Title :
Genetic algorithm for smart sensors calibration under disturbing condition
Author_Institution :
Inst. of Electron. Fundamentals, Warsaw Univ. of Technol., Poland
Abstract :
In this paper a concept of genetic algorithm (GA) usage for calculation of optimal plan for smart sensors calibration with presence of disturbing parameter is presented. A skeleton and genetic operators of applied GA are described. Comparison of experimental results for GA and Monte-Carlo algorithm (M-C) is provided
Keywords :
Monte Carlo methods; calibration; genetic algorithms; intelligent sensors; Monte-Carlo algorithm; cross over operator; disturbing condition; disturbing parameter; encoding; experimental results; genetic algorithm; genetic operators; optimal plan; smart sensors; smart sensors calibration; Automatic control; Calibration; Control systems; Data acquisition; Genetic algorithms; Intelligent sensors; Sensor phenomena and characterization; Sensor systems; Temperature sensors; World Wide Web;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 1997. IMTC/97. Proceedings. Sensing, Processing, Networking., IEEE
Conference_Location :
Ottawa, Ont.
Print_ISBN :
0-7803-3747-6
DOI :
10.1109/IMTC.1997.603945
