Kooperativer Bibliotheksverbund

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Format: 1 online resource (687 pages)

ISBN: 9783031040283

Series Statement: Studies in Systems, Decision and Control ; v.444

Note: Intro -- Preface -- Contents -- Editor and Contributors -- Introduction -- 1 Introduction -- 2 Executive Summary -- 3 Conclusion -- References -- Physics-Constrained Deep Learning for Isothermal CSTR -- 1 Introduction -- 2 Physics-Constrained Deep Learning -- 3 Research Methodology -- 3.1 Data Preparation -- 3.2 Network Architecture Design -- 3.3 Model Training -- 3.4 Model Validation -- 4 Result and Discussion -- 5 Summary -- References -- Heat Transfer Modelling with Physics-Informed Neural Network (PINN) -- 1 Introduction -- 2 Literature Review -- 2.1 Physics-Informed Neural Network -- 2.2 Heat Equation -- 3 Methodology -- 4 Benefits and Economical Consideration -- 5 Data Collection and Analysis -- 6 Results and Discussion -- 7 Summary -- References -- An Overview on Deep Learning Techniques in Solving Partial Differential Equations -- 1 Introduction -- 2 Deep Neural Networks (DNNs) -- 3 Some Deep Learning Techniques for Solving PDEs -- 3.1 Physics-Informed Neural Networks -- 3.2 Blended Inverse-PDE Network (BiPDE-Net) -- 3.3 Int-Deep -- 4 Optimization Methods -- 4.1 ADAM Method -- 4.2 Adagrad -- 4.3 L-BFGS -- 5 Conclusion -- References -- Solving HornSAT Fuzzy Logic Neuro-symbolic Integration -- 1 Introduction -- 2 Neuro-logic in Hopfield Neural Network -- 2.1 Hopfield Neural Network -- 2.2 Logic Programming in Hopfield Neural Network -- 3 Satisfiability Problem -- 3.1 HornSAT Problem -- 4 Fuzzy Logic Technique -- 5 Methodology -- 6 Results and Discussion -- 7 Conclusion -- References -- 3SAT and Fuzzy-HornSAT in Hopfield Neural Network -- 1 Introduction -- 2 Hopfield Neural Network in Logic Programming -- 3 Satisfiability Problem -- 4 Implementation of Fuzzy Logic in Hopfield Neural Network -- 4.1 The Algorithms -- 5 Performance Evaluation Metrics -- 5.1 Performance Evaluation Metric for the Learning Phase. , 5.2 Performance Evaluation Metric for the Retrieval Phase -- 6 Result and Discussion -- 7 Conclusion -- References -- Data-Driven Model with Spatio-Temporal RBFNN: Application to Photovoltaic Module Simulation -- 1 Introduction -- 2 Spatio-Temporal RBF Neural Network -- 2.1 Spatio-temporal RBFNN Training -- 3 PV Model -- 3.1 Newton-Raphson Method -- 3.2 The Solarex MSX60 PV Module -- 4 Experiments Results -- 4.1 SIMULINK PV Model Results -- 5 Conclusions -- References -- Machine Learning Optimization in Computational Advertising-A Systematic Literature Review -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 4 Results and Findings -- 5 Discussion -- 6 Summary -- References -- Data-Driven Macro-economic Model Analysis Using Non-standard Trimean Algorithm -- 1 Introduction -- 2 The Dynamic Interaction Model -- 3 Fitting Observed Data to the Dynamic Model -- 4 Non-standard Trimean Numerical Method -- 5 Experiment -- 6 Result and Discussion -- 7 Summary -- References -- Data-Driven Ordinary Differential Equations Model for Predicting Missing Data and Forecasting Crude Oil Prices -- 1 Introduction -- 2 Prediction Models Imputation -- 2.1 Least-Square Fitted Polynomial Model -- 2.2 Data-Driven Ordinary Differential Equation -- 2.3 Runge-Kutta-Fehlberg -- 3 Experiments -- 4 Results and Discussion -- 5 Summary -- References -- Data Interpolation Using Rational Cubic Ball with Three Parameters -- 1 Introduction -- 2 Methodology -- 2.1 Derivative Estimation -- 2.2 Local Shape Control Analysis -- 3 Curve Interpolation Using Rational Cubic Ball Interpolant -- 3.1 Absolute Error Analysis -- 3.2 Absolute Error Analysis -- 4 Discussion -- 5 Conclusion -- References -- Alpha-Rooting Color Image Enhancement Method for Discrete Fourier Transform and Discrete Quaternion Fourier Transform -- 1 Introduction -- 2 Basics Properties of Quaternion. , 3 Two-Dimensional Discrete Quaternion Fourier Transform -- 4 Numerical Experiments -- 5 Conclusion -- Appendix -- References -- New Norm Disease Resilient Air-Conditioning Control Module -- 1 Introduction -- 1.1 Health Hazards -- 1.2 System Hazards -- 1.3 Key Opportunities -- 2 Methodology -- 2.1 Parametric Identification and Limiters -- 2.2 Components of the Integrated Systems -- 3 Testing Resilience of the Systems -- 4 Summary -- References -- Thermal Analysis of VLSI System using Successive Over Relaxation (SOR) Method -- 1 Introduction -- 2 Crank-Nicolson Method -- 3 Numerical Crank-Nicolson Method -- 4 Gauss-Seidel Method -- 5 Successive Over Relaxation Method -- 6 Numerical Approach -- 6.1 Formula of Approximation -- 6.2 Formulation and Implementation of Gauss-Seidel Method -- 6.3 Formula and Implementation of Successive