Nota di contenuto |
Intro -- Preface -- Contents -- Part I Introduction -- 1 Promises of Artificial Intelligence for Urban and Regional Planning and Policymaking -- 1.1 Introduction -- 1.2 Knowledge Management -- 1.2.1 Ontologies -- 1.2.2 Knowledge Networks -- 1.2.3 Rule-Based Systems -- 1.3 Case-Based Reasoning -- 1.4 Machine Learning -- 1.5 Final Remarks -- References -- Part II Advanced Approaches -- 2 Regional Knowledge: Sources, Representation and Management -- 2.1 Introduction -- 2.2 Forms of Knowledge: Potential Sources, Representation and Management Frameworks -- 2.3 Representing and Reasoning with Conscious Knowledge -- 2.3.1 The Spatials3 Project -- 2.3.2 A Case Study Example of Management of Both Conscious, Domain, and Past Experience Knowledge Modelled Within Fuzzy Logic -- 2.4 Representing and Reasoning with Preconscious and Collective Knowledge -- 2.4.1 A Case Study for Events Detection -- 2.4.2 A Case Study for Popular Touristic Tour Analysis -- 2.5 Representing and Reasoning with Objectified Knowledge -- 2.6 Conclusions -- References -- 3 Employing Case-Based Reasoning to Provide Knowledge for Sustainable Regional Development -- 3.1 Introduction -- 3.2 Literature Review -- 3.2.1 Background of Sustainable Regional Development -- 3.2.2 Overview of Case-Based Reasoning -- 3.2.3 CBR Case Retrieval Methods -- 3.3 Methodology (Developed Case-Based Reasoning Approach) -- 3.3.1 Case Entry -- 3.3.2 Case Representation and Indexing -- 3.3.3 Case/Keyword Spacing -- 3.3.4 Case Selection and Retrieving -- 3.3.5 Case Ranking -- 3.3.6 Case Adaptation and Reuse -- 3.3.7 Case Revision and Retaining -- 3.3.8 Case Resemblance for Sustainable Regional Strategies -- 3.4 Discussion -- 3.5 Conclusion -- References -- 4 Knowledge Management at Multiple Decision Levels: A Use Case About COVID-19 Pandemic -- 4.1 Introduction -- 4.2 Related Work.
4.3 Challenges of Level-Based Knowledge Management -- 4.3.1 Modelling Rules -- 4.3.2 Rule Extraction -- 4.3.3 Relationship Detection -- 4.3.4 Data Integration and Quality -- 4.4 The COVID-19 Use Case -- 4.4.1 Modelling -- 4.4.2 Rule Extraction -- 4.4.3 Relationship Detection -- 4.4.4 Integration of Heterogeneous Data -- 4.5 Conclusion -- References -- 5 Semantic Analysis of Feedforward Knowledge for Regional Policymaking -- 5.1 Introduction -- 5.2 Knowledge Management and Territorial Intelligence -- 5.2.1 Rules in Knowledge Management -- 5.2.2 Origin of Knowledge -- 5.2.3 Projects and Plans -- 5.2.4 Example of Analysis for a Regional Knowledge Bundle -- 5.2.5 Feedforward Rules -- 5.2.6 Decisional Rules -- 5.2.7 About Land Opportunities -- 5.2.8 Harbingers -- 5.3 Preliminary Aspects of Feedforward Rule Semantics -- 5.3.1 Knowledge from Local History and Geography -- 5.3.2 Technological Watch -- 5.3.3 Sociological Watching -- 5.3.4 Case-Based Reasoning and Domino Effect -- 5.3.5 Upper-Level Project Framework -- 5.3.6 From Electoral Promises to Regional Project -- 5.3.7 Modification or Cancelation of Projects -- 5.4 States of a Project -- 5.4.1 From Pure Idea to Decision-Making -- 5.4.2 Approbation -- 5.4.3 From Approbation to Opening Ceremony -- 5.4.4 About Contestation -- 5.5 Organization of Project-Oriented Knowledge -- 5.5.1 Ongoing Projects -- 5.5.2 Realized Projects -- 5.5.3 Abandoned Projects -- 5.6 Conclusions -- References -- Part III Regional Knowledge on the Move -- 6 ICT Key Points in Emerging Spatial Knowledge Systems -- 6.1 Introduction -- 6.2 From GeoSpatial Big Data to Territorial Intelligence -- 6.2.1 Spatial Internet of Things -- 6.2.2 Spatial Data Science -- 6.2.3 GeoSpatial Artificial Intelligence -- 6.2.4 Territorial Intelligence -- 6.3 Spatial Knowledge Management and Regional Policy-making.
