Advances in mathematical methods and high performance computing. (2019)

• Record Type: Book
• Further Information: Note: Vinai K. Singh, David Gao, Andreas Fischer, editors.
• Editors: Singh, Vinai K; Gao, David; Fischer, Andreas
• Contents: Intro; Preface; Contents; Part I Mathematical Modeling, Applications, and Theoretical Foundations; Canonical Duality-Triality Theory: Unified Understanding for Modeling, Problems, and NP-Hardness in Global Optimizationof Multi-Scale Systems; 1 Introduction and Motivation; 2 Multi-Scale Modeling and Properly Posed Problems; 2.1 Objectivity, Isotropy, and Symmetry in Modeling; 2.2 Subjectivity, Symmetry Breaking, and Well-Posed Problem; 2.3 Management Optimization; 2.4 Nonconvex Analysis and Boundary-Value Problems; 2.5 Lagrangian Mechanics and Initial-Value Problems 2.6 Mono-Duality and Duality Gap2.7 Bi-Duality and Conceptual Mistakes; 3 Unified Problem and Canonical Duality-Triality Theory; 3.1 Canonical Transformation and Gap Function; 3.2 Complementary-Dual Principle and Analytical Solution; 3.3 Triality Theory and NP-Hard Criterion; 4 Applications in Complex Systems; 4.1 Unconstrained Nonconvex Optimization Problem; 4.2 D.C. Programming; 4.3 Fixed Point Problems; 4.4 Mixed Integer Nonlinear Programming (MINLP); 4.5 General Knapsack Problem and Analytical Solution; 4.6 Bilevel Optimization and Optimal Control 4.7 Multi-Level Multi-Targets MINLP and Topology Optimization5 Symmetry, NP-Hardness, and Perturbation Methods; 6 Connections with Popular Methods and Techniques; 6.1 Relation with SDP Programming; 6.2 Relation to Reformulation-Linearization/Convexification Technique; 6.3 Relation to Composite Minimization; 7 Conclusions; References; Numerical Investigation of Stochastic Neural Field Equations; 1 Introduction; 2 Numerical Approximation; 3 Numerical Examples; 4 Conclusions; References; Nonstationary Signal Decomposition for Dummies; 1 Introduction 2 The Ensemble Empirical Mode Decomposition Algorithm2.1 Numerical Examples; 3 The Iterative Filtering Method; 3.1 Numerical Examples; 4 Conclusions and Outlook; References; Modeling the Socio-Economic Waste Generation Factors Using Artificial Neural Network: A Case Study of Gurugram (Haryana State, India); 1 Introduction; 2 Materials and Methods; 2.1 Case Study Area; 2.2 Material and Methods; 2.2.1 Population (POP); 2.2.2 Urban Population (URB); 2.2.3 Literate Population (LIT); 2.2.4 Per Capita Income (PCI); 2.2.5 Municipal Solid Waste (MSW) Data; 2.2.6 Statistical Analysis of Data 2.2.7 Proposed Artificial Neural Network (ANN) Model3 Results; 4 Conclusion; References; Regularization of Highly Ill-Conditioned RBF Asymmetric Collocation Systems in Fractional Models; 1 Introduction; 2 Preliminaries; 2.1 Fractional Integrals and Derivatives; 2.2 RBF Approximation; 3 Methodology; 3.1 A Fractional RBF Approximation; 3.2 Tikhonov Regularization; 3.3 Variable Shape Parameter; 4 Numerical Illustrations; 5 Conclusions; References; The Effect of Toxin and Human Impact on Marine Ecosystem; 1 Introduction; 2 The Mathematical Model 1; 3 Some Preliminary Results
• Publisher Details: Cham, Switzerland : Springer
• Publication Date: 2019
• Extent: 1 online resource (ix, 503 pages), illustrations (some color)
• Subjects: 004.1/1; High performance computing -- Mathematics; Electronic books; Electronic books
• Languages: English
• ISBNs: 9783030024871; 3030024873
• Related ISBNs: 9783030024864; 3030024865
• Notes: Note: Online resource; title from PDF title page (SpringerLink, viewed February 20, 2019).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.