Over Relaxation Method -- 7 Numerical Experiments -- 8 Percentage Reduction Calculation -- 9 Conclusion -- Appendixes -- References -- Solution of Peak Junction Temperature with Crank-Nicolson and SOR Approach -- 1 Introduction -- 2 Model of Heat Equation -- 3 Discretization of Crank-Nicolson Method -- 4 Formulation Gauss-Seidel (GS) Method -- 5 Formulation of Successive Over Relaxation (SOR) Method -- 6 Numerical Treatments -- 7 Percentage Reduction Analysis -- 8 Summary -- References -- Using Intelligent Systems in Enterprises and Organizations in Russian Regions -- 1 Introduction -- 2 Theoretical and Conceptual Background -- 3 Methodology and Design -- 4 Results of Empirical Data Modeling -- 5 Discussion of Simulation Results -- 6 Summary -- References -- HornSAT Solver Using Agent-Based Modelling in Hopfield Network -- 1 Introduction -- 2 Hopfield Neural Network (HNN) -- 3 Satisfiability -- 4 An Instance of Horn Satisfiability -- 5 Procedures for Development of Our Agent-Based Model HornSAT Solver. , 6 Experimental Build-Up of Our Model -- 7 Results and Discussion -- 8 Summary -- References -- New Operational Matrices of Dejdumrong Polynomials to Solve Linear Fredholm-Volterra-Type Functional Integral Equations -- 1 Introduction -- 2 Dejdumrong Polynomial Representation -- 3 Fundamental Matrix Relations -- 3.1 The Representation of Differential Part in Matrix Form -- 3.2 The Representation of Integral Part mathcalV(t) in Matrix Form -- 3.3 The Representation of the Initial Conditions in Matrix Form -- 4 Method of Solution -- 5 Error Estimation -- 6 Numerical Examples -- 7 Conclusion -- References -- Modelling the Covid-19 Pandemic for a Small Population Size -- 1 Introduction -- 2 Prediction of Disease Spread Using Kermack/McKendrick (KM) SIR Epidemic Model -- 2.1 Terminology -- 2.2 Assumptions -- 2.3 Deterministic Solution -- 3 Results and Discussion -- 3.1 SIR Model for Full Population of Brunei Darussalam -- 3.2 SIR Model for Washing Hands and Wearing Masks -- 3.3 SIR Model for Social Distancing -- 3.4 Comparing SIR Model for Social Distancing with Brunei Situation -- 4 Conclusion -- References -- Efficient Iterative Approximation for Nonlinear Porous Medium Equation with Drainage Model -- 1 Introduction -- 2 Construction of a Quarter-Sweep Approximation -- 3 Stability Analysis -- 4 Derivation of a Quarter-Sweep Modified Successive Over-Relaxation -- 5 Numerical Experiment -- 6 Conclusion -- References -- A Bi-variate Relaxed Four-Point Approximating Subdivision Scheme -- 1 Introduction -- 2 Relaxed Four-Point -- 2.1 Necessary Condition for Convergence of the Scheme -- 3 Continuity of the Scheme -- 3.1 Polynomial Generation -- 3.2 Holder Regularity -- 3.3 Joint Spectral Radius -- 3.4 Local Analysis with Invariant Neighborhood -- 4 Construction and Analysis of Relaxed Four-Point Tensor Product Scheme. , 4.1 Analysis of Relaxed Four-Point Tensor Product Scheme -- 5 Numerical Examples -- 6 Conclusion and Future Work -- References -- Application of Bernstein Collocation Solutions for Solving Second Kind Volterra-Fredholm Integral Equations -- 1 Introduction -- 2 Volterra-Fredholm Integral Equations and Recent Methods -- 3 Derivation of Bernstein Collocation Approximation Equation -- 4 Performance Analysis of Numerical Experiments -- 5 Summary -- References -- Mathematical Modelling for COVID-19 Dynamics with Vaccination Class -- 1 Introduction -- 2 Model Formulation -- 3 Basic Properties of the Model -- 4 Equilibrium Solutions and the Basic Reproduction Number -- 5 Stability Analysis of the Equilibrium Solutions -- 5.1 Local Stability and Instability of the DFE -- 5.2 Global Stability of the Equilibrium Points -- 6 Numerical Simulations of the Model -- 7 Summary and Conclusion -- References -- Numerical Method for the System of Volterra-Fredholm Integral Equations and Its Convergence Analysis -- 1 Introduction -- 2 Description of the Proposed Technique -- 3 Stability and Convergence Analysis -- 4 Numerical Examples -- 5 Conclusion and Further Work -- References -- Continuity of Solution Mappings for Parametric Quasi-equilibria -- 1 Introduction -- 2 Preliminaries -- 3 Continuity of Solution Mappings -- 4 Application to Parametric Social Nash Equilibria -- References -- Pitt's Inequality for Offset Quaternion Linear Canonical Transform -- 1 Introduction -- 2 Quaternion Algebra and Basic Properties -- 3 Two-Sided Quaternion Fourier Transform -- 4 Quaternion Linear Canonical Transform (QLCT) -- 5 Offset Quaternion Linear Canonical Transform (OQLCT) -- 6 Pitt's Inequality for OQLCT -- 7 Conclusion -- References -- The Study of the Trend of Dengue Cases in Brunei Darussalam -- 1 Introduction -- 2 Data Collection and Forecasting Using Time Series. , 2.1 Deseasonalised Data.

