09825nam 2200445 450 991078839160332120230802133950.01-78906-265-9(MiAaPQ)EBC30374760(Au-PeEL)EBL30374760(CKB)27531977000041(EXLCZ)992753197700004120230802d2022 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMichael Abbott's Hydroinformatics Poiesis of New Relationships with Water /edited by Andreja JonoskiFirst edition.London :IWA Publishing,[2022]©20221 online resource (249 pages)Print version: Jonoski, Andreja Michael Abbott's Hydroinformatics: Poiesis of New Relationships with Water London : IWA Publishing,c2022 Cover -- Contents -- Editorial -- Preface -- Chapter 1 : Revisiting the motives for hydroinformatics -- 1.1   Introduction -- 1.2   Engineering Roots of Hydroinformatics -- 1.3   Modelling at the Centre of Hydroinformatics -- 1.4   Hydroinformatics: From Technology to Sociotechnology -- 1.5   Decision Support and Hydroinformatics -- 1.6   Hydroinformatics and the Virtual World -- 1.7   Role of Hydroinformaticians -- References -- Chapter 2 : Computational hydraulics: stage for the hydroinformatics act -- 2.1   Introduction -- 2.1.1   Historical context -- 2.2   Role of Characteristics in Computational Hydraulics -- 2.2.1   The meaning of characteristics -- 2.2.2   The three- and four-point method of characteristics -- 2.2.3   Practical aspects of characteristics -- 2.3   The Generations of Modelling -- 2.3.1   First- and second-generation modelling -- 2.3.2   Third-generation modelling -- 2.3.2.1   Establishment of the computational hydraulics centre -- 2.3.2.2   Challenges of the development -- 2.3.2.3   Stratified flow modelling -- 2.3.2.4   Wave modelling -- 2.3.2.5   Applications and commercialization of the third-generation models -- 2.3.3   Fourth-generation modelling -- 2.3.3.1   Driving forces for the development -- 2.3.3.2   Scope of the development -- 2.3.4   New developments in numerical methods -- 2.3.4.1   Finite difference methods -- 2.3.4.2   Unstructured grids -- 2.3.4.3   Particle tracking methods -- 2.4   Other Mike Abbott-Related Developments in Numerical Modelling -- 2.4.1   A dynamic population model -- 2.4.2   European Hydrologic System: Système Hydrologique Européen (SHE) -- 2.4.3   Laying of marine pipelines -- 2.5   From Computational Hydraulics to Hydroinformatics -- 2.5.1   The changing nature of modelling systems.2.5.2   Challenges to model users -- 2.5.3   The way ahead -- References -- Chapter 3 : Hydroinformatics opening new horizons: union of computational hydraulics and artificial intelligence -- 3.1   Introduction -- 3.2   Earliest AI Efforts in Hydraulics, Hydrology and Hydroinformatics -- 3.3   Picking-Up Momentum -- 3.4   The Formative Years -- 3.5   Opening the Black Box -- 3.6   Growing Volumes of Data and Accelerating Computing Power -- 3.7   Recent Examples of AI-Enabled Systems -- 3.7.1   Planetary-scale surface water detection from space -- 3.7.2   Water quality sensing -- 3.7.3   Computer vision for opportunistic rainfall monitoring -- 3.7.4   Hydrologically informed machine learning for rainfall-runoff modelling -- 3.8   Opportunities for Future Developments -- 3.8.1   Machine learning -- 3.8.2   Enabling technologies -- 3.8.3   Freedom to the data! -- 3.8.4   Deep learning -- 3.8.5   Hydroinformatics-informed machine learning? -- 3.9   The Way Forward -- References -- Chapter 4 : Hydroinformatics impact on hydrological modelling -- 4.1   Introduction -- 4.2   Terminology and Model Classifications -- 4.2.1   Classification according to hydrological process description -- 4.2.2   Classification according to technological level -- 4.3   The SHE Venture -- 4.3.1   State of the art in hydrological modelling in the early 1970s -- 4.3.2   Motivation of the SHE development and creation of the SHE partnership -- 4.3.3   The initial SHE development (1976-1986) -- 4.3.4   From research code to practical applications (1986-1990s) -- 4.4   Evaluation Of the SHE Achievements -- 4.4.1   SHE: a contentious quantum leap -- 4.4.2   Evaluation of the impact of SHE on hydrological modelling today -- 4.5   Other Hydroinformatics Contributions.4.5.1   