The China Lab Guide to Megablock Urbanisms |
Autore | Johnson Jeffrey |
Pubbl/distr/stampa | New York City : , : Actar D, , 2022 |
Descrizione fisica | 1 online resource (409 pages) |
Disciplina | 711/.40951 |
Altri autori (Persone) |
BrazierCressica
LamTat |
Soggetto topico |
Architecture and state
City planning Architectural design |
ISBN | 1-63840-829-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Intro -- Foreword -- Introduction/Redefinition -- Mapping the Superblock -- 100 Superblocks -- Superblock Data Comparison -- 1.0 History -- 2.0 Urbanism -- 3.0 Policy -- 4.0 Economy -- 5.0 Society -- 6.0 Ecology -- 7.0 Export -- Acknowledgments -- Image Credits. |
Record Nr. | UNINA-9910795675003321 |
Johnson Jeffrey | ||
New York City : , : Actar D, , 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
The China Lab Guide to Megablock Urbanisms |
Autore | Johnson Jeffrey |
Pubbl/distr/stampa | New York City : , : Actar D, , 2022 |
Descrizione fisica | 1 online resource (409 pages) |
Disciplina | 711/.40951 |
Altri autori (Persone) |
BrazierCressica
LamTat |
Soggetto topico |
Architecture and state
City planning Architectural design |
ISBN | 1-63840-829-7 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Intro -- Foreword -- Introduction/Redefinition -- Mapping the Superblock -- 100 Superblocks -- Superblock Data Comparison -- 1.0 History -- 2.0 Urbanism -- 3.0 Policy -- 4.0 Economy -- 5.0 Society -- 6.0 Ecology -- 7.0 Export -- Acknowledgments -- Image Credits. |
Record Nr. | UNINA-9910815951303321 |
Johnson Jeffrey | ||
New York City : , : Actar D, , 2022 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Designing intelligent machines . Volume 2 Concepts in artificial intelligence [[electronic resource] /] / by Jeffrey Johnson and Philip Picton |
Autore | Johnson Jeffrey |
Pubbl/distr/stampa | Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 |
Descrizione fisica | 1 online resource (393 p.) |
Disciplina |
621
629.89 |
Altri autori (Persone) | PictonPhilip |
Soggetto topico |
Mechatronics - Study and teaching
Artificial intelligence Engineering design |
Soggetto genere / forma | Electronic books. |
ISBN |
1-281-07716-X
9786611077167 0-08-052976-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Concepts in Artificial Intelligence; Copyright Page; Contents; Preface; Overview of Volume 2; Chapter 1. Introduction; 1.1 Artificial intelligence in engineering; 1.2 Strong AI, weak AI and cognitive science; 7.3 Why build intelligence into machines?; 1.4 How much intelligence can be built into machines?; 1.5 What is artificial intelligence?; 1.6 How is AI applied to engineering in practice?; 1.7 The principles behind the applications; Chapter 2. Pattern recognition; 2.1 Introduction; 2.2 Theoretical foundations; 2.3 Relational patterns and graph matching
2.4 Hierarchical structure in pattern recognition 2.5 Data transformation in pattern recognition; 2.6 Pattern recognition using multidimensional data; 2.7 Multiple classifications and fuzzy sets; 2.8 Errors: non-recognition versus misclassification; 2.9 Rigorous procedures for training pattern recognizers; 2.10 Conclusion; Chapter 3. Search; 3.1 Introduction; 3.2 Tree search; 3.3 Calculus-based search; 3.4 Probabilistic search; 3.5 Conclusion; Chapter 4. Neural networks; 4.1 Introduction; 4.2 The artificial neural unit; 4.3 Pattern classification; 4.4 Feed forward networks 4.5 Learning in neural networks 4.6 Feedback networks; 4.7 Uses of the multi-layer perception; 4.8 Conclusion; Chapter 5. Scheduling; 5.1 Introduction; 5.2 Representation in scheduling; 5.3 Graphs and networks for representing scheduling problems; 5.4 Shortest paths; 5.5 Critical path analysis; 5.6 Critical path activity scheduling; 5.7 The 'travelling