國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

AI and IOT in renewable energy

Shaw, Rabindra Nath.

AI and IOT in renewable energy

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI and IOT in renewable energyedited by Rabindra Nath Shaw ... [et al.].
其他作者:	Shaw, Rabindra Nath.
出版者:	Singapore :Springer Singapore :2021.
面頁冊數:	xii, 109 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligence.
電子資源:	https://doi.org/10.1007/978-981-16-1011-0
ISBN:	9789811610110$q(electronic bk.)

AI and IOT in renewable energy
AI and IOT in renewable energy[electronic resource] /edited by Rabindra Nath Shaw ... [et al.]. - Singapore :Springer Singapore :2021. - xii, 109 p. :ill., digital ;24 cm. - Studies in infrastructure and control,2730-6453. - Studies in infrastructure and control..

A Day Ahead Power Output Forecasting of three PV Systems using Regression, Machine Learning and Deep Learning Techniques -- Internet of Things and Internet of Drones in the Renewable Energy Infrastructure Towards Energy Optimization -- Reinforcement Learning Algorithm to Reduce Energy Consumption in Electric Vehicles -- Spotted Hyena Optimization (SHO) Algorithm based Novel Control Approach for Buck DC-DC Converter Fed PMBLDC Motor -- Simulation and Performance Analysis of Standalone Photovoltaic System with Boost Converter Under Irradiation and Temperature -- Analysis of Variation in Locational Marginal Pricing under Influence of Stochastic Wind Generation -- Optimal Integration of Plug-In Electric Vehicles Within a Distribution Network Using Genetic Algorithm -- Frequency Control of 5kW Self-Excited Induction Generator Using Gravitational Search Algorithm and Genetic Algorithm -- Cloud Based Real-time Vibration and Temperature Monitoring System for Wind Turbine -- Smart Solar-Powered Smart Agricultural Monitoring System Using Internet of Things Devices.

This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.

ISBN: 9789811610110$q(electronic bk.)

Standard No.: 10.1007/978-981-16-1011-0doiSubjects--Topical Terms:

194058
Artificial intelligence.

LC Class. No.: Q335 / .A5 2021

Dewey Class. No.: 006.3

AI and IOT in renewable energy
LDR:03386nmm a2200349 a 4500 001 598589
003 DE-He213
005 20210512133438.0
006 m d
007 cr nn 008maaau
008 211025s2021 si s 0 eng d
020 $a 9789811610110$q(electronic bk.)
020 $a 9789811610103$q(paper)
024 7 $a 10.1007/978-981-16-1011-0 $2 doi
035 $a 978-981-16-1011-0
040 $a GP $c GP
041 0 $a eng
050 4 $a Q335 $b .A5 2021
072 7 $a THR $2 bicssc
072 7 $a TEC007000 $2 bisacsh
072 7 $a THR $2 thema
072 7 $a GPFC $2 thema
082 0 4 $a 006.3 $2 23
090 $a Q335 $b .A288 2021
245 0 0 $a AI and IOT in renewable energy $h [electronic resource] / $c edited by Rabindra Nath Shaw ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2021.
300 $a xii, 109 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in infrastructure and control, $x 2730-6453
505 0 $a A Day Ahead Power Output Forecasting of three PV Systems using Regression, Machine Learning and Deep Learning Techniques -- Internet of Things and Internet of Drones in the Renewable Energy Infrastructure Towards Energy Optimization -- Reinforcement Learning Algorithm to Reduce Energy Consumption in Electric Vehicles -- Spotted Hyena Optimization (SHO) Algorithm based Novel Control Approach for Buck DC-DC Converter Fed PMBLDC Motor -- Simulation and Performance Analysis of Standalone Photovoltaic System with Boost Converter Under Irradiation and Temperature -- Analysis of Variation in Locational Marginal Pricing under Influence of Stochastic Wind Generation -- Optimal Integration of Plug-In Electric Vehicles Within a Distribution Network Using Genetic Algorithm -- Frequency Control of 5kW Self-Excited Induction Generator Using Gravitational Search Algorithm and Genetic Algorithm -- Cloud Based Real-time Vibration and Temperature Monitoring System for Wind Turbine -- Smart Solar-Powered Smart Agricultural Monitoring System Using Internet of Things Devices.
520 $a This book presents the latest research on applications of artificial intelligence and the Internet of Things in renewable energy systems. Advanced renewable energy systems must necessarily involve the latest technology like artificial intelligence and Internet of Things to develop low cost, smart and efficient solutions. Intelligence allows the system to optimize the power, thereby making it a power efficient system; whereas, Internet of Things makes the system independent of wire and flexibility in operation. As a result, intelligent and IOT paradigms are finding increasing applications in the study of renewable energy systems. This book presents advanced applications of artificial intelligence and the internet of things in renewable energy systems development. It covers such topics as solar energy systems, electric vehicles etc. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities engaged in the study and performance prediction of renewable energy systems.
650 0 $a Artificial intelligence. $3 194058
650 0 $a Internet of things. $3 670954
650 0 $a Renewable energy sources. $3 190766
650 1 4 $a Cyber-physical systems, IoT. $3 836359
650 2 4 $a Professional Computing. $3 763344
650 2 4 $a Renewable and Green Energy. $3 309696
700 1 $a Shaw, Rabindra Nath. $3 892403
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in infrastructure and control. $3 892404
856 4 0 $u https://doi.org/10.1007/978-981-16-1011-0
950 $a Engineering (SpringerNature-11647)