LEADER 01001nam0-22003131i-450- 001 990000954090403321 005 20080826154038.0 035 $a000095409 035 $aFED01000095409 035 $a(Aleph)000095409FED01 035 $a000095409 100 $a20001205d1964----km-y0itay50------ba 101 0 $aita 200 1 $aAppunti per il corso di "Cibernetica e teoria dell'informazione"$fredatti da M.G. Bresciani, B. Casè, G. Degli Antoni$gcon la collaborazione di P. Podini 210 $aMilano$cUniversità di Milano$d[1964?] 300 $aFogli ciclostilati. 610 0 $aTeoria dell'informazione 676 $a510.78 700 1$aBresciani,$bM.G.$0345554 702 1$aCase',$bB. 702 1$aDegli Antoni,$bGianni 702 1$aPodini,$bP. 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990000954090403321 952 $a8A-034$b10267$fFI1 959 $aFI1 996 $aAppunti per il corso di "Cibernetica e teoria dell'informazione"$9358003 997 $aUNINA LEADER 01404nam--2200409---450- 001 990001300160203316 005 20040225172845.0 010 $a88-206-4008-2 035 $a000130016 035 $aUSA01000130016 035 $a(ALEPH)000130016USA01 035 $a000130016 100 $a20031216d2001----km-y0enga50------ba 101 1 $aita$cfre 102 $aIT 105 $ay|||z|||001yy 200 1 $aAgricoltura biologica mediterranea$fGabriel Guet$gguida pratica ad uso professionale con la partecipazione del G.R.A.B.$gprefazione di Claude Aubert$g[traduzione di Domenico Tringale] 210 $aBologna$cEdagricola$dcopyr. 2001 215 $aX, 527 p.$d24 cm 225 2 $aManuali pratici di eco-agricoltura 410 0$12001$aManuali pratici di eco-agricoltura 454 1$12001$aAgricolture biologiche méditerranéenne$915307 606 0 $aColtivazione biologica 676 $a631.584 700 1$aGUET,$bGabriel$078979 702 1$aAUBERT,$bClaude 801 0$aIT$bsalbc$gISBD 912 $a990001300160203316 951 $a631.584 GUE (A)$b3620 Farm.$c631$d00092382 959 $aBK 969 $aFAR 979 $aMARIA$b10$c20031216$lUSA01$h0838 979 $aPAOLA$b90$c20040225$lUSA01$h1727 979 $aPAOLA$b90$c20040225$lUSA01$h1728 979 $aPATRY$b90$c20040406$lUSA01$h1732 996 $aAgricolture biologiche méditerranéenne$915307 997 $aUNISA LEADER 01031nam a2200301 i 4500 001 991000935699707536 005 20020507104059.0 008 930421s1987 ne ||| | eng 020 $a0444870180 035 $ab10150419-39ule_inst 035 $aLE00639381$9ExL 040 $aDip.to Fisica$bita 084 $a53.7.15 084 $a53.9.1 084 $a548 100 1 $aSangwal, Keshra$0461943 245 10$aEtching of crystals :$btheory, experiment, and application /$cKeshra Sangwal 260 $aAmsterdam :$bNorth-Holland Publ. Co.,$c1987 300 $axx, 497 p. :$bill. ;$ccm. 490 0 $aDefects in solids / S. Amelinckx, J. Nihoul ;$v15 500 $aIncludes index. 650 4$aCrystals-Etching 907 $a.b10150419$b17-02-17$c27-06-02 912 $a991000935699707536 945 $aLE006 53.9.1 SAN$g1$i2006000077194$lle006$o-$pE0.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i10180217$z27-06-02 996 $aEtching of crystals$9187596 997 $aUNISALENTO 998 $ale006$b01-01-93$cm$da $e-$feng$gne $h0$i1 LEADER 03702nam 2201081z- 450 001 9910674047703321 005 20220111 035 $a(CKB)5400000000042590 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76782 035 $a(oapen)doab76782 035 $a(EXLCZ)995400000000042590 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDynamics under Uncertainty: Modeling Simulation and Complexity 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (210 p.) 311 08$a3-0365-1576-3 311 08$a3-0365-1575-5 330 $aThe dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster-Shafer theory, etc. 517 $aDynamics under Uncertainty 606 $aMathematics & science$2bicssc 606 $aResearch & information: general$2bicssc 610 $aAES 610 $aaffective computing 610 $aAHP 610 $aapplied mathematics general 610 $aartificial emotions 610 $aBWM 610 $aBWM-I 610 $aclassification and discrimination 610 $acriteria weights 610 $aD numbers 610 $adata mining 610 $aDEMATEL 610 $adual-rotor 610 $aempathic building 610 $aensemble techniques 610 $afuzzy grey cognitive maps 610 $aFuzzy MARCOS 610 $aFuzzy PIPRECIA 610 $afuzzy sets 610 $aGARCH 610 $aKNN 610 $aLDA 610 $alinear regression 610 $aLLA 610 $alogistics 610 $aMagnetic Resonance Imaging (MRI) 610 $aMCDM 610 $amedical applications 610 $ametamodel 610 $aMIMO discrete-time system 610 $amulti-criteria 610 $amulti-criteria decision-making 610 $amulti-criteria optimization 610 $amulti-frequency excitation 610 $an/a 610 $aNDSL model 610 $anon-intrusive calculation 610 $apairwise comparisons 610 $aparameter dependence 610 $aPC 610 $aperformance comparison 610 $aprediction theory 610 $aRAFSI method 610 $arank reversal 610 $arenewable energy 610 $astackers 610 $astate feedback and output feedback 610 $aTFN 610 $aThayer's emotion model 610 $athe CCSD method 610 $athe ITARA method 610 $athe MARCOS method 610 $atheory of mathematical modeling 610 $atraffic risk 610 $awavelet transform 615 7$aMathematics & science 615 7$aResearch & information: general 700 $aPamuc?ar$b Dragan$4edt$00 702 $aMarinkovic$b Dragan$4edt 702 $aKar$b Samarjit$4edt 702 $aPamuc?ar$b Dragan$4oth 702 $aMarinkovic$b Dragan$4oth 702 $aKar$b Samarjit$4oth 906 $aBOOK 912 $a9910674047703321 996 $aDynamics under Uncertainty: Modeling Simulation and Complexity$93059536 997 $aUNINA