Yingping (27 resultados)

Condición: New.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Hardback. Condición: New. A comprehensive handbook on state-of-the-art DAS technology and applications Distributed Acoustic Sensing (DAS) is a technology that records sound and vibration signals along a fiber optic cable. Its advantages of high resolution, continuous, and real-time measurements mean that DAS systems have been rapidly adopted for a range of applications, including hazard mitigation, energy industries, geohydrology, environmental monitoring, and civil engineering. Distributed Acoustic Sensing in Geophysics: Methods and Applications presents experiences from both industry and academia on using DAS in a range of geophysical applications. Volume highlights include: DAS concepts, principles, and measurementsComprehensive review of the historical development of DAS and related technologiesDAS applications in hydrocarbon, geothermal, and mining industriesDAS applications in seismologyDAS applications in environmental and shallow geophysics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.…

Gebunden. Condición: New. Yingping Li, BlueSkyDas, USAMartin Karrenbach, OptaSense Inc., USAJonathan B. Ajo-Franklin, Rice University and Lawrence Berkeley National Laboratory, USADistributed Acoustic Sensing in GeophysicsMethods and ApplicationsDistributed Acoustic Sensing (DAS.

Hardcover. Condición: Brand New. 350 pages. 10.51x7.99x0.20 inches. In Stock.

Hardback. Condición: New. A comprehensive handbook on state-of-the-art DAS technology and applications Distributed Acoustic Sensing (DAS) is a technology that records sound and vibration signals along a fiber optic cable. Its advantages of high resolution, continuous, and real-time measurements mean that DAS systems have been rapidly adopted for a range of applications, including hazard mitigation, energy industries, geohydrology, environmental monitoring, and civil engineering. Distributed Acoustic Sensing in Geophysics: Methods and Applications presents experiences from both industry and academia on using DAS in a range of geophysical applications. Volume highlights include: DAS concepts, principles, and measurementsComprehensive review of the historical development of DAS and related technologiesDAS applications in hydrocarbon, geothermal, and mining industriesDAS applications in seismologyDAS applications in environmental and shallow geophysics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.…

Buch. Condición: Neu. Neuware - A comprehensive handbook on state-of-the-art DAS technology and applicationsDistributed Acoustic Sensing (DAS) is a technology that records sound and vibration signals along a fiber optic cable. Its advantages of high resolution, continuous, and real-time measurements mean that DAS systems have been rapidly adopted for a range of applications, including hazard mitigation, energy industries, geohydrology, environmental monitoring, and civil engineering.Distributed Acoustic Sensing in Geophysics: Methods and Applications presents experiences from both industry and academia on using DAS in a range of geophysical applications.Volume highlights include:\* DAS concepts, principles, and measurements\* Comprehensive review of the historical development of DAS and related technologies\* DAS applications in hydrocarbon, geothermal, and mining industries\* DAS applications in seismology\* DAS applications in environmental and shallow geophysicsThe American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.…

Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Condición: New.

Soft cover. Condición: New. Language:Chinese,English.Author:Xie Yingping.Binding:Soft Cover.

Hardcover. Condición: New. Language:Chinese.Author:Xie Yingping.Binding:HardCover.

Hardcover. Condición: New. Language:Chinese,English.Author:Xie Yingping.Binding:HardCover.

