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Intelligent Automation in Renewable Energy 2019 ed. [Kõva köide]

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  • Formaat: Hardback, 285 pages, kõrgus x laius: 235x155 mm, kaal: 617 g, 101 Illustrations, color; 131 Illustrations, black and white; XII, 285 p. 232 illus., 101 illus. in color., 1 Hardback
  • Sari: Computational Intelligence Methods and Applications
  • Ilmumisaeg: 19-Feb-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030022358
  • ISBN-13: 9783030022358
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Intelligent Automation in Renewable Energy 2019 ed.Suurem pilt
  • Formaat: Hardback, 285 pages, kõrgus x laius: 235x155 mm, kaal: 617 g, 101 Illustrations, color; 131 Illustrations, black and white; XII, 285 p. 232 illus., 101 illus. in color., 1 Hardback
  • Sari: Computational Intelligence Methods and Applications
  • Ilmumisaeg: 19-Feb-2019
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030022358
  • ISBN-13: 9783030022358
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783030022358.html

After an introduction to renewable energy technologies, the authors present computational intelligence techniques for optimizing the manufacture of related technologies, including solar concentrators. In particular the authors present new applications for their neural classifiers for image and pattern recognition.

The book will be of interest to researchers in computational intelligence, in particular in the domain of neural networks, and engineers engaged with renewable energy technologies.

