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Simulation and Analysis of Mathematical Methods in Real-Time Engineering Applications
Читать книгу Simulation and Analysis of Mathematical Methods in Real-Time Engineering Applications - Группа авторов - Страница 1
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Страница 1
Table of Contents
Guide
List of Illustrations
List of Tables
Pages
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1
Certain Investigations on Different Mathematical Models in Machine Learning and Artificial Intelligence
1.1 Introduction
1.1.1 Knowledge-Based Expert Systems
1.1.2 Problem-Solving Techniques
1.2 Mathematical Models of Classification Algorithm of Machine Learning
1.2.1 Tried and True Tools
1.2.2 Joining Together Old and New
1.2.3 Markov Chain Model
1.2.4 Method for Automated Simulation of Dynamical Systems
1.2.5 kNN is a Case-Based Learning Method
1.2.6 Comparison for KNN and SVM
1.3 Mathematical Models and Covid-19
1.3.1 SEIR Model (Susceptible-Exposed-Infectious-Removed)
1.3.2 SIR Model (Susceptible-Infected-Recovered)
1.4 Conclusion
References
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Edge Computing Optimization Using Mathematical Modeling, Deep Learning Models, and Evolutionary Algorithms
2.1 Introduction to Edge Computing and Research Challenges
2.1.1 Cloud-Based IoT and Need of Edge Computing
2.1.2 Edge Architecture
2.1.3 Edge Computing Motivation, Challenges and Opportunities
2.2 Introduction for Computational Offloading in Edge Computing
2.2.1 Need of Computational Offloading and Its Benefit
2.2.2 Computation Offloading Mechanisms
2.2.2.1 Offloading Techniques
2.3 Mathematical Model for Offloading
2.3.1 Introduction to Markov Chain Process and Offloading
2.3.1.1 Markov Chain Based Schemes
2.3.1.2 Schemes Based on Semi-Markov Chain
2.3.1.3 Schemes Based on the Markov Decision Process
2.3.1.4 Schemes Based on Hidden Markov Model
2.3.2 Computation Offloading Schemes Based on Game Theory
2.4 QoS and Optimization in Edge Computing
2.4.1 Statistical Delay Bounded QoS
2.4.2 Holistic Task Offloading Algorithm Considerations
2.5 Deep Learning Mathematical Models for Edge Computing
2.5.1 Applications of Deep Learning at the Edge
2.5.2 Resource Allocation Using Deep Learning
2.5.3 Computation Offloading Using Deep Learning
2.6 Evolutionary Algorithm and Edge Computing
2.7 Conclusion
References
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