wonkee hong (5 resultados)

Paperback. Condición: new. Paperback. 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 beamsMulti-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithmOffers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loadsHeavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codesThe 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. This introduces artificial neural network-based Lagrange optimization techniques for structural design in prestressed concrete based on Eurocode 2 and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. ANN-based design charts show how to use the Lagrange multiplier method. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: new. Paperback. This book introduces an autodesignbased optimization for building frames using an artificial neural network (ANN)based Lagrange method and novel genetic algorithm (GA). The work of great mathematician JosephLouis Lagrange and ANNs are merged to identify parameters that optimize structural frames of reinforced concrete, prestressed concrete, and steel frames subject to one or more design constraints. New features for enhancing conventional GA are also demonstrated to optimize structural frames.New features for optimizing multiple design targets of the building frames are highlighted, while design requirements imposed by codes are automatically satisfied. Chapters provide readers with an understanding of how both ANNbased and novel GAbased structural optimization can be implemented in holistically optimizing designated design targets for building structural frames, guiding readers toward more rational designs that is consistent with American Institute of Steel Construction (AISC) and American Concrete Institute (ACI) standards. ANNbased holistic designs of multistory frames in general and reinforced concrete, prestressed concrete, and steel frames in particular, are introduced. This book suits structural engineers, architects, and graduate students in the field of building frame designs and is heavily illustrated with color figures and tables. This book introduces an auto-design-based optimization for building frames using an artificial neural networks (ANN)-based Lagrange method and genetic algorithms (GAs), and consistent with codes of practice. It is heavily illustrated with color figures and tables. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: new. Paperback. 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 beamsMulti-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithmOffers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loadsHeavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codesThe 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. This introduces artificial neural network-based Lagrange optimization techniques for structural design in prestressed concrete based on Eurocode 2 and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. ANN-based design charts show how to use the Lagrange multiplier method. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. This book introduces an autodesignbased optimization for building frames using an artificial neural network (ANN)based Lagrange method and novel genetic algorithm (GA). The work of great mathematician JosephLouis Lagrange and ANNs are merged to identify parameters that optimize structural frames of reinforced concrete, prestressed concrete, and steel frames subject to one or more design constraints. New features for enhancing conventional GA are also demonstrated to optimize structural frames.New features for optimizing multiple design targets of the building frames are highlighted, while design requirements imposed by codes are automatically satisfied. Chapters provide readers with an understanding of how both ANNbased and novel GAbased structural optimization can be implemented in holistically optimizing designated design targets for building structural frames, guiding readers toward more rational designs that is consistent with American Institute of Steel Construction (AISC) and American Concrete Institute (ACI) standards. ANNbased holistic designs of multistory frames in general and reinforced concrete, prestressed concrete, and steel frames in particular, are introduced. This book suits structural engineers, architects, and graduate students in the field of building frame designs and is heavily illustrated with color figures and tables. This book introduces an auto-design-based optimization for building frames using an artificial neural networks (ANN)-based Lagrange method and genetic algorithms (GAs), and consistent with codes of practice. It is heavily illustrated with color figures and tables. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. 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 beamsMulti-objective optimizations (MOO) of prestressed concrete beams are performed using an ANN-based Lagrange algorithmOffers a Pareto frontier using an ANN-based MOO for composite beams and composite columns sustaining multi-biaxial loadsHeavily illustrated in color and with diverse practical design examples in line with EC2, ACI, and ASTM codesThe 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. This introduces artificial neural network-based Lagrange optimization techniques for structural design in prestressed concrete based on Eurocode 2 and composite structures based on American Institute of Steel Construction and American Concrete Institute standards. ANN-based design charts show how to use the Lagrange multiplier method. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.