salesman problem'; 5.8 Intelligent scheduling; 5.9 Conclusion; Chapter 6. Reasoning; 6.1 introduction; 6.2 Reasoning with certainty; 6.3 Reasoning with uncertainty; 6.4 Conclusion; Chapter 7. Rule-based systems 7.1 Knowledge-based, rule-based and expert systems 7.2 Implementation; 7.3 Confidence levels and fuzzy rules; 7.4 Programming language and rule-based system shells; 7.5 Conclusion; Chapter 8. Learning; 8.1 Introduction; 8.2 Learning by memory; 8.3 Learning by updating parameters; 8.4 learning during execution using Bayesian updating; 8.5 learning from examples; 8.6 learning by analogy; 8.7 Learning by discovery; 8.8 Conclusion; Chapter 9. Intelligent control; 9.1 Introduction; 9.2 The broom-balancer; 9.3 Classical solution; 9.4 Neural network solution; 9.5 Genetic algorithms; 9.6 Fuzzy rules 9.7 Hierarchical control of complex systems 9.8 Conclusion: principles for intelligent control design; Chapter 10. Computer vision; 10.1 Introduction; 10.2 Abstracting information from digital images; 10.3 The nature of digital images; 10.4 Computer vision versus computer graphics; 10.5 Object recognition and measurement; 10.6 A summary of the basic techniques in computer vision; 10.7 A hierarchical architecture for computer vision; 10.8 Conclusion: computer vision in intelligent machines; Chapter 11. Integration; 11.1 An introduction to blackboard systems 11.2 The blackboard system as a development environment |
Record Nr. | UNINA-9910450552703321 |
Johnson Jeffrey | ||
Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Designing intelligent machines . Volume 2 Concepts in artificial intelligence [[electronic resource] /] / by Jeffrey Johnson and Philip Picton |
Autore | Johnson Jeffrey |
Pubbl/distr/stampa | Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 |
Descrizione fisica | 1 online resource (393 p.) |
Disciplina |
621
629.89 |
Altri autori (Persone) | PictonPhilip |
Soggetto topico |
Mechatronics - Study and teaching
Artificial intelligence Engineering design |
ISBN |
1-281-07716-X
9786611077167 0-08-052976-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Concepts in Artificial Intelligence; Copyright Page; Contents; Preface; Overview of Volume 2; Chapter 1. Introduction; 1.1 Artificial intelligence in engineering; 1.2 Strong AI, weak AI and cognitive science; 7.3 Why build intelligence into machines?; 1.4 How much intelligence can be built into machines?; 1.5 What is artificial intelligence?; 1.6 How is AI applied to engineering in practice?; 1.7 The principles behind the applications; Chapter 2. Pattern recognition; 2.1 Introduction; 2.2 Theoretical foundations; 2.3 Relational patterns and graph matching
2.4 Hierarchical structure in pattern recognition 2.5 Data transformation in pattern recognition; 2.6 Pattern recognition using multidimensional data; 2.7 Multiple classifications and fuzzy sets; 2.8 Errors: non-recognition versus misclassification; 2.9 Rigorous procedures for training pattern recognizers; 2.10 Conclusion; Chapter 3. Search; 3.1 Introduction; 3.2 Tree search; 3.3 Calculus-based search; 3.4 Probabilistic search; 3.5 Conclusion; Chapter 4. Neural networks; 4.1 Introduction; 4.2 The artificial neural unit; 4.3 Pattern classification; 4.4 Feed forward networks 4.5 Learning in neural networks 4.6 Feedback networks; 4.7 Uses of the multi-layer perception; 4.8 Conclusion; Chapter 5. Scheduling; 5.1 Introduction; 5.2 Representation in scheduling; 5.3 Graphs and networks for representing scheduling problems; 5.4 Shortest paths; 5.5 Critical path analysis; 5.6 Critical path activity scheduling; 5.7 The 'travelling salesman problem'; 5.8 Intelligent scheduling; 5.9 Conclusion; Chapter 6. Reasoning; 6.1 introduction; 6.2 Reasoning with certainty; 6.3 Reasoning with