Computer Science, Algorithms and Complexity
- Length: 254 pages
- Edition: 1
- Language: English
- Publisher: Arcler Press
- Publication Date: 2020-11-01
- ISBN-10: 1774077485
- ISBN-13: 9781774077481
- Sales Rank: #0 (See Top 100 Books)
The book defines complexity as a numerical function T (n)-the relationship between time and input size n, as one of the basic ideas of computer science. The computational complexity is categorized by algorithm based on its nature and function. The (computational) complexity of the algorithm is a measurement of the ratio of computational resources (time and space) consumed when a particular algorithm is running. For these issues, the book tries to locate heuristic algorithms which can almost explain the problem and operate in a reasonable timeframe. Different kinds of algorithms are described such as graph and network algorithms, algebraic algorithms, parallel algorithms and randomized algorithms.
Cover Title Page Copyright ABOUT THE AUTHOR TABLE OF CONTENTS List of Figures List of Abbreviations Preface Chapter 1 Introduction to Computational Science 1.1. Introduction 1.2. Basic Principles 1.3. Reasons To Study The Subject 1.4. Merging Insights With Statistical Tools and Computational Abilities 1.5. Significance of Computational Sciences 1.6. Computational Models 1.7. Computational Science Tools 1.8. Fields of Computational Science 1.9. Computational Methods Chapter 2 Scientific Visualization 2.1. Introduction 2.2. Scientific Computing 2.3. History of Computers 2.4. Computer Components 2.5. The History of Scientific Visualization 2.6. Visualization Methods For The Two Dimensional Representations 2.7. Applications Areas of Scientific Visualization 2.8. Software Tools Used In Scientific Visualization 2.9. Advantages of Scientific Visualization 2.10. Disadvantages of Scientific Visualization Chapter 3 Computational Chemistry 3.1. Introduction 3.2. Main Principles To Understand 3.3. Numerical Techniques Used In Computational Chemistry Chapter 4 Computational Electromagnetics 4.1. Introduction 4.2. Background 4.3. Outline Of The Methods 4.4. Corroboration 4.5. Light Scattering Codes 4.6. Computational Electromagnetic In Plasmonics 4.7. Electromagnetic Field Solvers 4.8. Shooting And Bouncing Rays Chapter 5 Computational Fluid Dynamics 5.1. Introduction 5.2. Computational Fluid Dynamics As An Interdisciplinary Topic 5.3. History of Computational Fluid Dynamics 5.4. Software Used In Computational Fluid Dynamics 5.5. Simulation 5.6. Numerical Methods Used In Computational Fluid Dynamics 5.7. Hierarchy of Equations Used In CDF 5.8. Applications of CDF 5.9. Advantages of CDF 5.10. Limitations of CDF Chapter 6 Computational Ocean Modeling 6.1. Introduction 6.2. Computational Modeling Accelerating Discovery 6.3. Examples Of Computational Ocean Modeling And Its Use In The Study Of Complex And Complicated Systems 6.4. Improving Medical Care And Biomedical Research Using Computational Ocean Modeling 6.5. Nibib-Funded Researches Developing In The Area Of Computational Modeling 6.6. Computational Modeler 6.7. How Does Computational Ocean Models Give Their Response To Hurricanes 6.8. Coastal Ocean Modeling Projects 6.9. Getting To Understand What Part Does The Physical Environment Play When It Comes To Marine Organisms In Tropical Ecosystem 6.10. Grid Ocean Modeling That Is Unstructured 6.11. Problems That Computational Ocean Modelers Face Chapter 7 Computational Structural Mechanics 7.1. Introduction 7.2. Plastic Analysis Method 7.3. Finite Element Method In Structural Mechanics 7.4. Software Used In Computational Structural Mechanics 7.5. Emerging Trends In Computational Structural Mechanics 7.6. Job Opportunities In Computational Structural Mechanics Chapter 8 Computational Biology 8.1. Introduction 8.2. The Foundation Of Computational Biology 8.3. Applications Of Computational Biology 8.4. Jobs Of A Computational Biologist Chapter 9 Computational Astrophysics 9.1. Introduction 9.2. Brief History Of Astrophysical Simulations 9.3. The Original Simulation Experiments 9.4. Incentive For A Homogeneous Application Setting 9.5. Computational Astrophysics And Programming Languages 9.6. Computational Vs. Analytic Techniques 9.7. Astrophysical Fluid Dynamics 9.8. Codes For Astrophysics Fluid Dynamics 9.9. Equations Applied In Astrophysical Modeling Chapter 10 Computational Finance 10.1. Introduction 10.2. A Brief History 10.3. Implementation Of Computational Finance In Various Dimensions 10.4. Recent Progresses 10.5. High-Occurrence Trading Bibliography Index Back Cover
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