Encapsulation of knowledge in digital modelling systems -- 4.5.2   Intelligent software systems to support stakeholders in water management -- 4.6   Conclusions -- Acknowledgements -- References -- Chapter 5 : Hydroinformatics as a 'game changer' in the water business -- 5.1   Introduction -- 5.2   Evolution of Hydroinformatics -- 5.2.1   Building the fundaments: 1960s and 1970s -- 5.2.2   The rise of computational modelling business: 1980s -- 5.2.3   Maturing and expanding: 1990s -- 5.2.4   Water business in the new millennium -- 5.3   Technical and Commercial Aspects of Hydroinformatics -- 5.3.1   Original view on hydroinformatics as part of the knowledge economy -- 5.3.2   State of technology -- 5.3.3   Changes in education of hydroinformatics and their reflections on business -- 5.3.4   Business transformation -- 5.3.5   Software providers and their business models -- 5.3.6   Software users and their needs -- 5.3.7   Data collection, sharing and publishing -- 5.4   Societal and Political Aspects of Hydroinformatics -- 5.4.1   Social justice and hydroinformatics -- 5.4.2   Learning by playing -- 5.4.3   Transparency of modelling and ethical aspects of presentation materials -- 5.5   Business Opportunities as Seen from 21st Century Perspectives -- 5.5.1   Water in cities market -- 5.5.2   Water resources market -- 5.5.3   Marine market -- 5.5.4   Other market segments related to water or the environment -- 5.6   Future Challenges for Hydroinformatics Business -- 5.6.1   Uncertainty and parametrisation of models -- 5.6.2   Climate change and its impacts -- 5.6.3   New business models in simulation modelling -- 5.6.4   Growth in hydroinformatics: consultancy demands -- 5.6.5   Vision for future or business -- References.Chapter 6 : Hydroinformatics in China: overall developments and showcase of accomplishments in the Changjiang River basin -- 6.1   Introduction -- 6.2   DTR Decision Support Framework -- 6.3   Data Acquisition and Management -- 6.3.1   Types of data -- 6.3.2   Data acquisition -- 6.3.3   Data monitoring technologies -- 6.4   Models and Their Roles in DSS -- 6.4.1   Physically based water-related models -- 6.4.1.1   Meteorological modelling -- 6.4.1.2   Hydrological modelling and stochastic modelling -- 6.4.2   Regulation models -- 6.4.2.1   Regulation model for flood management in a river basin -- 6.4.2.2   Water resources regulation model -- 6.4.2.3   Ecological regulation model -- 6.4.2.4   Regulation model for power generation of group of reservoirs -- 6.4.2.5   Multi-objective regulation model -- 6.4.3   Risk assessment models -- 6.4.4   Data-driven approaches: artificial intelligence models -- 6.4.4.1   ML and AI models used for hydrological forecasting -- 6.4.4.2   Intelligent regulation technology based on a knowledge graph -- 6.4.4.3   ML and AI models for other water management tasks -- 6.5   Improved Governance and Public Involvement: The River/Lake Chief System -- 6.6   Applications in The Changjiang River Basin -- 6.6.1   Flood management -- 6.6.1.1   Data acquisition in the Changjiang River basin -- 6.6.1.2   Models and DSSs for the Changjiang River basin -- 6.6.1.3   Joint regulation of water projects for flood management -- 6.6.1.4   Application examples -- 6.6.2   River/Lake chief system and public participation -- 6.6.2.1   Functionalities of the RCS -- 6.6.2.2   Public participation -- 6.6.2.3   Performance of Chongqing RCS -- 6.7   Summary -- References -- Chapter 7 : Hydroinformatics education at IHE Delft: past and future -- 7.1   Introduction.7.2   Motivation and Origins -- 7.3   Developments of IHE ' s Hydroinformatics Education Over Last 30 Years -- 7.4   Current Status and The Course Content of the Hydroinformatics MSc Specialization -- 7.5   Associated MSc Programmes -- 7.5.1   Erasmus + Flood Risk Management Master ' s programme -- 7.5.2   International Master ' s in Hydroinformatics -- 7.6   Hydroinformatics Education Worldwide -- 7.7   Outlook -- References -- 1. On the numerical computation of nearly-horizontal flows -- 2. On the Numerical modelling of