LEADER 01144nam0-22003731i-450- 001 990005420680203316 005 20010829120000.0 035 $a000542068 035 $aUSA01000542068 035 $a(ALEPH)000542068USA01 035 $a000542068 100 $a20010829d1990-------|0enac50------ba 101 $aeng 102 $aGB 105 $a||||Z 1|||| 200 1 $aInformation techynology in geography and planning$eincluding principles of GIS$fIan Bracken and Christopher Webster 210 $aLondon$cRoutledge$d1990 - 444 p.$d24 cm 606 $aGeografia fisica$2FI 620 $dLondon 676 $a910.285$v21 700 1$aBRACKEN,$bIan$0613309 701 1$aWEBSTER,$bChristopher$0613310 712 $aRoutledge 801 $aIT$bSOL$c20120104 912 $a990005420680203316 950 $aDIP.TO SCIENZE ECONOMICHE - (SA)$dDS 900 910.285 BRA$e3705 DISES 951 $a900 910.285 BRA$b3705 DISES 959 $aBK 969 $aDISES 979 $c20121027$lUSA01$h1531 979 $c20121027$lUSA01$h1612 996 $aInformation techynology in geography and planning$91142839 997 $aUNISA NUM $aUSA696 LEADER 01342nam 2200349 n 450 001 996391543503316 005 20221108062638.0 035 $a(CKB)1000000000658397 035 $a(EEBO)2240927435 035 $a(UnM)99853508 035 $a(EXLCZ)991000000000658397 100 $a19920618d1591 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 03$a[A briefe collection or epitomie of all the notable and material things contained in the hystorie of Guicchiardine$b[electronic resource] $ebeing verie necessarie for Parliament, councell, treatises, and negotiations.] 210 $a[London $cBy T. Purfoote$d1591] 215 $a[4], 51 leaves 300 $aTitle taken from caption on B1r; imprint from STC. 300 $aLeaf A1 blank, except for signature mark on recto. 300 $aImperfect; lacks title page, A2. 300 $aReproduction of the original in the Folger Shakespeare Library. 330 $aeebo-0055 607 $aItaly$xHistory$y1492-1559 700 $aGuicciardini$b Francesco$f1483-1540.$08569 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bCStRLIN 801 2$bWaOLN 906 $aBOOK 912 $a996391543503316 996 $aA briefe collection or epitomie of all the notable and material things contained in the hystorie of Guicchiardine$92301964 997 $aUNISA LEADER 03601nam 2200577Ia 450 001 9910437909203321 005 20200520144314.0 010 $a9783642302787 010 $a3642302785 024 7 $a10.1007/978-3-642-30278-7 035 $a(CKB)3390000000030182 035 $a(SSID)ssj0000746156 035 $a(PQKBManifestationID)11418636 035 $a(PQKBTitleCode)TC0000746156 035 $a(PQKBWorkID)10861986 035 $a(PQKB)10459090 035 $a(DE-He213)978-3-642-30278-7 035 $a(MiAaPQ)EBC3070873 035 $a(PPN)168316269 035 $a(EXLCZ)993390000000030182 100 $a20120913d2013 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aTowards advanced data analysis by combining soft computing and statistics /$fChristian Borgelt ...[et al.] (eds.) 205 $a1st ed. 2013. 210 $aBerlin ;$aNew York $cSpringer$dc2013 215 $a1 online resource (X, 378 p.) 225 1 $aStudies in fuzziness and soft computing,$x1434-9922 ;$v285 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a9783642302770 311 08$a3642302777 320 $aIncludes bibliographical references and author index. 327 $aFrom the Contents: Arithmetic and Distance-Based Approach to the Statistical Analysis of Imprecisely Valued Data -- Linear Regression Analysis for Interval-valued Data Based on Set Arithmetic: A Bootstrap Confidence Intervals for the Parameters of a Linear Regression Model with Fuzzy Random Variables -- On the Estimation of the Regression Model M for Interval Data -- Hybrid Least-Squares Regression Modelling Using Confidence -- Testing the Variability of Interval Data: An Application to Tidal Fluctuation.-Comparing the Medians of a Random Interval Defined by Means of Two Different L1 Metrics.-Comparing the Representativeness of the 1-norm Median for Likert and Free-response Fuzzy Scales.-Fuzzy Probability Distributions in Reliability Analysis, Fuzzy HPD-regions, and Fuzzy Predictive Distributions. 330 $aSoft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis. Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty. Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance. Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively. 410 0$aStudies in fuzziness and soft computing ;$vv. 285. 606 $aMathematical statistics$xData processing 606 $aSoft computing 615 0$aMathematical statistics$xData processing. 615 0$aSoft computing. 676 $a006.3 701 $aBorgelt$b Christian$0280169 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910437909203321 996 $aTowards advanced data analysis by combining soft computing and statistics$94200498 997 $aUNINA