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Evolutionary methods based modeling ...

Das, Biplab.

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Evolutionary methods based modeling and analysis of solar thermal systems = a case studies approach /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Evolutionary methods based modeling and analysis of solar thermal systems/ edited by Biplab Das, Jagadish.
Reminder of title:	a case studies approach /
other author:	Das, Biplab.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xx, 128 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Modeling and optimization of energetic and exergetic performance of solar air collector -- Expert system based thermal performance analysis of corrugated absorber plate based solar air collector -- Investigation of thermal performance of SAC variables using fuzzy logic-based expert system -- Sustainability assessment of solar air collector using deep learning.
Contained By:	Springer Nature eBook
Subject:	Solar collectors - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-031-27635-4
ISBN:	9783031276354

Evolutionary methods based modeling and analysis of solar thermal systems = a case studies approach /
Evolutionary methods based modeling and analysis of solar thermal systemsa case studies approach /[electronic resource] :edited by Biplab Das, Jagadish. - Cham :Springer International Publishing :2023. - xx, 128 p. :ill., digital ;24 cm. - Mechanical engineering series,2192-063X. - Mechanical engineering series..

Introduction -- Modeling and optimization of energetic and exergetic performance of solar air collector -- Expert system based thermal performance analysis of corrugated absorber plate based solar air collector -- Investigation of thermal performance of SAC variables using fuzzy logic-based expert system -- Sustainability assessment of solar air collector using deep learning.

This book presents insights into the thermal performance of solar thermal collectors using both computational and experimental modeling. It consists of various computational and experimental case studies conducted by the authors on the solar thermal collector system. The authors begin by developing thermal modeling using a case study that shows the effect of different governing parameters. A few more experimental cases studies follow that highlight the energy, exergy, and environmental performance of the solar thermal collector system and to examine the performance of a modified solar collector system, illustrating performance improvement techniques. Finally, application of different evolutionary optimization techniques such as soft computing and evolutionary methods, like fuzzy techniques, MCDM methods like fuzzy logic based expert system (FLDS), Artificial Neural Network (ANN), Grey relational analysis (GRA), Entropy-Jaya algorithm, Entropy-VIKOR etc. are employed. Covers improvement of solar thermal systems and advances in solar air collector systems, modeling, and optimization; Includes modeling and parametric optimization issues for the practitioners of solar thermal industries; Provides a new method for modeling and optimizing solar air collectors using actual case studies from the field.

ISBN: 9783031276354

Standard No.: 10.1007/978-3-031-27635-4doiSubjects--Topical Terms:

3631493
Solar collectors
--Mathematical models.

LC Class. No.: TJ812 / .E96 2023

Dewey Class. No.: 621.472

Evolutionary methods based modeling and analysis of solar thermal systems = a case studies approach /
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505 0 $a Introduction -- Modeling and optimization of energetic and exergetic performance of solar air collector -- Expert system based thermal performance analysis of corrugated absorber plate based solar air collector -- Investigation of thermal performance of SAC variables using fuzzy logic-based expert system -- Sustainability assessment of solar air collector using deep learning.
520 $a This book presents insights into the thermal performance of solar thermal collectors using both computational and experimental modeling. It consists of various computational and experimental case studies conducted by the authors on the solar thermal collector system. The authors begin by developing thermal modeling using a case study that shows the effect of different governing parameters. A few more experimental cases studies follow that highlight the energy, exergy, and environmental performance of the solar thermal collector system and to examine the performance of a modified solar collector system, illustrating performance improvement techniques. Finally, application of different evolutionary optimization techniques such as soft computing and evolutionary methods, like fuzzy techniques, MCDM methods like fuzzy logic based expert system (FLDS), Artificial Neural Network (ANN), Grey relational analysis (GRA), Entropy-Jaya algorithm, Entropy-VIKOR etc. are employed. Covers improvement of solar thermal systems and advances in solar air collector systems, modeling, and optimization; Includes modeling and parametric optimization issues for the practitioners of solar thermal industries; Provides a new method for modeling and optimizing solar air collectors using actual case studies from the field.
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