Librarian View
Last updated in SearchWorks on November 24, 2023 10:48pm
LEADER 05294cam a2200589Ii 4500
001
a14007179
003
SIRSI
006
m o d
007
cr cnu|||unuuu
008
160711s2016 sz a ob 001 0 eng d
035
a| (Sirsi) a14007179
040
a| GW5XE
b| eng
e| rda
e| pn
c| GW5XE
d| YDXCP
d| OCLCF
d| UAB
d| IOG
d| ESU
d| Z5A
d| JBG
d| IAD
d| ICW
d| ICN
d| OTZ
d| U3W
d| CAUOI
d| OCLCQ
d| KSU
d| UKMGB
d| OCLCQ
d| UKAHL
d| CSt
015
a| GBB8O2736
2| bnb
016
7
a| 019179950
2| Uk
020
a| 9783319351629
q| (electronic bk.)
020
a| 3319351621
q| (electronic bk.)
020
z| 9783319351605
q| (print)
024
7
a| 10.1007/978-3-319-35162-9
2| doi
035
a| (OCoLC)953418988
z| (OCoLC)962436225
037
a| com.springer.onix.9783319351629
b| Springer Nature
050
4
a| Q342
072
7
a| UYQ
2| bicssc
072
7
a| COM004000
2| bisacsh
082
0
4
a| 006.3
2| 23
049
a| MAIN
100
1
a| Zhurovsʹkyĭ, M. Z.
q| (Mykhaĭlo Zakharovych)
e| author.
245
1
4
a| The fundamentals of computational intelligence :
b| system approach /
c| Mikhail Z. Zgurovsky, Yuriy P. Zaychenko.
264
1
a| Switzerland :
b| Springer,
c| 2016.
300
a| 1 online resource (xx, 375 pages) :
b| illustrations (some color)
336
a| text
b| txt
2| rdacontent
337
a| computer
b| c
2| rdamedia
338
a| online resource
b| cr
2| rdacarrier
490
1
a| Studies in computational intelligence,
x| 1860-949X ;
v| volume 652
504
a| Includes bibliographical references and index.
588
0
a| Online resource; title from PDF title page (SpringerLink, viewed July 11, 2016).
505
0
a| Neural Networks -- . Neural Networks with Feedback and Self-organization Introduction -- Fuzzy Inference Systems and Fuzzy Neural Networks -- Application of Fuzzy Logic Systems and Fuzzy Neural Networks in Forecasting Problems in Macroeconomics and Finance -- Fuzzy Neural Networks in Classification Problems -- Inductive Modeling Method (gmdh) in Problems of Intellectual Data Analysis and Forecasting -- The Cluster Analysis in Intellectual Systems -- Genetic Algorithms and Evolutionary Programing -- Problem of Fuzzy Portfolio optimization Under Uncertainty And Its Solution With Application of Computational Intelligence Methods.
520
a| This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization - the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. .
650
0
a| Computational intelligence.
650
0
a| Neural networks (Computer science)
650
7
a| Artificial intelligence.
2| bicssc
650
7
a| Computers
x| Intelligence (AI) & Semantics.
2| bisacsh
650
7
a| Computational intelligence.
2| fast
0| (OCoLC)fst00871995
650
7
a| Neural networks (Computer science)
2| fast
0| (OCoLC)fst01036260
700
1
a| Zaychenko, Yuriy P.,
e| author.
830
0
a| Studies in computational intelligence ;
v| v. 652.
x| 1860-949X
856
4
0
z| Available to Stanford-affiliated users.
