hauray et al.minimal time interv
Page 56 and 57:
38 Hauray et al.From this last theo
Page 58 and 59:
Approximation de l’opérateur d
Page 60 and 61:
42 LemrabetLorsque δ → 0, l’é
Page 62 and 63:
44 Lemrabetavec[∆ ∗ (δ)c = [I
Page 64 and 65:
46 Lemrabet6. Bibliographie[1] N. B
Page 66 and 67:
48 Jaafar-Belaid et al.1. Introduct
Page 68 and 69:
50 Jaafar-Belaid et al.where f(ρ)
Page 70 and 71:
52 Jaafar-Belaid et al.202040406060
Page 73:
IIContrôleControl55
Page 76 and 77:
58 Arfaoui1. IntroductionCe travail
Page 78 and 79: 60 ArfaouiLe système adjoint assoc
Page 80 and 81: 62 Arfaoui[3] H. ARFAOUI , « Comma
Page 82 and 83: 64 Benzekri et al.1. Global control
Page 84 and 85: 66 Benzekri et al.ẏ = ∂H∂x =
Page 86 and 87: 0 1 2 3 4 5 668 Benzekri et al.32.5
Page 88 and 89: 70 Akian et al.1. IntroductionWe co
Page 90 and 91: 72 Akian et al.We prove that v t+δ
Page 92 and 93: .74 Akian et al.0.0−1.0Exact solu
Page 94 and 95: 76 Bokanowski et al.1. General fram
Page 96 and 97: 78 Bokanowski et al.One interesting
Page 98 and 99: 80 Bokanowski et al.4. Numerical ex
Page 100 and 101: Sur les problèmes de contrôle opt
Page 102 and 103: 84 Metouileur lorsque u est dans L
Page 104 and 105: 86 MetouiThéorème 2 Soit ū ε le
Page 106 and 107: 88 Metoui[5] L.S. HOU, S.S. RAVINDR
Page 109 and 110: Système d’information intégré
Page 111 and 112: Gestion et modélisation des ressou
Page 123 and 124: Random perturbations of reduced gra
Page 125 and 126: Global Optimization of Water Resour
Page 127: Global Optimization of Water Resour
Page 132 and 133: 114 B. Abdelkader1. IntroductionTel
Page 134 and 135: 116 B. AbdelkaderNotons que les con
Page 136 and 137: 118 B. AbdelkaderAlors pour tout X
Page 138 and 139: 120 Bouzahir1. IntroductionWe consi
Page 140 and 141: 122 Bouzahirwhere the linear operat
Page 142 and 143: Goursat boundary value problem forh
Page 144 and 145: 126 A. Guezane-Lakoud et al.3. Func
Page 146 and 147: 128 A. Guezane-Lakoud et al.5. Exis
Page 148 and 149: ACP neuronale : application à l’
Page 150 and 151: 132 Chitroubl’approximation de la
Page 152 and 153: 134 Chitroubcompression égal à 3.
Page 154 and 155: 136 Chitroub[4] J. P. Nougier, Mét
Page 156 and 157: 138 Ferchichi et al.1. Introduction
Page 158 and 159: 140 Ferchichi et al.soit T −1 = (
Page 160 and 161: 142 Ferchichi et al.[4] G.I. BISCHI
Page 162 and 163: 144 Hafidi1. IntroductionOn étudie
Page 164 and 165: 146 Hafidia ) ∫ Ωpdx → +∞ qu
Page 166 and 167: 148 HafidiLEMME 3.2. On a lim R(θ
Page 168 and 169: 150 Lefebvre1. IntroductionSoit (X
Page 170 and 171: 152 LefebvreOn peut aussi écrire q
Page 172 and 173: 154 Lefebvre5. BibliographieD.R. Co
Page 174 and 175: 156 Meskine1. IntroductionDans le p
Page 176 and 177: 158 Meskinefaibles σ( ∏ L M ,
Page 178 and 179:
160 Meskine[12] E. YA. KHRUSLOV, L.
Page 180 and 181:
162 K. Saoudi1. IntroductionL’ét
Page 182 and 183:
164 K. Saoudice qui montre que la s
Page 184 and 185:
166 K. Saoudieton aboutit au résul
Page 186 and 187:
168 K. Saoudietc 1 + c 2 = 1 ∫(u
Page 188 and 189:
170 K. SaoudiRemarque 3.1. Du lemme
Page 190 and 191:
172 K. Saoudiet∫v(t, x) dxΩest c
Page 193:
VEstimation d’ErreursError Estima
Page 196 and 197:
178 Achchab et al.1. IntroductionDu
Page 198 and 199:
180 Achchab et al.such that}Xh 2 ={
Page 200 and 201:
182 Achchab et al.[2] B.ACHCHAB, M.
Page 202 and 203:
184 Alla et al.1. IntroductionLes e
Page 204 and 205:
186 Alla et al.3. Position du probl
Page 206 and 207:
IsoValue-0.00070533-0.000604452-0.0
Page 208 and 209:
190 Achchab et al.1. IntroductionLe
Page 210 and 211:
192 Achchab et al.où T hi/2 est le
Page 212 and 213:
IsoValue0.000933570.002800710.00840
Page 214 and 215:
196 El Dabaghi et al.1. Motivation
Page 216 and 217:
198 El Dabaghi et al.0 ≤ λ i ≤
Page 218 and 219:
200 El Dabaghi et al.Figure 4. Mail
Page 220 and 221:
Residual error estimators for the t
Page 222 and 223:
204 Kharrat et al.The step (3) need
Page 224 and 225:
206 Kharrat et al.following estimat
Page 227:
VIMécanique des FluidesFluid Mecha
Page 230 and 231:
212 Abdelwahed et al.1. Introductio
Page 232 and 233:
214 Abdelwahed et al.Ainsi, suivre
Page 234 and 235:
216 Abdelwahed et al.Figure 3. Isov
Page 236 and 237:
Procédure spectrale avec diagonali
Page 238 and 239:
220 El Guarmah et al.où Ra et P r
Page 240 and 241:
222 El Guarmah et al.M 10 20 25 35
Page 242 and 243:
Simulation de l’onde de crue via
Page 244 and 245:
226 El Dabaghi et al.de R 2 , de fr
Page 246 and 247:
228 El Dabaghi et al.INRIA-MODULEFm
Page 248 and 249:
INRIA-MODULEF230 El Dabaghi et al.I
Page 250 and 251:
232 Amoura et al.1. IntroductionFor
Page 252 and 253:
234 Amoura et al.where u = rot r ψ
Page 254 and 255:
236 Amoura et al.CURRENT FUNCTION5
Page 256 and 257:
238 Frih et al.1. IntroductionLa mo
Page 258 and 259:
240 Frih et al.et dans la fracture,
Page 260 and 261:
242 Frih et al.6. Bibliographie[1]
Page 262 and 263:
244 Hasnaoui et al.1. IntroductionL
Page 264 and 265:
246 Hasnaoui et al.On obtient alors
Page 266 and 267:
248 Hasnaoui et al.5. Conclusion et
Page 268 and 269:
250 Hernane-Boukari1. IntroductionW
Page 270 and 271:
252 Hernane-Boukarianda 3 =−11 +
Page 272 and 273:
254 Kloucha et al.1. Motivation et
Page 274 and 275:
256 Kloucha et al.Si le domaine Λ
Page 276 and 277:
INRIA-MODULEF0INRIA-MODULEF.250INRI
Page 278 and 279:
Dimensions fractales : attracteurs
Page 280 and 281:
262 Lamrini Uahabi et al.4. Attract
Page 282 and 283:
264 Lamrini Uahabi et al.l 0 = λ
Page 284 and 285:
266 Lamrini Uahabi et al.En conséq
Page 286 and 287:
Numerical analysis for the problem
Page 288 and 289:
270 El-Kyal et al.d(u) = 1 2(∇u +
Page 290 and 291:
272 El-Kyal et al.Theorem 3.1 There
Page 292 and 293:
274 Marchand et al.1. IntroductionD
Page 294 and 295:
276 Marchand et al.On remarque en p
Page 296 and 297:
278 Marchand et al.dans la formulat
Page 298 and 299:
280 Mezali et al.1. Motivation et m
Page 300 and 301:
282 Mezali et al.s’annulant sur c
Page 302 and 303:
284 Mezali et al.Temps CPUTemps Ela
Page 304 and 305:
R. Touihri & S. Ghnimi *Méthode de
Page 306 and 307:
288 Touihri et al.Les équations go
Page 308 and 309:
290 Touihri et al.Tol N It (Newt) t
Page 310 and 311:
292 Touihri et al.5. Bibliographie[
Page 313 and 314:
Décomposition de domaine pour un m
Page 315 and 316:
DDM pour les fractures 297et−→
Page 317 and 318:
DDM pour les fractures 299dont l’
Page 319 and 320:
Arlequin method: Practical impacts
Page 321 and 322:
Arlequin method 303of the Arlequin
Page 323 and 324:
Arlequin method 3052.2. Penalized A
Page 325 and 326:
Arlequin method 307refinements of t
Page 327 and 328:
Reduction methods and uncertaintypr
Page 329 and 330:
Reduction methods and uncertainty p
Page 331 and 332:
Reduction methods and uncertainty p
Page 333 and 334:
0.00e+00 1.00e−11 2.00e−11 3.00
Page 335 and 336:
Homogénéisation d’un problème
Page 337 and 338:
Problème de conduction-rayonnement
Page 339 and 340:
Problème de conduction-rayonnement
Page 341 and 342:
Equation d’Hamilton-Jacobi 3231.