short waves in shallow water -- 3. The fourth generation of numerical modelling in hydraulics -- 4. Introducing hydroinformatics -- 5. Forchheimer and Schoklitsch: a postmodern retrospection -- 6. Towards the hydraulics of the hydroinformatics era -- 7. Towards a hydroinformatics praxis in the service of social justice.HydrologyData processingHydrologyData processing.551.480285Jonoski AndrejaMiAaPQMiAaPQMiAaPQBOOK9910788391603321Michael Abbott's Hydroinformatics3722366UNINA04342nam 22004935 450 991101864650332120250724130242.03-031-87057-310.1007/978-3-031-87057-6(MiAaPQ)EBC32234549(Au-PeEL)EBL32234549(CKB)39710502200041(DE-He213)978-3-031-87057-6(OCoLC)1530382428(EXLCZ)993971050220004120250724d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierGeometry and Non-Convex Optimization /edited by Panos M. Pardalos, Themistocles M. Rassias1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (1280 pages)Springer Optimization and Its Applications,1931-6836 ;2233-031-87056-5 Preface -- Chapter 1 Hermite-Hadamard Like Inequalities Involving Generalized Bi-Convex Functions -- Chapter 2 Some properties of Barrelled and of Bornological locally convex spaces over an arbitrary complete valued field -- Chapter 3 Bounds for the Unweighted Jensen's Gap of Absolutely Continuous Functions -- Chapter 4 Test Instances for Multiobjective Mixed-Integer Nonlinear Optimization -- Chapter 5 A trace operator for weighted Sobolev spaces -- Chapter 6 Common fixed point results for Meir-Keeler type contraction mappings -- Chapter 7 Optimum Statistical Analysis on Sphere Surface -- Chapter 8 New Generalized Ostrowski Type Fractional Integral Inequalities -- Chapter 9 Genaralized Fractional Hilbert Type Integral Inequalities in Banach Spaces -- Chapter 10 Ternary derivation-homomorphism functional inequalities -- Chapter 11 C*-ternary biderivations and C*-ternary bihomomorphisms -- Chapter 12 A Survey of Erdős-Szekeres Products -- Chapter 13 Recent developments in general quasi variational inequality -- Chapter 14 General Variational Inequalities and Optimization -- Chapter 15 Characterizations and Set Theoretic Properties of Some Generalized Open and Fat Sets in Relator Spaces -- Chapter 16 Direct Continuity Properties of Relations in Relator Spaces -- Chapter 17 Variational Principles and Fixed Points in Symmetric Structures -- Chapter 18 Sequential Coercivity over Q-Ordered Q-Metric Spaces -- Chapter 19 A Hardy-Hilbert’s Integral Inequality with the Internal Variables Involving Two Derivative Functions.This book offers a comprehensive exploration of the dynamic intersection between geometry and optimization. It delves into the intricate study of Hermite-Hadamard inequalities, Hilbert type integral inequalities, and variational inequalities, providing a rich tapestry of theoretical insights and practical applications. Readers will encounter a diverse array of topics, including the bounds for the unweighted Jensen's gap of absolutely continuous functions and the properties of Barrelled and Bornological locally convex spaces. The volume also covers advanced subjects such as multiobjective mixed-integer nonlinear optimization and optimum statistical analysis on sphere surfaces. Contributions from eminent scholars provide a deep dive into C*-ternary biderivations, Erdős-Szekeres products, and variational principles, making this book a must-read for those seeking to expand their understanding of these complex fields. Ideal for researchers and scholars in mathematics and optimization, this volume is an invaluable resource for anyone interested in the latest developments in geometry and nonconvex optimization. Whether you are a seasoned academic or a graduate student, this book will enhance your knowledge and inspire further research in these fascinating domains.Springer Optimization and Its Applications,1931-6836 ;223Mathematical optimizationOptimizationMathematical optimization.Optimization.519.6Pardalos Panos M318341Rassias Themistocles M40345MiAaPQMiAaPQMiAaPQBOOK9911018646503321Geometry and Non-Convex Optimization4414601UNINA