1 Renewable Energy: Solar, Wind, and Others
1(12)
1.1 Solar Energy
3(3)
1.2 Wind Energy
6(4)
References
10(3)
2 Solar Concentrators: State of the Art
13(10)
2.1 Trough Solar Concentrators
15(2)
2.1.1 Fresnel-Type Concentrators
16(1)
2.2 Tower Solar Concentrator Systems
17(1)
2.2.1 Heliostat Field Concentrators
17(1)
2.3 Parabolic Dish Solar Concentrators
18(3)
References
21(2)
3 Solar Concentrators with Flat Mirrors
23(22)
3.1 History of the Development of Flat Mirror Solar Concentrator
23(2)
3.2 Architecture of Solar Concentrator with Flat Mirrors
25(2)
3.3 Structure of Parabolic Dish Concentrator
27(8)
3.3.1 Components of the Support Frame of Solar Concentrators
28(1)
3.3.2 Steps of Assembly of the Support Frame
29(1)
3.3.3 First Developed Prototype of Solar Concentrator
30(4)
3.3.4 Second Developed Prototype of the Solar Concentrator
34(1)
3.4 Supporting Device Manufacture and Assembly
35(5)
3.5 Parabolic Gauge for Adjustment of Parabolic Surface of Solar Concentrator
40(1)
3.6 Prototypes of Solar Concentrators with Flat Mirrors
41(1)
References
42(3)
4 Solar Thermal Power Station for Green Building Energy Supply
45(32)
4.1 Residential Power Plant
45(8)
4.1.1 New Prototype of Flat Mirror Solar Concentrator
47(1)
4.1.2 Cost Evaluation of the New Solar Concentrator
48(3)
4.1.3 Thermal Energy Storage and Cost Evaluation
51(2)
4.1.4 Approximate Evaluation of a Residential Solar Power Plant
53(1)
4.2 Solar Air Dehumidification Systems
53(4)
4.2.1 Flat Facet Solar Concentrator for Dehumidification Systems
54(2)
4.2.2 Thermal Energy Storage for Dehumidification Systems
56(1)
4.2.3 District Dehumidification Systems
57(1)
4.3 Solar Chillers for Air Conditioning Systems
57(5)
4.3.1 Flat Facet Solar Concentrator for Air Conditioning Systems
58(3)
4.3.2 District Solar Cooling System
61(1)
4.4 Thermal Energy Storage
62(3)
4.4.1 Large-Scale Thermal Energy Storage
62(1)
4.4.2 Pyramid Thermal Energy Storage
63(1)
4.4.3 Hot Pyramid Example
63(2)
4.5 Open Pit Mining Technologies
65(2)
4.5.1 Strip Mining Using Draglines
65(1)
4.5.2 Track and Shovels-Based Technology
66(1)
4.5.3 Pit Crushing and Conveying Technology
66(1)
4.5.4 Blast-Free Mining
66(1)
4.6 Seasonal Thermal Energy Storage
67(7)
4.6.1 Hot and Cold Water STES
68(1)
4.6.2 Calculations of Hot and Cold Water STES Parameters
69(5)
References
74(3)
5 Heat Engines
77(36)
5.1 Introduction
77(1)
5.2 Stirling Engines
78(2)
5.3 Heat Engines with Ericsson Cycle
80(5)
5.4 Micro-Channel Recuperators for Heat Engines
85(2)
5.5 Recuperator Parameters Evaluation
87(6)
5.6 Quasi-isothermal Heat Engine for Concentrating Solar Power System
93(17)
5.6.1 Introduction
94(1)
5.6.2 Rolling Piston Expanders and Compressors
95(4)
5.6.3 One-Valve Quasi-isothermal Heat Engine
99(1)
5.6.4 Valve-Less Rolling Piston Heat Engine
100(5)
5.6.5 Relative Efficiency
105(5)
References
110(3)
6 Travelling Energy Collectors
113(10)
6.1 Power Plant Based on Travelling Energy Collectors
114(1)
6.2 Scheme of Travelling Energy Collectors
115(3)
6.3 Solar Concentrators
118(3)
6.3.1 Solar Energy Mode
118(1)
6.3.2 Wind Mode
119(1)
6.3.3 Transport and Discharge Modes
120(1)
6.3.4 TEC Number
121(1)
References
121(2)
7 Automatization of Solar Concentrator Manufacture and Assembly
123(38)
7.1 Automatic System for Adjusting the Parabolic Surface
123(5)
7.2 Texture Recognition for Mirror Position Recognition
128(13)
7.2.1 Random Subspace Classifier
130(3)
7.2.2 Software for RSC Simulation
133(7)
7.2.3 Tests
140(1)
7.2.4 Center Calculation
141(1)
7.3 Small Flat-Facet Solar Concentrators
141(8)
7.3.1 System of Automatic Assembly
143(3)
7.3.2 Takeoff Procedure
146(2)
7.3.3 Pinhole Task
148(1)
7.4 Low-Cost Solar Concentrators
149(8)
7.4.1 Automation
150(2)
7.4.2 Lightweight and Rigid Materials
152(2)
7.4.3 New Method for Manufacturing Solar Concentrators
154(3)
References
157(4)
8 Computer Intelligent Systems for Manufacture and Control
161(66)
8.1 Microcomponent Measurement with Neural Networks
162(15)
8.1.1 Artificial Intelligence Methods
162(1)
8.1.2 Micro Pistons Image Database
163(2)
8.1.3 Extraction of Contours
165(2)
8.1.4 LIRA Neural Classifier
167(3)
8.1.5 Preliminary Results
170(3)
8.1.6 Measurements of Micro Pistons
173(4)
8.2 FPGA Realization of the LIRA Neural Classifier
177(14)
8.2.1 Implementation of FPGA
177(1)
8.2.2 LIRA Processes Simulation
178(3)
8.2.3 Neuron Model
181(1)
8.2.4 LIRA Neural Classifier Implementation for Two Classes
182(4)
8.2.5 Results
186(5)
8.3 Ensemble Neural Networks
191(11)
8.3.1 Neural Ensemble Formation
191(2)
8.3.2 Ensemble Neural Network Structure
193(6)
8.3.3 Storage Capacity Investigation
199(1)
8.3.4 Examples of Manipulator Maneuvers
200(2)
8.4 Hebbian Ensemble Neural Network for Robot Movement Control
202(20)
8.4.1 Hebbian Ensemble Network Description
203(3)
8.4.2 Ensemble Presentation of Robot Movements
206(3)
8.4.3 Examples of Robot Maneuvers
209(13)
References
222(5)
9 Examples of Computer Vision Systems Applications Based on Neural Networks
227
9.1 Face Recognition
227(25)
9.1.1 Introduction
227(2)
9.1.2 FRAV3D Face Database Descriptions
229(1)
9.1.3 PCNC
230(9)
9.1.4 Method of Error Calculation
239(1)
9.1.5 Results
240(6)
9.1.6 Rotation Distortions
246(3)
9.1.7 Skewing Procedure for Image Distortions
249(2)
9.1.8 Conclusion
251(1)
9.2 Recognition on FEI Image Database
252(9)
9.2.1 PCNC Algorithms
253(5)
9.2.2 FEI Image Database and Distortions
258(2)
9.2.3 Results of FEI Image Recognition Experiments
260(1)
9.3 Facial Recognition on the Basis of Facial Fragments
261(8)
9.3.1 PCNC for Facial Fragments Recognition
264(1)
9.3.2 LWF Image Database
265(2)
9.3.3 Experiments and Results
267(2)
9.3.4 Conclusion
269(1)
9.4 Recognition of Pests on Crops with a Random Subspace Classifier
269(11)
9.4.1 Description of Colorado Potato Beetle Image Dataset
270(3)
9.4.2 Image Analysis
273(1)
9.4.3 RSC Structure and Algorithm
273(3)
9.4.4 Results
276(1)
9.4.5 Conclusion
276(2)
9.4.6 Future Work
278(2)
References
280