eBook
Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures
| Τίτλος: | Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures |
|---|---|
| Περιγραφή: | This book introduces artificial neural network (ANN)-based Lagrange optimization techniques for a structural design of prestressed concrete structures based on Eurocode 2, and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. The book provides robust design charts for prestressed concrete structures, which are challenging to achieve using conventional design methods.Using ANN-based design charts, the holistic design of a post-tensioned beam is performed to optimize design targets (objective functions), while calculating 21 forward outputs, in arbitrary sequences, from 21 forward inputs. Applies the powerful tools of ANN to the optimization of prestressed concrete structures and composite structures including columns and beams Multi-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithm Offers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loads Heavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codes The book offers optimal solutions for structural designers and researchers, enabling readers to construct design charts to minimize their own design targets under various design requirements based on any design code. |
| Συγγραφείς: | Won‐Kee Hong |
| Resource Type: | eBook. |
| Θέματα: | Structural design--Data processing, Concrete construction, Neural networks (Computer science), Prestressed concrete |
| Categories: | TECHNOLOGY & ENGINEERING / Structural, COMPUTERS / Data Science / Neural Networks |
| Βάση Δεδομένων: | eBook Index |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: edsebk DbLabel: eBook Index An: 3657394 RelevancyScore: 969 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 968.509704589844 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures – Name: Abstract Label: Description Group: Ab Data: This book introduces artificial neural network (ANN)-based Lagrange optimization techniques for a structural design of prestressed concrete structures based on Eurocode 2, and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. The book provides robust design charts for prestressed concrete structures, which are challenging to achieve using conventional design methods.Using ANN-based design charts, the holistic design of a post-tensioned beam is performed to optimize design targets (objective functions), while calculating 21 forward outputs, in arbitrary sequences, from 21 forward inputs. Applies the powerful tools of ANN to the optimization of prestressed concrete structures and composite structures including columns and beams Multi-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithm Offers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loads Heavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codes The book offers optimal solutions for structural designers and researchers, enabling readers to construct design charts to minimize their own design targets under various design requirements based on any design code. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Won‐Kee+Hong%22">Won‐Kee Hong</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Structural+design--Data+processing%22">Structural design--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Concrete+construction%22">Concrete construction</searchLink><br /><searchLink fieldCode="DE" term="%22Neural+networks+%28Computer+science%29%22">Neural networks (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Prestressed+concrete%22">Prestressed concrete</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22TECHNOLOGY+%26+ENGINEERING+%2F+Structural%22">TECHNOLOGY & ENGINEERING / Structural</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Neural+Networks%22">COMPUTERS / Data Science / Neural Networks</searchLink> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=3657394 |
| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 624.18340285 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Structural design--Data processing Type: general – SubjectFull: Concrete construction Type: general – SubjectFull: Neural networks (Computer science) Type: general – SubjectFull: Prestressed concrete Type: general Titles: – TitleFull: Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Won‐Kee Hong – PersonEntity: Name: NameFull: Won‐Kee Hong IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2023 – D: 11 M: 01 Type: profile Y: 2024 Identifiers: – Type: isbn-print Value: 9781032408088 – Type: isbn-print Value: 9781032408095 – Type: isbn-electronic Value: 9781000913897 – Type: isbn-electronic Value: 9781000913934 – Type: isbn-electronic Value: 9781003354796 Titles: – TitleFull: Artificial Neural Network-based Designs of Prestressed Concrete and Composite Structures Type: main |
| ResultId | 1 |