uncertainty; 6.4 Conclusion; Chapter 7. Rule-based systems 7.1 Knowledge-based, rule-based and expert systems 7.2 Implementation; 7.3 Confidence levels and fuzzy rules; 7.4 Programming language and rule-based system shells; 7.5 Conclusion; Chapter 8. Learning; 8.1 Introduction; 8.2 Learning by memory; 8.3 Learning by updating parameters; 8.4 learning during execution using Bayesian updating; 8.5 learning from examples; 8.6 learning by analogy; 8.7 Learning by discovery; 8.8 Conclusion; Chapter 9. Intelligent control; 9.1 Introduction; 9.2 The broom-balancer; 9.3 Classical solution; 9.4 Neural network solution; 9.5 Genetic algorithms; 9.6 Fuzzy rules 9.7 Hierarchical control of complex systems 9.8 Conclusion: principles for intelligent control design; Chapter 10. Computer vision; 10.1 Introduction; 10.2 Abstracting information from digital images; 10.3 The nature of digital images; 10.4 Computer vision versus computer graphics; 10.5 Object recognition and measurement; 10.6 A summary of the basic techniques in computer vision; 10.7 A hierarchical architecture for computer vision; 10.8 Conclusion: computer vision in intelligent machines; Chapter 11. Integration; 11.1 An introduction to blackboard systems 11.2 The blackboard system as a development environment |
Record Nr. | UNINA-9910783135903321 |
Johnson Jeffrey | ||
Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Designing intelligent machines . Volume 2 Concepts in artificial intelligence / / by Jeffrey Johnson and Philip Picton |
Autore | Johnson Jeffrey |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 |
Descrizione fisica | 1 online resource (393 p.) |
Disciplina |
621
629.89 |
Altri autori (Persone) | PictonPhilip |
Soggetto topico |
Mechatronics - Study and teaching
Artificial intelligence Engineering design |
ISBN |
1-281-07716-X
9786611077167 0-08-052976-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Concepts in Artificial Intelligence; Copyright Page; Contents; Preface; Overview of Volume 2; Chapter 1. Introduction; 1.1 Artificial intelligence in engineering; 1.2 Strong AI, weak AI and cognitive science; 7.3 Why build intelligence into machines?; 1.4 How much intelligence can be built into machines?; 1.5 What is artificial intelligence?; 1.6 How is AI applied to engineering in practice?; 1.7 The principles behind the applications; Chapter 2. Pattern recognition; 2.1 Introduction; 2.2 Theoretical foundations; 2.3 Relational patterns and graph matching
2.4 Hierarchical structure in pattern recognition 2.5 Data transformation in pattern recognition; 2.6 Pattern recognition using multidimensional data; 2.7 Multiple classifications and fuzzy sets; 2.8 Errors: non-recognition versus misclassification; 2.9 Rigorous procedures for training pattern recognizers; 2.10 Conclusion; Chapter 3. Search; 3.1 Introduction; 3.2 Tree search; 3.3 Calculus-based search; 3.4 Probabilistic search; 3.5 Conclusion; Chapter 4. Neural networks; 4.1 Introduction; 4.2 The artificial neural unit; 4.3 Pattern classification; 4.4 Feed forward networks 4.5 Learning in neural networks 4.6 Feedback networks; 4.7 Uses of the multi-layer perception; 4.8 Conclusion; Chapter 5. Scheduling; 5.1 Introduction; 5.2 Representation in scheduling; 5.3 Graphs and networks for representing scheduling problems; 5.4 Shortest paths; 5.5 Critical path analysis; 5.6 Critical path activity scheduling; 5.7 The 'travelling salesman problem'; 5.8 Intelligent scheduling; 5.9 Conclusion; Chapter 6. Reasoning; 6.1 introduction; 6.2 Reasoning with certainty; 6.3 Reasoning with uncertainty; 6.4 Conclusion; Chapter 7. Rule-based systems 7.1 Knowledge-based, rule-based and expert systems 7.2 Implementation; 7.3 Confidence levels and fuzzy rules; 7.4 Programming language and