LEADER 01305nam0-22003851i-450- 001 990003144370403321 035 $a000314437 035 $aFED01000314437 035 $a(Aleph)000314437FED01 035 $a000314437 100 $a20000920d1991----km-y0itay50------ba 101 0 $aita 102 $aIT 200 1 $aNuove imprese e rapporti tra imprese$eL'esperienza della legge 44$fa cura del Comitato per lo sviluppo di nuova imprenditorialità giovanile, legge 44$f86. 210 $aTorino$cIsedi$d1991. 215 $aVII, 197 p.$d24 cm 225 1 $aCreazione d'impresa$v2 300 $a[Studio curato dal CLES] 610 0 $aCooperazione industriale$aCasi internazionali 610 0 $aDistretti industriali 610 0 $aImprese$aAccordi e alleanze 610 0 $aImprese tutors$aLegge 44/86 676 $aG/3.330 676 $aG/3.342 676 $aH/2.14 712 2$aComitato per lo sviluppo di nuova imprenditorialità giovanile, legge 44/86 712 2$aCentro di ricerche e studi sui problemi del lavoro, dell'economia e dello sviluppo 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003144370403321 952 $aH/2.14 COM/2$b14043$fSES 959 $aSES 996 $aNuove imprese e rapporti tra imprese$9455849 997 $aUNINA DB $aING01 LEADER 00939nam a22002531i 4500 001 991000168089707536 005 20040727173211.0 008 040802s1972 it a||||||||||||||||ita 035 $ab13185378-39ule_inst 035 $aARCHE-113798$9ExL 040 $aBiblioteca Interfacoltà$bita$cA.t.i. 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Pandora Sicilia s.r.l. 082 04$a920.9 100 1 $aCarpi, Pier$0489271 245 10$aCagliostro il taumaturgo /$cPier Carpi 260 $aTorino :$bMEB,$cstampa 1972 300 $a258 p. :$bill. ;$c22 cm 440 0$aMondi sconosciuti ;$v5 600 14$aCagliostro, Alessandro$c(Conte di) 907 $a.b13185378$b02-04-14$c05-08-04 912 $a991000168089707536 945 $aLE002 Fondo Giudici N 1044$g1$iLE002G-13825$lle002$nC. 1$o-$pE0.00$q-$rn$so $t0$u0$v0$w0$x0$y.i13826839$z05-08-04 996 $aCagliostro il taumaturgo$91101915 997 $aUNISALENTO 998 $ale002$b05-08-04$cm$da $e-$fita$git $h0$i1 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