Coolen ton (10 resultados)
Más imágenesIdioma: Inglés
Editorial: NaN
- Tapa blanda
Librería: Bookbot, Prague, Republica ChecaBookbot
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 3,80
Envío por EUR 20,99Se envía de Republica Checa a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Softcover. Condición: As New. Leichte Kratzer / Abnutzungen / Druckstellen.
- Tapa dura
Librería: Phatpocket Limited, Waltham Abbey, HERTS, Reino UnidoPhatpocket Limited
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Aceptable
EUR 89,84
Envío por EUR 12,46Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.
- Tapa dura
Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 122,20
Envío por EUR 21,83Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 15 disponibles
Hardback. Condición: New. New copy - Usually dispatched within 4 working days.
- Tapa dura
- Impresión bajo demanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 122,42
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Generating random networks efficiently and accurately is an important challenge for practical applications, and an interesting question for theoretical study. This book presents and discusses common methods of generating random graphs. It begins with approaches such as Exponential Random Gra…ph Models, where the targeted probability of each network appearing in the ensemble is specified. This section also includes degree-preserving randomisation algorithms, where theaim is to generate networks with the correct number of links at each node, and care must be taken to avoid introducing a bias. Separately, it looks at growth style algorithms (e.g. preferentialattachment) which aim to model a real process and then to analyse the resulting ensemble of graphs. It also covers how to generate special types of graphs including modular graphs, graphs with community structure and temporal graphs.The book is aimed at the graduate student or advanced undergraduate. It includes many worked examples and open questions making it suitable for use in teaching. Explicit pseudocode algorithms are included throughout the book to make the ideasstraightforward to apply.With larger and larger datasets, it is crucial to have practical and well-understood tools. Being able to test a hypothesis against a properly specifiedcontrol case is at the heart of the 'scientific method'. Hence, knowledge on how to generate controlled and unbiased random graph ensembles is vital for anybody wishing to apply network science in their research. This book describes how to correctly and efficiently generate random networks based on certain constraints. Being able to test a hypothesis against a properly specified control case is at the heart of the 'scientific method'. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
- Tapa dura
- Impresión bajo demanda
Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 156,85
Envío por EUR 3,50Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. Print on Demand.
- Tapa dura
- Impresión bajo demanda
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 163,02
Envío por EUR 7,61Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. Print on Demand.
- Tapa dura
- Impresión bajo demanda
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 163,40
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. PRINT ON DEMAND.
- Tapa dura
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 135,63
Envío por EUR 43,31Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Generating random networks efficiently and accurately is an important challenge for practical applications, and an interesting question for theoretical study. This book presents and discusses common methods of generating random graphs. It begins with approaches such as Exponential Random Gra…ph Models, where the targeted probability of each network appearing in the ensemble is specified. This section also includes degree-preserving randomisation algorithms, where theaim is to generate networks with the correct number of links at each node, and care must be taken to avoid introducing a bias. Separately, it looks at growth style algorithms (e.g. preferentialattachment) which aim to model a real process and then to analyse the resulting ensemble of graphs. It also covers how to generate special types of graphs including modular graphs, graphs with community structure and temporal graphs.The book is aimed at the graduate student or advanced undergraduate. It includes many worked examples and open questions making it suitable for use in teaching. Explicit pseudocode algorithms are included throughout the book to make the ideasstraightforward to apply.With larger and larger datasets, it is crucial to have practical and well-understood tools. Being able to test a hypothesis against a properly specifiedcontrol case is at the heart of the 'scientific method'. Hence, knowledge on how to generate controlled and unbiased random graph ensembles is vital for anybody wishing to apply network science in their research. This book describes how to correctly and efficiently generate random networks based on certain constraints. Being able to test a hypothesis against a properly specified control case is at the heart of the 'scientific method'. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Tapa dura
- Impresión bajo demanda
Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 110,60
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Buch. Condición: Neu. Generating Random Networks and Graphs | Ton Coolen | Buch | Gebunden | Englisch | 2017 | Oxford University Press(UK) | EAN 9780198709893 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
- Tapa dura
- Impresión bajo demanda
Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 132,12
Envío por EUR 63,70Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Generating random networks efficiently and accurately is an important challenge for practical applications, and an interesting question for theoretical study. This book presents and discusses common methods of generating random graphs. It begin…s with approaches such as Exponential Random GraphModels, where the targeted probability of each network appearing in the ensemble is specified. This section also includes degree-preserving randomisation algorithms, where the aim is to generate networks with the correct number of links at each node, and care must be taken to avoid introducing abias. Separately, it looks at growth style algorithms (e.g. preferential attachment) which aim to model a real process and then to analyse the resulting ensemble of graphs. It also covers how to generate special types of graphs including modular graphs, graphs with community structure and temporalgraphs. The book is aimed at the graduate student or advanced undergraduate. It includes many worked examples and open questions making it suitable for use in teaching. Explicit pseudocode algorithms are included throughout the book to make the ideas straightforward to apply. With larger and larger datasets, it is crucial to have practical and well-understood tools. Being able to test a hypothesis against a properly specified control case is at the heart of the 'scientific method'. Hence, knowledge on how to generate controlled and unbiased random graph ensembles isvital for anybody wishing to apply network science in their research.
