By a News Reporter-Staff News Editor at Clinical Trials Week -- New research on Clinical Research is the subject of a report. According to news reporting out of Pulau Pinang, Malaysia, by NewsRx editors, research stated, "Nowadays, infrared thermographic inspection has increasingly been utilized for fault diagnosis tools of electrical equipment, because it maintains non-interrupting operation of power system and ensures early diagnosis of faults. The article discusses the performance comparison of multilayer perceptron (MLP) networks using various backpropagation algorithms for thermal imaging-based condition monitoring of electrical hotspots."
Our news journalists obtained a quote from the research from the University of Science Malaysia, "The training algorithms are Levenberg-Marquardt, Broyden-Fletcher-Goldfarb-Shanno quasi-Newton, resilient backpropagation, gradient descent with momentum and adaptive learning rate and standard gradient descent training algorithms. The performance of the training algorithms are evaluated in terms of percentage of accuracy, sensitivity, specificity, false-positive and false-negative results. In the beginning, thermal images of electrical equipment are captured using infrared camera. Six statistical intensity features, namely mean, maximum, minimum, median, standard deviation and variance extracted from each hotspot of equipment thermal image are used as the inputs of multilayered perceptron networks to classify the thermal conditions of hotspots into two classes, namely normal and defective."
According to the news editors, the research concluded: "The comparison of MLP networks using training algorithms proves that the MLP network trained with resilient backpropagation algorithm gives the best performance in thermal condition recognition."
For more information on this research see: A Comparative Study of MLP Networks Using Backpropagation Algorithms in Electrical Equipment Thermography. Arabian Journal for Science and Engineering, 2014;39(5):3873-3885. Arabian Journal for Science and Engineering can be contacted at: Springer Heidelberg, Tiergartenstrasse 17, D-69121 Heidelberg, Germany. (Springer - www.springer.com; Arabian Journal for Science and Engineering - www.springerlink.com/content/1319-8025/)
Our news journalists report that additional information may be obtained by contacting A.S.N. Huda, University of Sains Malaysia, Sch Elect & Elect Engn, Nibong Tebal 14300, Pulau Pinang, Malaysia (see also Clinical Research).
Keywords for this news article include: Asia, Malaysia, Algorithms, Perceptron, Pulau Pinang, Machine Learning, Clinical Research, Emerging Technologies, Clinical Trials and Studies
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