rule-based system shells; 7.5 Conclusion; Chapter 8. Learning; 8.1 Introduction; 8.2 Learning by memory; 8.3 Learning by updating parameters; 8.4 learning during execution using Bayesian updating; 8.5 learning from examples; 8.6 learning by analogy; 8.7 Learning by discovery; 8.8 Conclusion; Chapter 9. Intelligent control; 9.1 Introduction; 9.2 The broom-balancer; 9.3 Classical solution; 9.4 Neural network solution; 9.5 Genetic algorithms; 9.6 Fuzzy rules 9.7 Hierarchical control of complex systems 9.8 Conclusion: principles for intelligent control design; Chapter 10. Computer vision; 10.1 Introduction; 10.2 Abstracting information from digital images; 10.3 The nature of digital images; 10.4 Computer vision versus computer graphics; 10.5 Object recognition and measurement; 10.6 A summary of the basic techniques in computer vision; 10.7 A hierarchical architecture for computer vision; 10.8 Conclusion: computer vision in intelligent machines; Chapter 11. Integration; 11.1 An introduction to blackboard systems 11.2 The blackboard system as a development environment |
Record Nr. | UNINA-9910826593703321 |
Johnson Jeffrey | ||
Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Non-Equilibrium Social Science and Policy [[electronic resource] ] : Introduction and Essays on New and Changing Paradigms in Socio-Economic Thinking / / edited by Jeffrey Johnson, Andrzej Nowak, Paul Ormerod, Bridget Rosewell, Yi-Cheng Zhang |
Autore | Johnson Jeffrey |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Springer Nature, 2017 |
Descrizione fisica | 1 online resource (VIII, 232 p.) |
Disciplina | 621 |
Collana | Understanding Complex Systems |
Soggetto topico |
Sociophysics
Econophysics Social sciences Economic theory Operations research Decision making Computational complexity Social sciences—Data processing Social sciences—Computer programs Data-driven Science, Modeling and Theory Building Methodology of the Social Sciences Economic Theory/Quantitative Economics/Mathematical Methods Operations Research/Decision Theory Complexity Computational Social Sciences |
Soggetto non controllato |
Data-driven Science, Modeling and Theory Building
Methodology of the Social Sciences Economic Theory/Quantitative Economics/Mathematical Methods Operations Research/Decision Theory Complexity Computational Social Sciences Complex Systems Biotechnology Quantitative Economics Operations Research and Decision Theory Applied Dynamical Systems Behavioral economics Complex socio-economic systems Econophysics and Social Dynamics Information economy and policy informatics Paradigm shift in economic thinking Social dynamics in policy Quantitative social sciences Social research & statistics Ecological science, the Biosphere Economic theory & philosophy Operational research Management decision making Cybernetics & systems theory Computer applications in the social & behavioural sciences |
ISBN | 3-319-42424-6 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Non-Equilibrium Social Science & Policy -- Economics -- Social Psychology and Narrative Economy -- Sociology and Non-Equilibrium Social Science -- Geography far from Equilibrium -- Cities in Disequilibrium -- The Evolutionary Theory of Globalization -- Systems, Networks, and Policy -- Towards a Complexity-Friendly Policy: breaking the vicious circle of equilibrium thinking in economic and public policy -- The Information Economy -- Complexity Science & the Art of Policy Making -- The Complexity of Government -- The Room Around the Elephant: Tackling Context-Dependency in the Social Sciences -- Global Systems Science and Policy -- Index. . |
Record Nr. | UNINA-9910166955503321 |
Johnson Jeffrey | ||
Springer Nature, 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|