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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
  2. Altmetric Badge
    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 10: Product Matching to Determine the Energy Efficiency of Used Cars Available at Internet Marketplaces
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Mentioned by

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1 X user

Citations

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5 Mendeley
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Chapter title
Product Matching to Determine the Energy Efficiency of Used Cars Available at Internet Marketplaces
Chapter number 10
Book title
Soft Computing for Sustainability Science
Published in
Studies in Fuzziness and Soft Computing, July 2017
DOI 10.1007/978-3-319-62359-7_10
Book ISBNs
978-3-31-962358-0, 978-3-31-962359-7
Authors

Mario Rivas-Sánchez, Maria P. Guerrero-Lebrero, Elisa Guerrero, Guillermo Bárcena-Gonzalez, Jaime Martel, Pedro L. Galindo

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 2 40%
Professor 1 20%
Other 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 4 80%
Unknown 1 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 July 2017.
All research outputs
#17,732,227
of 25,992,468 outputs
Outputs from Studies in Fuzziness and Soft Computing
#1
of 1 outputs
Outputs of similar age
#211,564
of 329,324 outputs
Outputs of similar age from Studies in Fuzziness and Soft Computing
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 1.0. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,324 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them