Additional Edition: Print version: Abdul Karim, Samsul Ariffin Intelligent Systems Modeling and Simulation II Cham : Springer International Publishing AG,c2022 ISBN 9783031040276

Language: English

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: XIX, 695 p. 260 illus., 234 illus. in color. , online resource.

Edition: 1st ed. 2022.

ISBN: 9783031040283

Series Statement: Studies in Systems, Decision and Control, 444

Content: This book develops a new system of modeling and simulations based on intelligence system. As we are directly moving from Third Industrial Revolution (IR3.0) to Fourth Industrial Revolution (IR4.0), there are many emergence techniques and algorithm that appear in many sciences and engineering branches. Nowadays, most industries are using IR4.0 in their product development as well as to refine their products. These include simulation on oil rig drilling, big data analytics on consumer analytics, fastest algorithm for large-scale numerical simulations and many more. These will save millions of dollar in the operating costs. Without any doubt, mathematics, statistics and computing are well blended to form an intelligent system for simulation and modeling. Motivated by this rapid development, in this book, a total of 41 chapters are contributed by the respective experts. The main scope of the book is to develop a new system of modeling and simulations based on machine learning, neural networks, efficient numerical algorithm and statistical methods. This book is highly suitable for postgraduate students, researchers as well as scientists that have interest in intelligent numerical modeling and simulations.

Note: Introduction -- Data-driven Ordinary Differential Equations Model for predicting missing data and forecasting Crude Oil Prices -- Efficient iterative approximation for nonlinear porous medium equation with drainage model -- The Performance of Logistic Regression and Discriminant Analysis in Spam E-mail Classification -- Detecting Structural Breaks and Outliers for Volatility Data via Impulse Indicator Saturation -- Index.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031040276

Additional Edition: Printed edition: ISBN 9783031040290

Additional Edition: Printed edition: ISBN 9783031040306

Language: English

DOI: 10.1007/978-3-031-04028-3

URL: https://doi.org/10.1007/978-3-031-04028-3