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Multi-disciplinary Trends in Artificial Intelligence

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Cover of 'Multi-disciplinary Trends in Artificial Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 BoWT: A Hybrid Text Representation Model for Improving Text Categorization Based on AdaBoost.MH
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    Chapter 2 An Improved Teaching-Learning Based Optimization for Optimization of Flatness of a Strip During a Coiling Process
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    Chapter 3 An Entailment Procedure for Kleene Answer Set Programs
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    Chapter 4 An Efficient Gaussian Kernel Based Fuzzy-Rough Set Approach for Feature Selection
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    Chapter 5 WSCOVER: A Tool for Automatic Composition and Verification of Web Services Using Heuristic-Guided Model Checking and Logic-Based Clustering
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    Chapter 6 An Improvement of Pattern-Based Information Extraction Using Intuitionistic Fuzzy Sets
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    Chapter 7 Shape Optimization in Product Design Using Interactive Genetic Algorithm Integrated with Multi-objective Optimization
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    Chapter 8 A Hierarchical Learning Approach for Finding Multiple Vehicle Number Plate Under Cluttered Background
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    Chapter 9 Multi-disciplinary Trends in Artificial Intelligence
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    Chapter 10 Causal Basis for Probabilistic Belief Change: Distance vs. Closeness
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    Chapter 11 A Scalable Spatial Anisotropic Interpolation Approach for Object Removal from Images Using Elastic Net Regularization
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    Chapter 12 Identification of Relevant and Redundant Automatic Metrics for MT Evaluation
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    Chapter 13 Bankruptcy Prediction Using Memetic Algorithm
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    Chapter 14 Crowd Simulation in 3D Virtual Environments
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    Chapter 15 Filter-Based Feature Selection Using Two Criterion Functions and Evolutionary Fuzzification
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    Chapter 16 Resolving the Manufacturing Cell Design Problem Using the Flower Pollination Algorithm
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    Chapter 17 A New Multiple Objective Cuckoo Search for University Course Timetabling Problem
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    Chapter 18 Application of Genetic Algorithm for Quantifying the Affect of Breakdown Maintenance on Machine Layout
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    Chapter 19 A Random Forest-Based Self-training Algorithm for Study Status Prediction at the Program Level: minSemi-RF
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    Chapter 20 Multi-disciplinary Trends in Artificial Intelligence
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    Chapter 21 A Comparison of Domain Experts and Crowdsourcing Regarding Concept Relevance Evaluation in Ontology Learning
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    Chapter 22 Evolutionary Analysis and Computing of the Financial Safety Net
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    Chapter 23 Learning to Navigate in a 3D Environment
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    Chapter 24 Analysis of Similarity/Dissimilarity of DNA Sequences Based on Pulse Coupled Neural Network
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    Chapter 25 Computing Sentiment Scores of Adjective Phrases for Vietnamese
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    Chapter 26 Sentiment Analysis Using Anaphoric Coreference Resolution and Ontology Inference
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    Chapter 27 A GA-SSO Based Intelligent Channel Assignment Approach for MR-MC Wireless Sensors Networks
Attention for Chapter 16: Resolving the Manufacturing Cell Design Problem Using the Flower Pollination Algorithm
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Chapter title
Resolving the Manufacturing Cell Design Problem Using the Flower Pollination Algorithm
Chapter number 16
Book title
Multi-disciplinary Trends in Artificial Intelligence
Published by
Springer, Cham, December 2016
DOI 10.1007/978-3-319-49397-8_16
Book ISBNs
978-3-31-949396-1, 978-3-31-949397-8
Authors

Ricardo Soto, Broderick Crawford, Rodrigo Olivares, Michele De Conti, Ronald Rubio, Boris Almonacid, Stefanie Niklander

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 14%
Student > Bachelor 1 14%
Student > Ph. D. Student 1 14%
Student > Master 1 14%
Researcher 1 14%
Other 1 14%
Unknown 1 14%
Readers by discipline Count As %
Computer Science 3 43%
Environmental Science 1 14%
Engineering 1 14%
Unknown 2 29%