Machine learning application reacting (28 resultados)
Idioma: Inglés
Editorial: Springer 2023-01 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 23,11
Envío por EUR 17,87Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 10 disponibles
PF. Condición: New.
Idioma: Inglés
Editorial: Springer International Publishing AG, CH 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Rarewaves.com USA, London, Reino UnidoRarewaves.com USA
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 42,11
Gastos de envío gratisSe envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback. Condición: New. 1st ed. 2023. This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.These two fields, ML and turbulent combustion, hav…e large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world's total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and "greener" combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
Librería: GreatBookPrices, Columbia, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 54,85
Envío por EUR 2,27Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Books Puddle, New York, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 54,70
Envío por EUR 3,42Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 50,54
Envío por EUR 7,50Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Biblios, frankfurt am main, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 51,41
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
Librería: GreatBookPrices, Columbia, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 64,74
Envío por EUR 2,27Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
Idioma: Inglés
Editorial: Springer 2023-01 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Chiron Media, Wallingford, Reino UnidoChiron Media
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 50,64
Envío por EUR 17,87Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 10 disponibles
PF. Condición: New.
Idioma: Inglés
Editorial: Springer International Publishing AG, Cham 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Primera edición
Librería: Grand Eagle Retail, Bensenville, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 70,83
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.These two fields, ML and turbulent combustion, have l…arge body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the worlds total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and greener combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
Librería: Books Puddle, New York, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 75,66
Envío por EUR 3,42Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New.
Machine Learning and Its Application to Reacting Flows: Ml and Combustion
Swaminathan, Nedunchezhian (Editor)/ Parente, Alessandro (Editor)
Idioma: Inglés
Editorial: Springer Nature 2022
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 72,68
Envío por EUR 11,54Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 357 pages. 9.25x6.10x0.75 inches. In Stock.
Idioma: Inglés
Editorial: SPRINGER NP 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
- Edición internacional
Librería: UK BOOKS STORE, London, Reino UnidoUK BOOKS STORE
Contactar con el vendedorVendedor de 5 estrellasEdición internacionalCondición: Nuevo
EUR 81,47
Envío por EUR 6,91Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Condición: New. Brand New ! Fast Delivery "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 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This… Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Machine Learning and Its Application to Reacting Flows: ML and Combustion
Swaminathan, Nedunchezhian (Edited by)/ Parente, Alessandro (Edited by)
Idioma: Inglés
Editorial: Springer 2022
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 88,87
Envío por EUR 14,42Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: Brand New. 357 pages. 9.25x6.10x0.94 inches. In Stock.
Idioma: Inglés
Editorial: SPRINGER NP 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Edición internacional
Librería: UK BOOKS STORE, London, Reino UnidoUK BOOKS STORE
Contactar con el vendedorVendedor de 5 estrellasEdición internacionalCondición: Nuevo
EUR 97,32
Envío por EUR 6,91Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New. Brand New ! Fast Delivery "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 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This… Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Idioma: Inglés
Editorial: Springer International Publishing AG, CH 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 27,97
Envío por EUR 75,00Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Paperback. Condición: New. 1st ed. 2023. This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.These two fields, ML and turbulent combustion, hav…e large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world's total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and "greener" combustion systems that are friendlier to the environment can be designed. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Idioma: Inglés
Editorial: Springer International Publishing 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 42,79
Envío por EUR 62,73Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.These two… fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world's total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and 'greener' combustion systems that are friendlier to the environment can be designed.The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Idioma: Inglés
Editorial: Springer International Publishing 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,49
Envío por EUR 63,86Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.These two fields…, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world's total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and 'greener' combustion systems that are friendlier to the environment can be designed.The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Impresión bajo demanda
Librería: Brook Bookstore On Demand, Napoli, ItaliaBrook Bookstore On Demand
Contactar con el vendedorVendedor de 3 estrellasCondición: Nuevo
EUR 46,22
Envío por EUR 8,00Se envía de Italia a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: new. Questo è un articolo print on demand.
Idioma: Inglés
Editorial: Springer Nature B.V. 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
- Impresión bajo demanda
Librería: PBShop.store US, Wood Dale, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 58,35
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Idioma: Inglés
Editorial: Springer Nature B.V. 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
- Impresión bajo demanda
Librería: PBShop.store UK, Fairford, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 54,01
Envío por EUR 5,79Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
PAP. 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.
Idioma: Inglés
Editorial: Springer International Publishing Jan 2023 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 42,79
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent… flows.These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world's total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and 'greener' combustion systems that are friendlier to the environment can be designed.The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation. 360 pp. Englisch.
Idioma: Inglés
Editorial: Springer International Publishing Jan 2023 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,49
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.…These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world's total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and 'greener' combustion systems that are friendlier to the environment can be designed.The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation. 360 pp. Englisch.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Impresión bajo demanda
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 75,64
Envío por EUR 7,50Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. Print on Demand.
Idioma: Inglés
Editorial: Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Impresión bajo demanda
Librería: Biblios, frankfurt am main, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 76,76
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. PRINT ON DEMAND.
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Université Libre de Bruxelles|University of Cambridge|Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
- Impresión bajo demanda
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 39,60
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically rea…cting turbulent flows.These tw.
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Université Libre de Bruxelles|University of Cambridge|Springer 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Impresión bajo demanda
Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 48,37
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chem…ically reacting turbulent flows.These tw.
Idioma: Inglés
Editorial: Springer International Publishing, Springer International Publishing Jan 2023 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa blanda
- Impresión bajo demanda
Librería: buchversandmimpf2000, Emtmannsberg, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 42,79
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flo…ws.These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world¿s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and ¿greener¿ combustion systems that are friendlier to the environment can be designed.The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 360 pp. Englisch.
Idioma: Inglés
Editorial: Springer International Publishing, Springer International Publishing Jan 2023 2023
Serie: Lecture Notes in Energy, Libro 79 de 81. Libro 79 de 81 - Lecture Notes in Energy
- Tapa dura
- Impresión bajo demanda
Librería: buchversandmimpf2000, Emtmannsberg, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 53,49
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.Thes…e two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world¿s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. Whether this is practical or not is entirely a different question, and an answer to this question depends on the respondent. However, a pragmatic analysis suggests that the combustion share to TPES is likely to be more than 70% even by 2070. Hence, it will be prudent to take advantage of ML techniques to improve combustion sciences and technologies so that efficient and ¿greener¿ combustion systems that are friendlier to the environment can be designed.The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges. The required mathematical equations and backgrounds are discussed with ample references for readers to find further detail if they wish. This book is unique since there is not any book with similar coverage of topics, ranging from big data analysis and machine learning algorithm to their applications for combustion science and system design for energy generation.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 360 pp. Englisch.
