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Soft Computing for Sustainability Science

Overview of attention for book
Cover of 'Soft Computing for Sustainability Science'

Table of Contents

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    Book Overview
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    Chapter 1 Soft Computing Techniques and Sustainability Science, an Introduction
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    Chapter 2 Vessels Fuel Consumption: A Data Analytics Perspective to Sustainability
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    Chapter 3 FuzzyCovering: A Spatial Decision Support System for Solving Fuzzy Covering Location Problems
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    Chapter 4 A Fuzzy Location Problem Based Upon Georeferenced Data
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    Chapter 5 A Review of the Application to Emergent Subfields in Viticulture of Local Reflectance and Interactance Spectroscopy Combined with Soft Computing and Multivariate Analysis
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    Chapter 6 Consumer Segmentation Through Multi-instance Clustering Time-Series Energy Data from Smart Meters
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    Chapter 7 A Multicriteria Group Decision Model for Ranking Technology Packages in Agriculture
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    Chapter 8 Fuzzy Degree of Geographic Appropriateness for Social Impact Investing
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    Chapter 9 A New Approach for Information Dissemination in VANETs Based on Covering Location and Metaheuristics
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    Chapter 10 Product Matching to Determine the Energy Efficiency of Used Cars Available at Internet Marketplaces
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    Chapter 11 Fault Diagnosis in a Steam Generator Applying Fuzzy Clustering Techniques
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    Chapter 12 An Updated Review on Watershed Algorithms
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    Chapter 13 An Application Sample of Machine Learning Tools, Such as SVM and ANN, for Data Editing and Imputation
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    Chapter 14 Multimodal Transport Network Problem: Classical and Innovative Approaches
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    Chapter 15 A Linguistic 2-Tuple Based Environmental Impact Assessment for Maritime Port Projects: Application to Moa Port
Attention for Chapter 8: Fuzzy Degree of Geographic Appropriateness for Social Impact Investing
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Chapter title
Fuzzy Degree of Geographic Appropriateness for Social Impact Investing
Chapter number 8
Book title
Soft Computing for Sustainability Science
Published by
Springer, Cham, July 2017
DOI 10.1007/978-3-319-62359-7_8
Book ISBNs
978-3-31-962358-0, 978-3-31-962359-7
Authors

Vicente Liern, Blanca Pérez-Gladish

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 14%
Student > Doctoral Student 2 14%
Student > Ph. D. Student 2 14%
Professor 1 7%
Unspecified 1 7%
Other 2 14%
Unknown 4 29%
Readers by discipline Count As %
Business, Management and Accounting 4 29%
Social Sciences 3 21%
Engineering 2 14%
Unspecified 1 7%
Unknown 4 29%

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