LEADER 01927nam 2200517 450 001 9910480266203321 005 20200929202011.0 010 $a0-271-07786-7 035 $a(CKB)3710000001000721 035 $a(OCoLC)1080549910 035 $a(MdBmJHUP)muse68683 035 $a(MiAaPQ)EBC6224401 035 $a(EXLCZ)993710000001000721 100 $a20200929d2016 ub 0 101 0 $aeng 135 $aur|||||||nn|n 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe evolution of taste in American collecting /$fRene? Brimo ; translated, edited, and with an introduction by Kenneth Haltman 210 1$aUniversity Park, Pennsylvania :$cThe Pennsylvania State University Press,$d[2016] 210 4$dİ2016 215 $a1 online resource (x, 405 pages ) 300 $aOriginally published as L'e?volution du gou?t aux E?tats-Unis d'apre?s l'histoire des collections by Rene? Brimo (Paris, 1938). 311 $a0-271-07324-1 320 $aIncludes bibliographical references (pages 433-370) and index. 330 $a"A critical translation of Rene Brimo's 1938 French study of eighteenth- and nineteenth-century patronage and art collecting in the United States"--Provided by publisher. 606 $aAesthetics 606 $aArt museums$zUnited States 606 $aArt$xCollectors and collecting$zUnited States 606 $aArt$zUnited States$xHistory 608 $aElectronic books. 615 0$aAesthetics. 615 0$aArt museums 615 0$aArt$xCollectors and collecting 615 0$aArt$xHistory. 676 $a709.73 700 $aBrimo$b Rene?$f1911-1948,$0988350 702 $aHaltman$b Kenneth$f1957- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910480266203321 996 $aThe evolution of taste in American collecting$92260099 997 $aUNINA LEADER 01681oam 2200493 450 001 9910706820303321 005 20180316104745.0 035 $a(CKB)5470000002459268 035 $a(OCoLC)982495047 035 $a(EXLCZ)995470000002459268 100 $a20170417d2017 ua 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBrackish groundwater in the United States /$fby Jennifer S. Stanton [and 10 others] 210 1$aReston, Virginia :$cU.S. Department of the Interior, U.S. Geological Survey,$d2017. 215 $a1 online resource (xii, 185 pages) $ccolor illustrations, color maps 225 1 $aProfessional paper ;$v1833 300 $a"Water Availability and Use Science Program." 320 $aIncludes bibliographical references (pages 144-157). 606 $aGroundwater$xQuality$zUnited States 606 $aBrackish waters$xQuality$zUnited States 606 $aWater-supply$zUnited States 606 $aWater resources development$zUnited States 606 $aAquifers$zUnited States 615 0$aGroundwater$xQuality 615 0$aBrackish waters$xQuality 615 0$aWater-supply 615 0$aWater resources development 615 0$aAquifers 676 $a551.490973 700 $aStanton$b Jennifer S.$01398793 712 02$aWater Availability and Use Science Program (U.S.) 712 02$aGeological Survey (U.S.), 801 0$bCUV 801 1$bCUV 801 2$bCUV 801 2$bGPO 906 $aBOOK 912 $a9910706820303321 996 $aBrackish groundwater in the United States$93515403 997 $aUNINA LEADER 03535nam 22006015 450 001 9910338246303321 005 20251116212358.0 010 $a3-030-16936-7 024 7 $a10.1007/978-3-030-16936-7 035 $a(CKB)4100000008153893 035 $a(MiAaPQ)EBC5771270 035 $a(DE-He213)978-3-030-16936-7 035 $a(PPN)236523600 035 $a(EXLCZ)994100000008153893 100 $a20190508d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMathematical Foundations of Nature-Inspired Algorithms /$fby Xin-She Yang, Xing-Shi He 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (114 pages) 225 1 $aSpringerBriefs in Optimization,$x2190-8354 311 08$a3-030-16935-9 327 $a1 Introduction to Optimization -- 2 Nature-Inspired Algorithms -- 3 Mathematical Foundations -- 4 Mathematical Analysis I -- 5 Mathematical Analysis II. 330 $aThis book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms. 410 0$aSpringerBriefs in Optimization,$x2190-8354 606 $aMathematical optimization 606 $aNumerical analysis 606 $aMarkov processes 606 $aAlgorithms 606 $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008 606 $aNumerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M14050 606 $aMarkov model$3https://scigraph.springernature.com/ontologies/product-market-codes/M27010 606 $aAlgorithms$3https://scigraph.springernature.com/ontologies/product-market-codes/M14018 615 0$aMathematical optimization. 615 0$aNumerical analysis. 615 0$aMarkov processes. 615 0$aAlgorithms. 615 14$aOptimization. 615 24$aNumerical Analysis. 615 24$aMarkov model. 615 24$aAlgorithms. 676 $a004.678015118 676 $a004.678 700 $aYang$b Xin-She$4aut$4http://id.loc.gov/vocabulary/relators/aut$0781375 702 $aHe$b Xing-Shi$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910338246303321 996 $aMathematical Foundations of Nature-Inspired Algorithms$92507101 997 $aUNINA