首页|Study Findings on Machine Learning Described by Researchers at Beijing Universit y of Posts and Telecommunications (Machine learning assisted high-precision temp erature sensor in a multimode microcavity)
Study Findings on Machine Learning Described by Researchers at Beijing Universit y of Posts and Telecommunications (Machine learning assisted high-precision temp erature sensor in a multimode microcavity)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on artificial intell igence are discussed in a new report. According to news reporting originating fr om Beijing, People’s Republic of China, by NewsRx correspondents, research state d, “Whispering gallery mode (WGM) microcavities are excellent platforms for ultr a-sensitive sensing due to high-quality factor and small mode volume.” The news editors obtained a quote from the research from Beijing University of P osts and Telecommunications: “However, the conventional sensing method by tracki ng single-mode changes is difficult to fully utilize the sensing information, wh ich limits the measurement precision and dynamical range. Here, we demonstrate a high-precision temperature sensor based on the multimode sensing method in a pa ckaged microbubble resonator (PMBR). Remarkably, a low-cost broadband spectrum s ource is used as probe light to provide more sensing modes for high-precision me asurement. Empowered by a machine learning method, the multimode spectral inform ation are fully utilized, and the true temperature is precisely readout with mea n-squared error (MSE) of 0.0138. The detection limit is lower three times than s ingle-mode sensing method, capable of reaching 0.117 °C. In addition, the correl ation coefficient (R2) between predictions and truth is as high as 0.9996 within the measurement range of 25-45 °C.”
Beijing University of Posts and Telecomm unicationsBeijingPeople’s Republic of ChinaAsiaCyborgsEmerging Technol ogiesMachine Learning
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