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Soft Computing and its Application in Engineering
Submission Deadline: Aug. 30, 2015
Lead Guest Editor
Mehdi Neshat
Department of Computer Engineering, Islamic Azad University, Shirvan, Iran
Guest Editor
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Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=135). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
Published Papers
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Introduction
In the recent decade, Soft Computing methods have been appeared as a significant tool regarding obtaining intelligent computational patterns where key components are learning from experience in the attendance of uncertainties computing strategies of the learning agent itself. Fuzzy logic, neural network and evolutionary computing are the three major subjects of soft computing.

This Special issue aims to advance new developments and research directions to address with the theory of soft computing and its application in engineering design and manufacturing. The methodologies have dealt with a large diversity of factual life issues. In addition, application of soft computing has supplied the chance to merge human like 'vagueness' and real life 'uncertainty'. Meanwhile, nowadays, tendencies incline to involve evolutionary and swarm intelligence based algorithms and bio-inspired computation. Topics of interest include (but are not limited to):

1. Neural Network (NN)
2. Support Vector Machines (SVM)
3. Fuzzy logic (FL)
4. Evolutionary computation (EC), including:
4.1. Evolutionary algorithms
4.1.1. Genetic algorithms
4.1.2. Differential evolution
4.2.Metaheuristic and Swarm Intelligence
4.2.1. Ant colony optimization
4.2.2. Particle swarm optimization
4.2.3. Firefly algorithm
4.2.4. Cuckoo search
5. Ideas about probability including:
5.1. Bayesian network
6. Chaos theory
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