Central Library

Normal view MARC view ISBD view

Soft Computing Techniques in Engineering Applications [electronic resource] / edited by Srikanta Patnaik, Baojiang Zhong.

Contributor(s): Patnaik, Srikanta [editor.] | Zhong, Baojiang [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 543Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: VI, 206 p. 134 illus., 57 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319046938.Subject(s): Engineering | Image processing | Computational intelligence | Cognitive psychology | Engineering | Computational Intelligence | Image Processing and Computer Vision | Cognitive PsychologyAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
From the Contents: Machine Vision Solutions in Automotive Industry Kinect Quality Enhancement for Triangular Mesh Reconstruction with a Medical Image Application -- Matlab GUI Package for Comparing Data Clustering Algorithms -- Multi Objective Line Symmetry Based Evolutionary Clustering Approach -- An Efficient Method for Contrast Enhancement of Digital Mammographic Images -- Simulation of Obstacle Detection and Speed Control for Autonomous Robotic Vehicle -- A Review of Global Path Planning Algorithms for Planar Navigation of Autonomous Underwater Robots.
In: Springer eBooksSummary: The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well as acting on the environment. Ideally speaking, soft computing is not a subject of homogeneous concepts and techniques; rather, it is an amalgamation of distinct methods that confirms to its guiding principle. At present, the main aim of soft computing is to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solutions cost. The principal constituents of soft computing techniques are probabilistic reasoning, fuzzy logic, neuro-computing, genetic algorithms, belief networks, chaotic systems, as well as learning theory. This book covers contributions from various authors to demonstrate the use of soft computing techniques in various applications of engineering.  .
    average rating: 0.0 (0 votes)
No physical items for this record

From the Contents: Machine Vision Solutions in Automotive Industry Kinect Quality Enhancement for Triangular Mesh Reconstruction with a Medical Image Application -- Matlab GUI Package for Comparing Data Clustering Algorithms -- Multi Objective Line Symmetry Based Evolutionary Clustering Approach -- An Efficient Method for Contrast Enhancement of Digital Mammographic Images -- Simulation of Obstacle Detection and Speed Control for Autonomous Robotic Vehicle -- A Review of Global Path Planning Algorithms for Planar Navigation of Autonomous Underwater Robots.

The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well as acting on the environment. Ideally speaking, soft computing is not a subject of homogeneous concepts and techniques; rather, it is an amalgamation of distinct methods that confirms to its guiding principle. At present, the main aim of soft computing is to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness and low solutions cost. The principal constituents of soft computing techniques are probabilistic reasoning, fuzzy logic, neuro-computing, genetic algorithms, belief networks, chaotic systems, as well as learning theory. This book covers contributions from various authors to demonstrate the use of soft computing techniques in various applications of engineering.  .

There are no comments for this item.

Log in to your account to post a comment.