6.3.1 Key Points in Geospatial Big Data Management -- 6.3.2 Key Points in GeoAI -- 6.3.3 Key Points in Spatial IoT: GeoAI at Edge for Geospatial Big Data -- 6.3.4 Training Professionalism -- 6.4 Final Remarks -- References -- 7 No "Prêt à Porter" but a Multi-scalar Perspective of "Smart Cities" -- 7.1 Introduction -- 7.2 What is Smart in 'Smart Cities'? -- 7.3 Which Cities Should Be Smart? -- 7.4 Three Dimensions to Represent the Intra-Urban Diversity -- 7.5 Inter-Urban Diversity: Three Systematic Expressions of Urban Diversity at Higher Spatio-Temporal Scales -- 7.5.1 Urban Hierarchy and Scaling Relationships of Urban Attributes with City Size -- 7.5.2 Specialization, Innovation Waves and Urban Trajectories -- 7.5.3 Path Dependency and Stage of Regional Urban Systems in Global Trends -- 7.6 Reconciling Urban Dynamics with Smartness -- 7.6.1 Dynamics -- 7.6.2 Sustainability Targets -- 7.6.3 Measuring -- 7.7 Conclusion -- References -- 8 Smart Cities: Missing the Stigmergy? -- 8.1 Introduction -- 8.2 The City of Information -- 8.3 The Information of Distributed Actors and Their Networks -- 8.4 The Smartness of Coordination -- 8.5 Conclusion: Exploiting Stigmergy in Smart Cities -- References -- 9 Blockchain Systems for Smart Cities and Regions: An Illustration of Self-Sovereign Data Governance -- 9.1 Smart Spatial Policy and Blockchain Systems -- 9.2 Paper Blockchain Systems in a Smart Context: Setting the Scene -- 9.3 The Wider Scope of Blockchain Technology -- 9.3.1 Financial Services: Cryptocurrencies and Transactions -- 9.3.2 Healthcare Systems -- 9.3.3 Business and Industry -- 9.3.4 Energy -- 9.3.5 Governance and the Public Sector -- 9.4 The Use of Blockchain Systems in Smart Cities and Regions -- 9.4.1 Introduction -- 9.4.2 Impediments to Blockchain Systems Adoption in Smart Cities and Regions.
9.5 Example of a Self-Sovereign Decision Support Application: Design and Operation of an Experimental Blockchain App -- 9.5.1 Preface -- 9.5.2 Design Principles of the PS-SSApp -- 9.5.3 Modus Operandi of the PS-SSApp -- 9.5.4 Test Benefits of PS-SSApp Against Design Criteria -- 9.5.5 Illustrative Applications -- 9.6 Synthesis -- 9.7 Retrospect and Prospect -- 9.8 Epilogue -- References -- 10 The Data-Driven Smart Region, Innovation and Sustainability -- 10.1 Introduction -- 10.2 Theoretical Background -- 10.2.1 From Intelligence to Sustainability: The Role of Innovation -- 10.2.2 From Innovation to Sustainability -- 10.3 Indicators of Intelligence and Urban Sustainability -- 10.4 Research Methodology -- 10.4.1 Data Base -- 10.4.2 Bivariate Interrelationships Among the Study Variables -- 10.4.3 Unsupervised Classification: K-means Clustering -- 10.5 Neural Network Learning -- 10.5.1 Neural Network -- 10.5.2 Decision Tree -- 10.5.3 Clusters and Discriminating Variables -- 10.6 Simultaneous Equation Analysis -- 10.6.1 Cross-Relationships -- 10.6.2 Regression in Simultaneous Equations -- 10.7 Conclusion -- Appendices -- Appendix 1: K-Means Classification -- A.1 Descriptives -- A.2 K-Means Algorithm for Optimal Clusters Number -- A.3 Countries by Clusters Table -- Appendix 2: Neuronal Network -- References -- Part IV Research and Knowledge Agenda -- 11 Regional Knowledge Management and Sustainable Regional Development: In Quest of a Research and Knowledge Agenda -- 11.1 Introduction -- 11.2 Setting the Scene -- 11.2.1 Objectives -- 11.2.2 Regional Concerns -- 11.2.3 Significance and Origin of Regional Knowledge -- 11.2.4 Links with the UN Sustainable Development Goals -- 11.2.5 Cross-Fertilization Between Research and Practice -- 11.2.6 Framing of the Work -- 11.3 Unveiling Characteristics of Regional Knowledge -- 11.3.1 Spatio-Temporal Knowledge.
11.3.2 Fuzzy Knowledge and Rules -- 11.3.3 Gazetteers and Places with Fuzzy Geometries -- 11.3.4 Regional Ontologies -- 11.3.5 Rule Superseding -- 11.3.6 Scalability of Regional Knowledge -- 11.3.7 Border Effects -- 11.3.8 Natural Continuous Phenomena -- 11.3.9 Locally Embodied Information -- 11.3.10 Past Rules and Actual Rules -- 11.3.11 From Urban Analytics to Regional Analytics -- 11.3.12 Feedforward Knowledge -- 11.3.13 Quality of Knowledge -- 11.3.14 Knowledge Visualization and Sharing for Reasoning -- 11.3.15 Dashboards for Real-Time Monitoring -- 11.3.16 Case-Based Reasoning -- 11.3.17 Cross-Border Regional Knowledge Continuity -- 11.3.18 Cross-Border Regional Knowledge Integration -- 11.3.19 Cross-Border Regional Interoperability or Seamless Interoperability -- 11.3.20 Dedicated Inference and Reasoning Engines -- 11.3.21 Transparency and Explicability -- 11.3.22 Extracting Knowledge and Rules from Written Documents -- 11.3.23 Configurational Ontology -- Space Syntax -- 11.3.24 Regional Knowledge and Links with SDI -- 11.3.25 Regional Knowledge Indexing -- 11.3.26 Knowledge Curation and Removal of "Fake Knowledge" -- 11.3.27 Epilogue -- 11.4 Governance and Decision-Making Based on Knowledge Management -- 11.4.1 Data Governance-Privacy, Confidentiality, Ownership -- 11.4.2 Jurisdiction and Rule Inception -- 11.4.3 Combining AI-Based Collective and Knowledge Intelligence -- 11.4.4 Formation of a Team of Professionals -- 11.4.5 Citizen Empowerment -- 11.4.6 Decision Rules -- 11.4.7 Lessons Learnt from Accepted and Abandoned Projects -- 11.4.8 Digital Twins for Regions -- 11.4.9 Border Effects, Unexpected Outcomes -- 11.4.10 Use of Knowledge to Boost Economy/Innovation -- 11.4.11 Cost of Enforcing Rules -- 11.4.12 Technological and Sociological Watching -- 11.4.13 Epilogue -- 11.5 Retrospect and Prospect -- References.
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