u| https://link.springer.com/10.1007/978-3-319-35162-9
x| WMS
y| SpringerLink
x| Provider: Springer
x| purchased
x| eLoaderURL
x| sp4
x| spocn953418988
994
a| 92
b| STF
596
a| 22
035
a| (Sirsi) spocn953418988
999
f
f
i| 2dd00931-7bf0-5ba1-ba70-8bcb9db9dae0
s| 393ddf4d-499e-5ab3-9181-65d47a7af9fc
Holdings JSON
{ "holdings": [ { "id": "d0abdc43-f574-5d04-8894-aa34e5ea8f0c", "hrid": "ah14007179_1", "notes": [ ], "_version": 1, "metadata": { "createdDate": "2023-08-21T21:07:00.427Z", "updatedDate": "2023-08-21T21:07:00.427Z", "createdByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766", "updatedByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766" }, "sourceId": "f32d531e-df79-46b3-8932-cdd35f7a2264", "boundWith": null, "formerIds": [ ], "illPolicy": null, "instanceId": "2dd00931-7bf0-5ba1-ba70-8bcb9db9dae0", "holdingsType": { "id": "996f93e2-5b5e-4cf2-9168-33ced1f95eed", "name": "Electronic", "source": "folio" }, "holdingsItems": [ ], "callNumberType": null, "holdingsTypeId": "996f93e2-5b5e-4cf2-9168-33ced1f95eed", "electronicAccess": [ ], "bareHoldingsItems": [ ], "holdingsStatements": [ ], "statisticalCodeIds": [ ], "administrativeNotes": [ ], "effectiveLocationId": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "permanentLocationId": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "suppressFromDiscovery": false, "holdingsStatementsForIndexes": [ ], "holdingsStatementsForSupplements": [ ], "location": { "effectiveLocation": { "id": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "code": "SUL-ELECTRONIC", "name": "online resource", "campus": { "id": "c365047a-51f2-45ce-8601-e421ca3615c5", "code": "SUL", "name": "Stanford Libraries" }, "details": { }, "library": { "id": "c1a86906-ced0-46cb-8f5b-8cef542bdd00", "code": "SUL", "name": "SUL" }, "isActive": true, "institution": { "id": "8d433cdd-4e8f-4dc1-aa24-8a4ddb7dc929", "code": "SU", "name": "Stanford University" } }, "permanentLocation": { "id": "b0a1a8c3-cc9a-487c-a2ed-308fc3a49a91", "code": "SUL-ELECTRONIC", "name": "online resource", "campus": { "id": "c365047a-51f2-45ce-8601-e421ca3615c5", "code": "SUL", "name": "Stanford Libraries" }, "details": { }, "library": { "id": "c1a86906-ced0-46cb-8f5b-8cef542bdd00", "code": "SUL", "name": "SUL" }, "isActive": true, "institution": { "id": "8d433cdd-4e8f-4dc1-aa24-8a4ddb7dc929", "code": "SU", "name": "Stanford University" } } } } ], "items": [ ] }
FOLIO JSON
{ "pieces": [ null ], "instance": { "id": "2dd00931-7bf0-5ba1-ba70-8bcb9db9dae0", "hrid": "a14007179", "notes": [ { "note": "Includes bibliographical references and index", "staffOnly": false, "instanceNoteTypeId": "86b6e817-e1bc-42fb-bab0-70e7547de6c1" }, { "note": "Online resource; title from PDF title page (SpringerLink, viewed July 11, 2016)", "staffOnly": false, "instanceNoteTypeId": "66ea8f28-d5da-426a-a7c9-739a5d676347" }, { "note": "Neural Networks -- . Neural Networks with Feedback and Self-organization Introduction -- Fuzzy Inference Systems and Fuzzy Neural Networks -- Application of Fuzzy Logic Systems and Fuzzy Neural Networks in Forecasting Problems in Macroeconomics and Finance -- Fuzzy Neural Networks in Classification Problems -- Inductive Modeling Method (gmdh) in Problems of Intellectual Data Analysis and Forecasting -- The Cluster Analysis in Intellectual Systems -- Genetic Algorithms and Evolutionary Programing -- Problem of Fuzzy Portfolio optimization Under Uncertainty And Its Solution With Application of Computational Intelligence Methods", "staffOnly": false, "instanceNoteTypeId": "5ba8e385-0e27-462e-a571-ffa1fa34ea54" }, { "note": "This monograph is dedicated to the systematic presentation of main trends, technologies and methods of computational intelligence (CI). The book pays big attention to novel important CI technology- fuzzy logic (FL) systems and fuzzy neural networks (FNN). Different FNN including new class of FNN- cascade neo-fuzzy neural networks are considered and their training algorithms are described and analyzed. The applications of FNN to the forecast in macroeconomics and at stock markets are examined. The book presents the problem of portfolio optimization under uncertainty, the novel theory of fuzzy portfolio optimization free of drawbacks of classical model of Markovitz as well as an application for portfolios optimization at Ukrainian, Russian and American stock exchanges. The book also presents the problem of corporations bankruptcy risk forecasting under incomplete and fuzzy information, as well as new methods based on fuzzy sets theory and fuzzy neural networks and results of their application for bankruptcy risk forecasting are presented and compared with Altman method. This monograph also focuses on an inductive modeling method of self-organization - the so-called Group Method of Data Handling (GMDH) which enables to construct the structure of