Surveying Robot Routing Algorithms with Data Mining Approach


Authors

Rouhollah Maghsoudi - Department of Computer, Nour Branch, Islamic Azad University, Nour, Iran Somayye Hoseini - Payame Noor University of Shahrerey ,Tehran, Iran Yaghub Heidari - Department of Electrical, Nour Branch, Islamic Azad University, Nour, Iran


Abstract

Data mining knowledge in response to technological advances in various Rmynh, foot arena is built there. Data Mining face a different situation that the data size is large and we want to build a small model and not too complicated and yet the data as well as describe. Necessity to use data analysis to reduce the amount and the huge volume of information. One important and practical issues in the world of machine intelligence and is robotics robots routing. Robot router has obstacle detection and how to deal with the decision with obstacle. For routing, algorithms including probabilistic methods (filtering particulate), evolutionary algorithms such as genetic, ants social and optimization particle mass, neural methods - Fuzzy, inequality of matrix method based on gradient methods combined sensor information, etc. There are data mining methods in the years 2010-2008 as a technique for routing and a complete robot has been used and still is in progress. Overview of the methods in the paper mentioned in various articles since 2000 has so far. Although many data mining methods include, but mentioned in this article with specific literature data mining will deal with the routing problem.


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ISRP Style

Rouhollah Maghsoudi, Somayye Hoseini, Yaghub Heidari, Surveying Robot Routing Algorithms with Data Mining Approach, Journal of Mathematics and Computer Science, 2 (2011), no. 2, 284--294

AMA Style

Maghsoudi Rouhollah, Hoseini Somayye, Heidari Yaghub, Surveying Robot Routing Algorithms with Data Mining Approach. J Math Comput SCI-JM. (2011); 2(2):284--294

Chicago/Turabian Style

Maghsoudi, Rouhollah, Hoseini, Somayye, Heidari, Yaghub. "Surveying Robot Routing Algorithms with Data Mining Approach." Journal of Mathematics and Computer Science, 2, no. 2 (2011): 284--294


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