Isbn: 9783642292125 - data processing for the ahp/anp: 1 (17 risultati)

Condizione: New.

Hardback or Cased Book. Condizione: New. Data Processing for the Ahp/Anp. Book.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. In English.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. pp. 150.

Hardcover. Condizione: Brand New. 2013 edition. 125 pages. 9.25x6.25x0.50 inches. In Stock.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank reversal.The maximum eigenvalue threshold method is proposed as the new consistency index for the AHP/ANP. An induced bias matrix model (IBMM) is proposed to identify and adjust the inconsistent data, and estimate the missing or uncertain data.Two applications of IBMM including risk assessment and decision analysis, task scheduling and resource allocation in cloud computing environment, are introduced to illustrate the proposed IBMM.…

Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank reversal. The maximum eigenvalue threshold method is proposed as the new consistency index for the AHP/ANP. An induced bias matrix model (IBMM) is proposed to identify and adjust the inconsistent data, and estimate the missing or uncertain data. Two applications of IBMM including risk assessment and decision analysis, task scheduling and resource allocation in cloud computing environment, are introduced to illustrate the proposed IBMM.…

Condizione: new. Questo è un articolo print on demand.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank reversal.The maximum eigenvalue threshold method is proposed as the new consistency index for the AHP/ANP. An induced bias matrix model (IBMM) is proposed to identify and adjust the inconsistent data, and estimate the missing or uncertain data.Two applications of IBMM including risk assessment and decision analysis, task scheduling and resource allocation in cloud computing environment, are introduced to illustrate the proposed IBMM. 148 pp. Englisch.…

Condizione: New. Print on Demand pp. 150 22 Illus.

Condizione: New. PRINT ON DEMAND pp. 150.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A timely report of state-of-the art analytical techniques An analysis of different methods such as an induced bias matrix model (IBMM) for the data processing A method of missing item score estimation in questionnaire A proposal of i.…

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank reversal. The maximum eigenvalue threshold method is proposed as the new consistency index for the AHP/ANP. An induced bias matrix model (IBMM) is proposed to identify and adjust the inconsistent data, and estimate the missing or uncertain data. Two applications of IBMM including risk assessment and decision analysis, task scheduling and resource allocation in cloud computing environment, are introduced to illustrate the proposed IBMM.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch.…