Designing with computational intelligence
This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also...
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| Other Authors | , , |
|---|---|
| Format | Electronic eBook |
| Language | English |
| Published |
Switzerland :
Springer,
[2016]
|
| Series | Studies in computational intelligence ;
v. 664. |
| Subjects | |
| Online Access | Full text |
| ISBN | 9783319447353 9783319447346 |
| ISSN | 1860-949X ; |
| Physical Description | 1 online resource (xviii, 238 pages) : illustrations (some color) |
Cover
Table of Contents:
- Intro; Preface; Contents; List of Figures; List of Tables; 1 On Using Fuzzy Logic to Control a Simulated Hexacopter Carrying an Attached Pendulum; 1.1 Introduction; 1.2 Description of the Controlled Plant: The Hexacopter; 1.3 Proposed Multi-layer Controller; 1.3.1 Pre-processing Phase; 1.3.2 Post-processing Phase; 1.4 The Fuzzy Controllers; 1.4.1 The Fuzzy Method; 1.4.2 Roll Stabilization; 1.4.3 Pitch Stabilization; 1.4.4 Heading to Goal (Yaw Controller); 1.4.5 The Horizontal Navigation; 1.4.6 The Vertical Navigation; 1.5 Experiment and Results; 1.5.1 Overview of the Experiment; 1.5.2 Results
- 1.5.3 Discussion1.6 Conclusions and Future Work; References; 2 Monocular Pose Estimation for an Unmanned Aerial Vehicle Using Spectral Features; 2.1 Introduction; 2.2 Homography-Based Pose Estimation; 2.2.1 Review of Plane-Induced Homography; 2.2.2 Homography Decomposition; 2.3 Spectral Features Correspondence; 2.3.1 Corresponding Points; 2.4 Implementation and Results; 2.4.1 Spectral Features Evaluation; 2.4.2 Pose Estimation in Simulated Quadcopter; 2.5 Conclusions; References; 3 Simultaneous Navigation and Mapping in an Autonomous Vehicle Based on Fuzzy Logic; 3.1 Introduction
- 3.2 Virtual Robot Experimentation Platform3.3 Autonomous Vehicle; 3.4 Navigation and Mapping; 3.4.1 Trajectory Planning; 3.4.2 Navigation; 3.4.3 Decision Tree; 3.5 Simulation; 3.6 Case Study; 3.7 Conclusions; References; 4 Fully Scalable Parallel Hardware for Wheeled Robot Navigation Using Fuzzy Control; 4.1 Introduction; 4.2 Fuzzy Controlllers; 4.3 Fuzzy Models for Wheeled Robot Navigation; 4.4 The Proposed Macro-architecture; 4.5 Micro-architecture of the Functional Units; 4.5.1 Membership Function Unit; 4.5.2 Membership Function Memory; 4.5.3 Fuzzification Unit; 4.5.4 Inference Unit
- 4.5.5 Defuzzification Unit4.6 Performance Results; 4.7 Conclusion; References; 5 Nonlinear Correction for an Energy Estimator Operating at Severe Pile-Up Conditions; 5.1 Introduction; 5.2 High-Energy Signal Pile-Up; 5.3 Online Linear Estimation; 5.3.1 Minimum Variance Linear Unbiased Estimator; 5.3.2 Maximum Likelihood Estimation; 5.4 Nonlinear Correction; 5.5 Performance Comparisons; 5.5.1 Data Set; 5.5.2 Nonlinear Corrector Design; 5.5.3 Efficiency Tests; 5.5.4 Bias and Linearity; 5.5.5 Performance at Different Occupancy Levels; 5.5.6 Exploring the ANN Generalization; 5.6 Conclusions
- 8 Human
- Machine Musical Composition in Real-Time Based on Emotions Through a Fuzzy Logic Approach