Page 343 and 344:
Equation d’Hamilton-Jacobi 325qui
Page 345 and 346:
0Equation d’Hamilton-Jacobi 3272
Page 347 and 348:
Détermination du nombre de région
Page 349 and 350:
Page 351 and 352:
Page 353 and 354:
Simulation des courants de Foucault
Page 355 and 356:
Page 357 and 358:
Page 359 and 360:
Une méthode d’accélération de
Page 361 and 362:
Page 363 and 364:
Page 365 and 366:
Page 367 and 368:
Schéma SRNHS 3491. IntroductionUn
Page 369 and 370:
Schéma SRNHS 3513. Application du
Page 371 and 372:
Schéma SRNHS 3535. ConclusionLes r
Page 373 and 374:
Smoothing and compressing surfaces
Page 375 and 376:
Page 377 and 378:
Page 379 and 380:
Problème de convection en milieu p
Page 381 and 382:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0
Page 383 and 384:
Condensation de masse pour la méth
Page 385 and 386:
Condensation de masse 367montre que
Page 387 and 388:
Condensation de masse 369Le terme h
Page 389 and 390:
Condensation de masse 371Aet Qile f
Page 391:
VIIIModèles CinétiquesKinetic Mod
Page 394 and 395:
376 Ben Abdallah et al.1. Introduct
Page 396 and 397:
378 Ben Abdallah et al.where B ∓
Page 398 and 399:
380 Ben Abdallah et al.ture that th
Page 400 and 401:
382 Degond et al.1. IntroductionOn
Page 402 and 403:
384 Degond et al.q φ s (x, t)/(|q|
Page 404 and 405:
386 Degond et al.Enfin l’opérate
Page 407 and 408:
Les métaheuristiques : application
Page 409 and 410:
Les métaheuristiques 391simulé fu
Page 411 and 412:
Les métaheuristiques 393Fig. 1 Dia
Page 413 and 414:
Les métaheuristiques 395Fig.4 : R
Page 415 and 416:
Prices after capacity addition in m
Page 417 and 418:
Multi-user elastic demand communica
Page 419 and 420:
Page 421 and 422:
Page 423 and 424:
Shape optimization 4051. Introducti
Page 425 and 426:
Shape optimization 4072.1. Variatio
Page 427 and 428:
Shape optimization 409(a)(b)(c)(d)F
Page 429 and 430:
Problèmes d’optimisation en éco
Page 431 and 432:
Page 433:
Page 437 and 438:
Assimilation de données pour l’e
Page 439 and 440:
Page 441 and 442:
Page 443 and 444:
Écart à la Réciprocité et ident
Page 445 and 446:
Identification de fissures planes 4
Page 447 and 448:
Page 449 and 450:
Page 451 and 452:
Algorithme de Kohn et Vogelius 4331
Page 453 and 454:
Algorithme de Kohn et Vogelius 435l
Page 455 and 456:
Algorithme de Kohn et Vogelius 4375
Page 457 and 458:
Résolution d’un problème de Cau
Page 459 and 460:
Page 461 and 462:
Page 463 and 464:
Problème inverse géométrique 445
Page 465 and 466:
Page 467 and 468:
Page 469 and 470:
Identification de fissures 4511. In
Page 471 and 472:
−0.5 −0.4 −0.3 −0.2 −0.1
Page 473 and 474:
Application de l’algorithme deNeu
Page 475 and 476:
Complétion de données en élastic
Page 477 and 478:
Complétion de données en élastic
Page 479 and 480:
Analytic extensions on an annulus:a
Page 481 and 482:
Analytic extensions on an annulus 4
Page 483 and 484:
Analytic extensions on an annulus 4
Page 485 and 486:
−1 −0.8 −0.6 −0.4 −0.2 0
Page 487 and 488:
Cauchy problem for Laplace’s equa
Page 489 and 490:
Page 491:
Page 495 and 496:
Modélisation asymptotique des onde
