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Decision Support for Product Development : Using Computational Intelligence for Information Acquisition in Enterprise Databases / by Marcin Relich

By: Relich, Marcin, autor
Contributor(s): SpringerLink
Material type: materialTypeLabelE-bookSeries: (Computational Intelligence Methods and Applications, 2510-1765).Publisher: Cham, Switzerland : Springer International Publising, 2021Edition: First edition 2021.Description: 1 recurso en línea (XII, 114 páginas) : 55 ilustraciones, 16 ilustraciones a color.ISBN: 9783030438975.Subject: Inteligencia artificial | Nuevos productosOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Product Development: State of the Art and Challenges -- Model for Formulating Decision Problems Within Portfolio Management -- Method for Supporting Product Development -- A Decision Support System for Portfolio Management of NPD Projects -- Implications for Management.
Abstract: This book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new product development. These approaches, including artificial neural networks and constraint satisfaction solutions, enable a more precise prediction of product development performance compared to widely used multiple regression models. They support decision-makers by providing more reliable information regarding, for example, project portfolio selection and project scheduling. The book is appropriate for computer scientists, management scientists, students and practitioners engaged with product innovation and computational intelligence applications.
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería Q335 2021 EB (Browse shelf(Opens below)) Acceso electrónico eBook.26042124
Total holds: 0

Product Development: State of the Art and Challenges -- Model for Formulating Decision Problems Within Portfolio Management -- Method for Supporting Product Development -- A Decision Support System for Portfolio Management of NPD Projects -- Implications for Management.

This book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new product development. These approaches, including artificial neural networks and constraint satisfaction solutions, enable a more precise prediction of product development performance compared to widely used multiple regression models. They support decision-makers by providing more reliable information regarding, for example, project portfolio selection and project scheduling. The book is appropriate for computer scientists, management scientists, students and practitioners engaged with product innovation and computational intelligence applications.

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