Title :
Multi-Sensor Fusion Using Knowledge-based Mind Evolutionary Algorithm
Author :
Niu, Yuguang ; Yan, Gaowei ; Xie, Gang ; Chen, Zehua ; Xie, Keming
Author_Institution :
Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan
Abstract :
The knowledge-acquisition mechanism, which is generated from rough set and granular computing, is integrated into mind evolutionary algorithm. The evolution direction is guided by the knowledge discovered in the evolution process. As a result, the mind evolutionary algorithm under the guide of knowledge is realized, which indicates the knowledge abstraction and usage functionalities during human beings´ mind activities. The result of weight-value optimization of the neural network in multi-sensor information fusion system shows that this method is able to effectively improve the study efficiency and study precision for neural networks.
Keywords :
data mining; evolutionary computation; knowledge based systems; neural nets; optimisation; rough set theory; sensor fusion; granular computing; knowledge abstraction; knowledge discovery; knowledge-acquisition mechanism; knowledge-based mind evolutionary algorithm; multisensor fusion; multisensor information fusion system; neural network; rough set; usage functionality; weight-value optimization; Data analysis; Educational institutions; Evolutionary computation; Humans; Information analysis; Information technology; Knowledge engineering; Knowledge representation; Neural networks; Optimization methods; Granular Computing; Knowledge based Mind Evolutionary Algorithms; Multi-Sensor Fusion; Rough Set Theory;
Conference_Titel :
Convergence and Hybrid Information Technology, 2008. ICCIT '08. Third International Conference on
Conference_Location :
Busan
Print_ISBN :
978-0-7695-3407-7
DOI :
10.1109/ICCIT.2008.245
