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Soft Computing Applications in Industry

Overview of attention for book
Cover of 'Soft Computing Applications in Industry'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Optimization of Industrial Processes Using Improved and Modified Differential Evolution
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    Chapter 2 Noise-Robust Tool Condition Monitoring in Micro-milling with Hidden Markov Models
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    Chapter 3 Dynamically Self-generated Fuzzy Neural Networks with Industry Applications
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    Chapter 4 Kernel Estimators in Industrial Applications
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    Chapter 5 Negative Selection Algorithm with Applications in Motor Fault Detection
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    Chapter 6 Harmony Search Applications in Industry
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    Chapter 7 Soft Computing in Bioinformatics: Genomic and Proteomic Applications
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    Chapter 8 Evolutionary Regression and Neural Imputations of Missing Values
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    Chapter 9 Glowworm Swarm Optimization Algorithm for Hazard Sensing in Ubiquitous Environments Using Heterogeneous Agent Swarms
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    Chapter 10 Self-organization in Evolution for the Solving of Distributed Terrestrial Transportation Problems
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    Chapter 11 Statistical Forecasting of Indian Summer Monsoon Rainfall: An Enduring Challenge
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    Chapter 12 Fault Diagnosis of Electronic Circuits Using Cellular Automata Based Pattern Classifier
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    Chapter 13 A Survey of Artificial Neural Network-Based Modeling in Agroecology
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    Chapter 14 Software Development Knowledge Management Using Case-Based Reasoning
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    Chapter 15 Learning from Demonstration and Case-Based Planning for Real-Time Strategy Games
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    Chapter 16 A CBR System: The Core of an Ambient Intelligence Health Care Application
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    Chapter 17 Soft Query-Answering Computing in P2P Systems with Epistemically Independent Peers
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    Chapter 18 Power Distribution System Fault Diagnosis Using Hybrid Algorithm of Fuzzy Classification and Artificial Immune Systems
  20. Altmetric Badge
    Chapter 19 Detection of Phishing Attacks: A Machine Learning Approach
Overall attention for this book and its chapters
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About this Attention Score

  • High Attention Score compared to outputs of the same age (80th percentile)

Mentioned by

blogs
1 blog

Readers on

mendeley
34 Mendeley
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Title
Soft Computing Applications in Industry
Published by
Studies in Fuzziness and Soft Computing, January 2008
DOI 10.1007/978-3-540-77465-5
ISBNs
978-3-54-077464-8, 978-3-54-077465-5
Authors

Bhanu Prasad

Editors

Prasad, Bhanu

Timeline

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 2 6%
Colombia 1 3%
Unknown 31 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 15%
Student > Master 5 15%
Student > Doctoral Student 4 12%
Student > Ph. D. Student 4 12%
Student > Bachelor 2 6%
Other 6 18%
Unknown 8 24%
Readers by discipline Count As %
Computer Science 13 38%
Engineering 6 18%
Agricultural and Biological Sciences 4 12%
Mathematics 1 3%
Environmental Science 1 3%
Other 0 0%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 09 July 2014.
All research outputs
#6,602,534
of 25,992,468 outputs
Outputs from Studies in Fuzziness and Soft Computing
#1
of 1 outputs
Outputs of similar age
#34,132
of 170,919 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 has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. 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 170,919 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
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