forecasting models almost automatically. The results of experimental investigations of GMDH for forecasting at stock exchanges are presented. The final chapters are devoted to theory and applications of evolutionary modeling (EM) and genetic algorithms. The distinguishing feature of this monograph is a great number of practical examples of CI technologies and methods application for solution of real problems in technology, economy and financial sphere, in particular forecasting, classification, pattern recognition, portfolio optimization, bankruptcy risk prediction under uncertainty which were developed by authors and published in this book for the first time. All CI methods and algorithms are presented from the general system approach and analysis of their properties, advantages and drawbacks that enables practitioners to choose the most adequate method for their own problems solution. ", "staffOnly": false, "instanceNoteTypeId": "10e2e11b-450f-45c8-b09b-0f819999966e" } ], "title": "The fundamentals of computational intelligence : system approach / Mikhail Z. Zgurovsky, Yuriy P. Zaychenko.", "series": [ "Studies in computational intelligence, 1860-949X ; volume 652", "Studies in computational intelligence ; v. 652. 1860-949X" ], "source": "MARC", "_version": 1, "editions": [ ], "metadata": { "createdDate": "2023-08-21T21:04:22.221Z", "updatedDate": "2023-08-21T21:04:22.221Z", "createdByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766", "updatedByUserId": "58d0aaf6-dcda-4d5e-92da-012e6b7dd766" }, "statusId": "9634a5ab-9228-4703-baf2-4d12ebc77d56", "subjects": [ "Computational intelligence", "Neural networks (Computer science)", "Artificial intelligence", "Computers Intelligence (AI) & Semantics" ], "languages": [ "eng" ], "indexTitle": "Fundamentals of computational intelligence : system approach", "identifiers": [ { "value": "(Sirsi) a14007179", "identifierTypeId": "7e591197-f335-4afb-bc6d-a6d76ca3bace" }, { "value": "9783319351629 (electronic bk.)", "identifierTypeId": "8261054f-be78-422d-bd51-4ed9f33c3422" }, { "value": "3319351621 (electronic bk.)", "identifierTypeId": "8261054f-be78-422d-bd51-4ed9f33c3422" }, { "value": "9783319351605 (print)", "identifierTypeId": "fcca2643-406a-482a-b760-7a7f8aec640e" }, { "value": "10.1007/978-3-319-35162-9 doi", "identifierTypeId": "2e8b3b6c-0e7d-4e48-bca2-b0b23b376af5" }, { "value": "10.1007/978-3-319-35162-9", "identifierTypeId": "ebfd00b6-61d3-4d87-a6d8-810c941176d5" }, { "value": "10.1007/978-3-319-35162-9", "identifierTypeId": "1795ea23-6856-48a5-a772-f356e16a8a6c" }, { "value": "(OCoLC)953418988", "identifierTypeId": "439bfbae-75bc-4f74-9fc7-b2a2d47ce3ef" }, { "value": "(OCoLC)962436225", "identifierTypeId": "fc4e3f2a-887a-46e5-8057-aeeb271a4e56" }, { "value": "(Sirsi) spocn953418988", "identifierTypeId": "7e591197-f335-4afb-bc6d-a6d76ca3bace" } ], "publication": [ { "role": "Publication", "place": "Switzerland", "publisher": "Springer", "dateOfPublication": "2016" } ], "contributors": [ { "name": "Zhurovsʹkyĭ, M. Z. (Mykhaĭlo Zakharovych)", "primary": true, "contributorTypeId": "6e09d47d-95e2-4d8a-831b-f777b8ef6d81", "contributorTypeText": "author.", "contributorNameTypeId": "2b94c631-fca9-4892-a730-03ee529ffe2a" }, { "name": "Zaychenko, Yuriy P.", "primary": false, "contributorTypeId": "6e09d47d-95e2-4d8a-831b-f777b8ef6d81", "contributorTypeText": "author.", "contributorNameTypeId": "2b94c631-fca9-4892-a730-03ee529ffe2a" } ], "catalogedDate": "2021-09-25", "staffSuppress": false, "instanceTypeId": "6312d172-f0cf-40f6-b27d-9fa8feaf332f", "previouslyHeld": false, "classifications": [ { "classificationNumber": "Q342", "classificationTypeId": "ce176ace-a53e-4b4d-aa89-725ed7b2edac" }, { "classificationNumber": "006.3", "classificationTypeId": "42471af9-7d25-4f3a-bf78-60d29dcf463b" } ], "instanceFormats": [ ], "electronicAccess": [ { "uri": "https://link.springer.com/10.1007/978-3-319-35162-9", "name": "Resource", "linkText": "SpringerLink", "publicNote": "Available to Stanford-affiliated users", "relationshipId": "f5d0068e-6272-458e-8a81-b85e7b9a14aa" } ], "holdingsRecords2": [ ], "modeOfIssuanceId": "9d18a02f-5897-4c31-9106-c9abb5c7ae8b", "publicationRange": [ ], "statisticalCodes": [ ], "alternativeTitles": [ ], "discoverySuppress": false, "instanceFormatIds": [ "f5e8210f-7640-459b-a71f-552567f92369" ], "publicationPeriod": { "start": 2016 }, "statusUpdatedDate": "2023-08-21T21:04:22.200+0000", "statisticalCodeIds": [ ], "administrativeNotes": [ ], "physicalDescriptions": [ "1 online resource (xx, 375 pages) : illustrations (some color)" ], "publicationFrequency": [ ], "suppressFromDiscovery": false, "natureOfContentTermIds": [ ] }, "holdingSummaries": [ { "poLineId": null, "orderType": null, "orderStatus": null, "poLineNumber": null, "orderSentDate": null, "orderCloseReason": null, "polReceiptStatus": null } ] }