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Solvent Manufacturing Process Monitoring using Artificial Neural Networks
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  • Solvent Manufacturing Process Monitoring using Artificial Neural Networks
  • Solvent Manufacturing Process Monitoring using Artificial Neural Networks
저자명
Lim. Chang-Gyoon
간행물명
퍼지 및 지능시스템학회 논문지
권/호정보
2005년|15권 2호|pp.264-269 (6 pages)
발행정보
한국지능시스템학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

Advances in sensors, actuators, and computers and developments In information systems offer unprecedented opportunities to implement highly ambitious automation, control and decision strategies. There are also new challenges and demands for control and automation in modern industrial practices. There is a growing need for an active participation from the information systems in industrial, manufacturing and process industry environments because currently there are many control problems. This paper provides pattern recognition to the monitoring system for solvent manufacturing process and shows performance in real-time response with multiple input signals. Data is teamed by a multilayer feedforward network trained by error-backpropagation. The two kinds of test results show that the trained network has the ability to show the current system status with different input data sets.