Page 497 and 498:
Ondes de relief 479 uuuv 1 1 pu v
Page 499 and 500:
Ondes de relief 481( )ˆeiZw( C e D
Page 501 and 502:
Ondes de relief 4836. Bibliographie
Page 503 and 504:
Régularisation pour l’aéroacous
Page 505 and 506:
Page 507 and 508:
Page 509 and 510:
Miroir à retournement temporel 491
Page 511 and 512:
Page 513 and 514:
Page 515 and 516:
Vibro-acoustique instationnaire 497
Page 517 and 518:
Vibro-acoustique instationnaire 499
Page 519 and 520:
Ondes dans les milieux poroélastiq
Page 521 and 522:
Page 523 and 524:
Page 525 and 526:
The implicitly restarted Arnoldi me
Page 527 and 528:
¨§¨ §IRAM method 509To overcome
Page 529 and 530:
IRAM method 511The application of t
Page 531:
XIIScience du VivantLife Science513
Page 534 and 535:
516 Achchab1. IntroductionDans la m
Page 536 and 537:
518 AchchabNous montrons dans le pa
Page 538 and 539:
520 Achchab5. Bibliographie[1 ] AIE
Page 540 and 541:
522 Derbel et al.1. IntroductionLa
Page 542 and 543:
524 Derbel et al.On se propose de d
Page 544 and 545:
A Stochastic partial differential e
Page 546 and 547:
528 El Saadidiffusion process to a
Page 548 and 549:
530 El Saadiwhere δ Xi(t) is the D
Page 550 and 551:
532 El Saadi5. References[1] A. L.
Page 552 and 553:
534 Ben Miled et al.1. Introduction
Page 554 and 555:
536 Ben Miled et al.nature de l’e
Page 556 and 557:
538 Ben Miled et al.Ensuite on étu
Page 558 and 559:
Optimal spatial distribution of a b
Page 560 and 561:
542 Mchich et al.at time t. The com
Page 562 and 563:
544 Mchich et al.3∑where r = r i
Page 565:
XIIIStructureStructure547
Page 568 and 569:
550 Ayadi1. IntroductionConsider a
Page 570 and 571:
552 AyadiFor all 0 ≤ p ≤ i, P p
Page 572 and 573:
554 AyadiFigure 3. The curves above
Page 574 and 575:
Analyse mathématique et numérique
Page 576 and 577:
558 Chamekh et al.2. Modèle de tig
Page 578 and 579:
560 Chamekh et al.Γ sr(s)r(σ)Figu
Page 580 and 581:
Modélisation de l’effet dynamiqu
Page 582 and 583:
564 RahmaniI 2 étant l’identité
Page 584 and 585:
566 Rahmani• ( u 1δ1∫+ ,0u 1δ
Page 586 and 587:
Résolution d’un systéme d’ela
Page 588 and 589:
570 Saidoù u vérifie :n∑n∑j=1
Page 590 and 591:
572 SaidEn effet :∣ u(y, s) 1+α
Page 592 and 593:
Régularisation d’un problème d
Page 594 and 595:
576 Achchab et al.On définit : F +
Page 596 and 597:
578 Achchab et al.3. Estimation a p
Page 598 and 599:
Modélisation d’un pieuR. Aboulai
Page 600 and 601:
582 Aboulaich et al.Figure 1. Struc
Page 602 and 603:
584 Aboulaich et al.5. Résultats n
Page 605:
XIVThéorie des GraphesGraph Theory
Page 608 and 609:
590 Hlaoui1. IntroductionMore and m
Page 610 and 611:
592 Hlaoui3. The New Graph Represen
Page 612 and 613:
594 Hlaoui1 1 2 3 4 1 1 3 411 421 4
Page 614 and 615:
596 M. Nekri et al.1. IntroductionL
Page 616 and 617:
598 M. Nekri et al.proposés. Ces m
Page 618 and 619:
600 M. Nekri et al.cycle de longueu
Page 620 and 621:
TAMTAM -Tunis- 2005 602
Page 622 and 623:
El Guarmah, M., 218El Kacimi, A., 2
show all

Tamtam Proceedings - lamsin

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?