Towards Analytical Techniques for Systems Engineering Applications (Studies in Systems, Decision and Control, 286)

✍ Scribed by Griselda Acosta, Eric Smith, Vladik Kreinovich

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 102
• Category: Library

✦ Synopsis

This book is intended for specialists in systems engineering interested in new, general techniques and for students and practitioners interested in using these techniques for solving specific practical problems. For many real-world, complex systems, it is possible to create easy-to-compute explicit analytical models instead of time-consuming computer simulations. Usually, however, analytical models are designed on a case-by-case basis, and there is a scarcity of general techniques for designing such easy-to-compute models. This book fills this gap by providing general recommendations for using analytical techniques in all stages of system design, implementation, testing, and monitoring. It also illustrates these recommendations using applications in various domains, such as more traditional engineering systems, biological systems (e.g., systems for cattle management), and medical and social-related systems (e.g., recommender systems).

✦ Table of Contents

Introduction
Contents
1 Formulation of the Problem
2 Analytical Techniques for Describing User Preferences: Justification for (and Extension Of) the Matrix Factorization Technique
2.1 Formulation of the Problem
2.2 Why Matrix Factorization: Our Explanation
References
3 Analytical Techniques for Describing User Preferences: 80/20 Rule Partially Explains 7 Plus Minus 2 Law: General System-Based Analysis
3.1 Formulation of the Problem
3.2 Our Explanation
References
4 Analytical Techniques for Analyzing Probability Distributions: How to Explain That Changes in Elderlies Depression Level Are Uniformly Distributed
4.1 Formulation of the Problem
4.2 Our Explanation
References
5 Analytical Techniques for Analyzing How Systems Change with Time: A Natural Explanation for the Minimum Entropy Production Principles
5.1 Formulation of the Problem
5.2 How Complex Problems Are Solved: Reminder and Related Analysis
5.3 How This Analysis Helps Explain the Minimum Entropy Production Principle
References
6 Analytical Techniques for Gauging Accuracy of Expert Knowledge: A Simple System-Based Explanation of the Dunning–Kruger Effect
6.1 Formulation of the Problem
6.2 Our Explanation
References
7 Analytical Techniques Help Enhance the Results of Data Mining: Case Study of Cow Insemination
7.1 Formulation of the Problem
7.2 Our Explanation
References
8 Analytical Techniques Help Enhance the Results of Data Mining: Why Pink Noise Is Best for Enhancing Sleep and Memory
8.1 Formulation of the Problem
8.2 Our Explanation
References
9 Analytical Techniques Help Enhance the Results of Data Mining: Why Filtering Out Higher Harmonics Makes It Easier to Carry a Tune
9.1 Formulation of the Problem
9.2 Our Explanation
References
10 Case When Analytical Techniques Invalidate the Conclusions of Data Mining: Reversed Flynn Effect of Decreasing IQ Test Scores
10.1 Formulation of the Problem
10.2 Systems-Based Analysis of the Problem and the Resulting Explanation...
10.3 Maybe the Same Idea Can Explain the Observed Increase...
References
11 Analytical Techniques in Hypothesis Testing: Why Area Under the Curve?
11.1 Formulation of the Problem
11.2 Our Explanation
References
12 It Is Important to Revisit the Selection of the Best Model When New Data Appear: Why Confirmation Bias is a Faulty Strategy
12.1 Formulation of the Problem
12.2 Analysis of the Problem
References
13 Need for a Careful Comparison Between Hypotheses: Case Study of Epicycles
13.1 Epicycles: Bad Science or Genius Idea
13.2 Analysis of the Problem and the Resulting Conclusions
References
14 Analytical Techniques Help in Emulating Biological Systems: An Explanation of Why High-Level Attention Constantly Oscillates
14.1 Formulation of the Problem
14.2 Analysis of the Problem
14.3 Oscillations Are Better: Proofs
References
15 Analytical Techniques for Taking into Account Several Aspects of a Designed Systems: Case Study of Computation-Communication Tradeoff
15.1 Formulation of the Problem
15.2 Description of a Model
15.3 Analysis of the Model: What Is the Optimal Tradeoff Between Computation …
References
16 Users Do Not Always Follow Expert Recommendations: Analytical Technique Explains Empirical Data
16.1 Formulation of the Problem
16.2 Our Explanation
References
17 Analytical Techniques for Making Recommendations More Acceptable to Users: Status Quo Bias Actually Helps Decision Makers to Take Nonlinearity into Account
17.1 Formulation of the Problem
17.2 Analysis of the Problem and the Resulting Explanation
References
18 Analytical Techniques for Testing: Optimal Distribution of Testing Resources Between Different System Levels
18.1 Formulation of the Problem
18.2 Analysis of the Problem
18.3 Formulation of the Problem in Precise Terms
18.4 Solving the Resulting Optimization Problem
References
Appendix Bibliography
Index