Hardcover. Condición: new. Hardcover. The global transition towards sustainable energy systems necessitates the seamless integration of variable renewable sources like solar and wind. However, the intermittent nature of renewables and the complex dynamics of power electronics pose significant challenges to system stability and reliable operation. Artificial intelligence, with its powerful capabilities in prediction, optimization, and adaptive control, has emerged as a pivotal enabler for managing the inherent complexity and uncertainty of modern hybrid renewable energy systems (HRES). This Reprint presents a collection of high-quality research addressing the design, operation, and optimization of AI-based energy management systems (EMS) for HRES. The contributions explore cutting-edge applications of machine learning, deep learning, and advanced control algorithms to enhance the efficiency, reliability, and economic viability of integrated energy systems. Topics covered include predictive maintenance for system components, intelligent forecasting of renewable generation and load demand, multi-objective optimization for real-time dispatch and storage control, and the development of digital twin frameworks for system simulation and resilience analysis. By presenting novel methodologies, empirical case studies, and quantitative findings, this volume provides significant new insights and practical tools. It demonstrates how AI-driven EMS can unlock greater energy autonomy, facilitate higher penetrations of renewables, and contribute decisively to the development of smarter, more resilient, and sustainable power grids. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condición: new. Hardcover. The global transition towards sustainable energy systems necessitates the seamless integration of variable renewable sources like solar and wind. However, the intermittent nature of renewables and the complex dynamics of power electronics pose significant challenges to system stability and reliable operation. Artificial intelligence, with its powerful capabilities in prediction, optimization, and adaptive control, has emerged as a pivotal enabler for managing the inherent complexity and uncertainty of modern hybrid renewable energy systems (HRES). This Reprint presents a collection of high-quality research addressing the design, operation, and optimization of AI-based energy management systems (EMS) for HRES. The contributions explore cutting-edge applications of machine learning, deep learning, and advanced control algorithms to enhance the efficiency, reliability, and economic viability of integrated energy systems. Topics covered include predictive maintenance for system components, intelligent forecasting of renewable generation and load demand, multi-objective optimization for real-time dispatch and storage control, and the development of digital twin frameworks for system simulation and resilience analysis. By presenting novel methodologies, empirical case studies, and quantitative findings, this volume provides significant new insights and practical tools. It demonstrates how AI-driven EMS can unlock greater energy autonomy, facilitate higher penetrations of renewables, and contribute decisively to the development of smarter, more resilient, and sustainable power grids. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Condición: new. Hardcover. The global transition towards sustainable energy systems necessitates the seamless integration of variable renewable sources like solar and wind. However, the intermittent nature of renewables and the complex dynamics of power electronics pose significant challenges to system stability and reliable operation. Artificial intelligence, with its powerful capabilities in prediction, optimization, and adaptive control, has emerged as a pivotal enabler for managing the inherent complexity and uncertainty of modern hybrid renewable energy systems (HRES). This Reprint presents a collection of high-quality research addressing the design, operation, and optimization of AI-based energy management systems (EMS) for HRES. The contributions explore cutting-edge applications of machine learning, deep learning, and advanced control algorithms to enhance the efficiency, reliability, and economic viability of integrated energy systems. Topics covered include predictive maintenance for system components, intelligent forecasting of renewable generation and load demand, multi-objective optimization for real-time dispatch and storage control, and the development of digital twin frameworks for system simulation and resilience analysis. By presenting novel methodologies, empirical case studies, and quantitative findings, this volume provides significant new insights and practical tools. It demonstrates how AI-driven EMS can unlock greater energy autonomy, facilitate higher penetrations of renewables, and contribute decisively to the development of smarter, more resilient, and sustainable power grids. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The global transition towards sustainable energy systems necessitates the seamless integration of variable renewable sources like solar and wind. However, the intermittent nature of renewables and the complex dynamics of power electronics pose significant challenges to system stability and reliable operation. Artificial intelligence, with its powerful capabilities in prediction, optimization, and adaptive control, has emerged as a pivotal enabler for managing the inherent complexity and uncertainty of modern hybrid renewable energy systems (HRES). This Reprint presents a collection of high-quality research addressing the design, operation, and optimization of AI-based energy management systems (EMS) for HRES. The contributions explore cutting-edge applications of machine learning, deep learning, and advanced control algorithms to enhance the efficiency, reliability, and economic viability of integrated energy systems. Topics covered include predictive maintenance for system components, intelligent forecasting of renewable generation and load demand, multi-objective optimization for real-time dispatch and storage control, and the development of digital twin frameworks for system simulation and resilience analysis. By presenting novel methodologies, empirical case studies, and quantitative findings, this volume provides significant new insights and practical tools. It demonstrates how AI-driven EMS can unlock greater energy autonomy, facilitate higher penetrations of renewables, and contribute decisively to the development of smarter, more resilient, and sustainable power grids.…

Buch. Condición: Neu. Digital Modeling, Operation and Control of Sustainable Energy Systems | Buch | Englisch | 2026 | MDPI AG | EAN 9783725881055 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condición: new. Hardcover. A comprehensive handbook on state-of-the-art DAS technology and applications Distributed Acoustic Sensing (DAS) is a technology that records sound and vibration signals along a fiber optic cable. Its advantages of high resolution, continuous, and real-time measurements mean that DAS systems have been rapidly adopted for a range of applications, including hazard mitigation, energy industries, geohydrology, environmental monitoring, and civil engineering. Distributed Acoustic Sensing in Geophysics: Methods and Applications presents experiences from both industry and academia on using DAS in a range of geophysical applications. Volume highlights include: DAS concepts, principles, and measurementsComprehensive review of the historical development of DAS and related technologiesDAS applications in hydrocarbon, geothermal, and mining industriesDAS applications in seismologyDAS applications in environmental and shallow geophysics The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…