Intelligent Systems Modeling and Simulation II. Machine Learning, Neural Networks, Efficient Numerical Algorithm and Statistical Methods

✍ Scribed by Samsul Ariffin Abdul Karim

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 688
• Series: Studies in Systems, Decision and Control, Volume 444
• Category: Library

✦ Table of Contents

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
2.2 Forecasting
2.3 Determination of Significant Relationship Between the Number of Dengue Cases and Both Rainfall and Average Temperature Using Multiple Regression
3 Results and Discussion
4 Summary
References
Interacting Wave Phenomena Described by Coupled Beta Time Fractional mKdV Equation in Fluid-Filled Elastic Tube
1 Introduction
2 Mathematical Model Equations and Limitations
3 Formation of Coupled mKdVEs
4 Formation of Coupled Beta-Time Fractional mKdVEs
5 Solution of Coupled BTF-MKdVEs
6 Phase Shifts
7 Result and Discussion
8 Summary
References
Influence of Induced Magnetic Over Stagnation Point Ag-MgO/H2O Hybrid Nanofluid Flow and Heat Transfer Towards Moving Surface
1 Introduction
2 Formulation Problem
3 Temporal Stability Analysis
4 Results and Discussion
5 Conclusion
References
The Performance of Logistic Regression and Discriminant Analysis in Spam E-mail Classification
1 Introduction
2 Methodology
2.1 Logistic Regression
2.2 Discriminant Analysis
3 Data Collection and Pre-Processing
4 Results and Discussion
5 Summary
References
Performance of Several Statistical Methods in Forecasting Particulate Matter Concentrations in Pasir Gudang, Johor
1 Introduction
2 Methodology
2.1 Multiple Linear Regression (MLR)
2.2 Principal Component Regression (PCR)
2.3 Time Series Analysis (TSA)
2.4 Evaluation Indices
3 Data Collection
4 Results and Discussion
4.1 Results of Multiple Linear Regression
4.2 Results of Principal Component Regression (PCR)
4.3 Results of Time Series Analysis (TSA)
4.4 Evaluation of Performance
5 Summary
References
Re-examining the Feldstein-Horioka Puzzle in Few Asian Countries: A Nonlinear ARDL Approach
1 Introduction
2 Literature Reviews
2.1 Concept and Theoretical Framework
2.2 Empirical Reviews
3 Data
4 Methodology
5 Results
6 Conclusion
References
Commodity Price Persistency and Dynamics: A Smooth Transition Regression Approach
1 Introduction
2 Literature Reviews
2.1 Concept and Theoretical Framework
2.2 Empirical Reviews
3 Data
4 Methodology
4.1 The Smooth Transition Regression (STR) Model
5 Results and Discussions
6 Conclusion
References
Time Series and Statistical Analyses on REIT Stock Prices for Forecasting and Assessing the Impact of COVID-19
1 Introduction
2 Time Series Analysis and Statistical Analysis
3 Data Description and Resources
4 Results and Discussion on the Time Series Analysis
4.1 Model Identification
4.2 Parameter Estimation
4.3 Model Diagnostic Checking
4.4 Testing the ARCH Effect and Fitting the GARCH Model
5 Forecasting
6 Evaluate the Impact of COVID-19 to the REITs’ Prices
7 Summary
References
A New 7-Point Quaternary Approximating Subdivision Scheme
1 Introduction
2 Preliminaries
3 A 7-Point Quaternary Approximating SS
3.1 Continuity
3.2 Holder Regularity
3.3 Limit Stencil
3.4 Approximating Order
3.5 Support of Basic Limit Function
4 Results and Discussions
4.1 Error Bound
4.2 Continuity
4.3 Shapes of Limit Curves
5 Conclusion
References
Assessment of Groundwater Quality Using Multivariate Statistical Techniques
1 Introduction
2 Materials
2.1 Study Area
2.2 Data Collection and Analysis
3 Methods
3.1 Multivariate Statistical Approaches
3.2 Principal Components Analysis (PCA)
3.3 Factor Analysis
3.4 Cluster Analysis
4 Results and Discussion
5 Conclusion
References
A Novel Three Term Conjugate Gradient Method for Unconstrained Optimization via Shifted Variable Metric Approach with Application
1 Introduction
2 Derivation of the New Method
2.1 Algorithms of
3 Convergence Analysis
4 Numerical Results
5 Applications of RB Method in Inflation Rate
6 Conclusion
References
The Full Process in Modeling and Quantitative Methods by Using SPSS
1 Stage One: Getting Started
1.1 Getting to Know SPSS
1.2 Types of Data Measurement Scales in SPSS
1.3 Creating Variable and Input
1.4 Input Data from Excel
2 Stage Two: Refining Model
2.1 Exploring Factor Analysis of Independent Variables and Dependent Variables
3 Stage Three: Credibility by Cronbach’s α Testing
4 Stage Four: Descriptive Statistics
5 Stage Five: Analysis of Correlation by Pearson
6 Stage Six: Linear Regression Analysis
7 Stage Seven: Test the Relationship Between Two Qualitative Variables with Chi-Square
7.1 Chi-Square Test for Nominal Versus Nominal or Nominal Versus Ordinal Measures
7.2 Chi-Square Test for Ordinal Versus Ordinal
8 Stage Eight: Sample T Tests
8.1 One-Sample T Test
8.2 Paired-Sample T-Test in SPSS
9 Stage Nine: Independent Sample T-Test
10 Summary
References
The Evaluation of Marketers on Digital Platforms for Organizations (The Full Steps of Measurement and Each Element’s Function)
1 Introduction of Digital Platforms
2 Categories of E-Commerce
3 Catching Up with Digital Platforms Fast-Paced Development
4 Measurement and Evaluation of Elements
4.1 Overview
4.2 Traffic and Engagement
4.3 Geography and Country Targeting
4.4 Audience Interests
4.5 Competitors and Similar Sites
4.6 Social Media Traffic
4.7 Keywords
5 Summary
References
Quantitative Methodology: Applied Modeling by Using AMOS (Step-By-Step)
1 Getting Started with AMOS
2 CFA—Confirmatory Factor Analysis
2.1 Direction of Using CFA
2.2 The Measure of Model Fit in CFA
2.3 The Measure of Scalars in CFA Method
3 SEM—Structural Equation Modeling
4 Bootstrap Testing
5 Summary
References
Understanding and Applying STATA in Quantitative Research and in Forecast Trend
1 Dataset in Stata
2 Getting Started with Stata
2.1 Open, and Exit
2.2 Interface
2.3 Input
3 Command Syntax of Stata
4 Operators and Functions
5 Statistics in Stata
5.1 Using Statistics with Types of Measurement Scales in Stata
5.2 Describe Data
5.3 Display Values of Variables
5.4 Counting the Observations
5.5 Basic Statistics
6 Linear Regression—OLS Method
6.1 Estimating Linear Regression Model by OLS Method
6.2 Coefficient of Determination and Test of Coefficient of Determination
6.3 Confidence Interval of the Coefficient of Regression
7 Hypothesis Testing of Regression Coefficients
7.1 Two-way Hypothesis Testing
7.2 Testing the Right Hypothesis
7.3 Testing the Left Hypothesis
7.4 Simultaneous Hypothesis Testing Involves a Linear Combination of Regression Coefficients
8 Summary
References
Detecting Structural Breaks and Outliers for Volatility Data via Impulse Indicator Saturation
1 Introduction
2 Methodology
3 Simulation Procedure
4 Result and Discussion
5 Conclusion
References
Index