LEADER 00717nam 2200241 450 001 9910294858903321 005 20181210115421.0 100 $a20181210d2018----u y0engy50 ba 101 0 $aita 102 $aIT 105 0 $a 00 200 1 $aVisabilità$eil giubileo dei malati e dei disabili$fa cura di Francesca Guarino 210 $aMilano$cFrancoAngeli$d2018 215 $a293 p.$cfot.$d20 cm 225 $aLaboratorio sociologico$ericerca empirica ed intervento sociale$v90 610 0 $aDisabilità 676 $a362.4$v22$zita 700 1$aGuarino,$bFrancesca$0509734 912 $a9910294858903321 952 $a362.4 GUA 1$b5550$fbfs 959 $aBFS 996 $aVisabilità$91540242 997 $aUNINA LEADER 04998nam 2200661Ia 450 001 9911006671003321 005 20200520144314.0 010 $a1-281-05519-0 010 $a9786611055196 010 $a0-08-053256-X 035 $a(CKB)1000000000383887 035 $a(EBL)318223 035 $a(OCoLC)190795160 035 $a(SSID)ssj0000072073 035 $a(PQKBManifestationID)11120420 035 $a(PQKBTitleCode)TC0000072073 035 $a(PQKBWorkID)10091627 035 $a(PQKB)10431408 035 $a(MiAaPQ)EBC318223 035 $a(EXLCZ)991000000000383887 100 $a19950413d1995 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aGlobal optimization methods in geophysical inversion /$fMrinal Sen and Paul L. Stoffa 210 $aAmsterdam ;$aNew York $cElsevier$dc1995 215 $a1 online resource (294 p.) 225 1 $aAdvances in exploration geophysics ;$v4 300 $aDescription based upon print version of record. 311 $a0-444-81767-0 320 $aIncludes bibliographical references (p. 269-277) and index. 327 $aFront Cover; Global Optimization Methods in Geophysical Inversion; Copyright Page; Contents; Preface; Chapter 1. Preliminary Statistics; 1.1. Random variables; 1.2. Random numbers; 1.3. Probability; 1.4. Probability distribution, distribution function and density function; 1.5. Joint and marginal probability distributions; 1.6. Mathematical expectation, moments, variances, and covariances; 1.7. Conditional probability; 1.8. Monte Carlo integration; 1.9. Importance sampling; 1.10. Stochastic processes; 1.11. Markov chains 327 $a1.12. Homogeneous, inhomogeneous, irreducible and aperiodic Markov chains1.13. The limiting probability; Chapter 2. Direct, Linear and Iterative-linear Inverse Methods; 2.1. Direct inversion methods; 2.2. Model based inversion methods; 2.3. Linear/linearized inverse methods; 2.4. Iterative linear methods for quasi-linear problems; 2.5. Bayesian formulation; 2.6. Solution using probabilistic formulation; 2.7. Summary; Chapter 3. Monte Carlo Methods; 3.1. Enumerative or grid search techniques; 3.2. Monte Carlo inversion; 3.3. Hybrid Monte Carlo-linear inversion 327 $a3.4. Directed Monte Carlo methodsChapter 4. Simulated Annealing Methods; 4.1. Metropolis algorithm; 4.2. Heat bath algorithm; 4.3. Simulated annealing without rejected moves; 4.4. Fast simulated annealing; 4.5. Very fast simulated reannealing; 4.6. Mean; 4.7. Using SA in geophysical inversion; 4.8. Summary; Chapter 5. Genetic Algorithms; 5.1. A classical GA; 5.2. Schemata and the fundamental theorem of genetic algorithms; 5.3. Problems; 5.4. Combining elements of SA into a new GA; 5.5. A mathematical model of a GA; 5.6. Multimodal fitness functions, genetic drift; 5.7. Uncertainty estimates 327 $a5.8. Evolutionary programming5.9. Summary; Chapter 6. Geophysical Applications of SA and G A; 6.1. 1-D Seismic waveform inversion; 6.2. Pre-stack migration velocity estimation; 6.3. Inversion of resistivity sounding data for 1-D earth models; 6.4. Inversion of resistivity profiling data for 2-D earth models; 6.5. Inversion of magnetotelluric sounding data for 1-D earth models; 6.6. Stochastic reservoir modeling; 6.7. Seismic deconvolution by mean field annealing and Hopfield network; Chapter 7. Uncertainty Estimation; 7.1. Methods of Numerical Integration 327 $a7.2. Simulated annealing: The Gibbs' sampler7.3. Genetic algorithm: The parallel Gibbs' sampler; 7.4. Numerical examples; 7.5. Summary; References; Subject Index 330 $aOne of the major goals of geophysical inversion is to find earth models that explain the geophysical observations. Thus the branch of mathematics known as optimization has found significant use in many geophysical applications. Both local and global optimization methods are used in the estimation of material properties from geophysical data. As the title of the book suggests, the aim of this book is to describe the application of several recently developed global optimization methods to geophysical problems. The well known linear and gradient based optimization methods have been summari 410 0$aAdvances in exploration geophysics ;$v4. 606 $aGeological modeling 606 $aGeophysics$xMathematical models 606 $aInverse problems (Differential equations) 606 $aMathematical optimization 615 0$aGeological modeling. 615 0$aGeophysics$xMathematical models. 615 0$aInverse problems (Differential equations) 615 0$aMathematical optimization. 676 $a550/.1/13 700 $aSen$b Mrinal K$01714149 701 $aStoffa$b Paul L.$f1948-$0530386 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911006671003321 996 $aGlobal optimization methods in geophysical inversion$94392111 997 $aUNINA LEADER 01514nam0 22003611i 450 001 UON00464662 005 20231205105139.25 100 $a20160211d1959 |0itac50 ba 101 $afre 102 $aFR 105 $a|||| ||||| 200 1 $aHamlet$aOthello ; Macbeth$fShakespeare$gtraductions de Yves Bonnefoy, Armand Robin et Pierre Jean Jouve ;notes des traducteurs$gnotices de Jacques Vallette 210 $aParis$cLe Livre de Poche$d1959 215 $a509 p.$d17 cm. 316 $aValore stimato$5IT-UONSI Francese1 L.P.SHA/1 410 1$1001UON00461392$12001 $aˆLe ‰livre de poche$1210 $aParis$v1265-1266 620 $aFR$dParis$3UONL002984 700 1$aShakespeare$bWilliam$3UONV006939$0132200 702 1$aBonnefoy$bYves$3UONV000007 702 1$aJOUVE$bPierre-Jean$3UONV121010 702 1$aROBIN$bArmand$3UONV198731 702 1$aVALLETTE$bJean$3UONV230317 712 $aLivre de poche$3UONV253545$4650 790 0$aSAIKSPI'IR$zShakespeare, William$3UONV090012 790 1$a?EKSPIR, Vilijam$zShakespeare, William$3UONV229123 790 1$aSHEKSPIR, Uiliam$zShakespeare, William$3UONV285540 801 $aIT$bSOL$c20250627$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00464662 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI 1 L.P. 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