Abnormal patterns recognition in bivariate autocorrelated process using optimized random forest and multi-feature extraction.
Sign Up to like & getrecommendations! Published in 2020 at "ISA transactions"
DOI: 10.1016/j.isatra.2020.09.008
Abstract: Traditional multivariate control charts are unable to determine the specific abnormal variables as detecting process abnormality. To solve this problem, a new model based on optimized random forest (RF) and multi-feature extraction has been proposed.… read more here.
Keywords: optimized random; process; model; multi feature ... See more keywords
Optimized random phase encryption.
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DOI: 10.1364/ol.43.003558
Abstract: We propose for the first time, to the best of our knowledge, the use of optimized random phases (ORAPs) in a double random phase encryption scheme (DRPE). In DRPE schemes the convolution between two random… read more here.
Keywords: phase encryption; phase; random phase; optimized random ... See more keywords
Optimized Random Forest for Solar Radiation Prediction Using Sunshine Hours
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DOI: 10.3390/mi13091406
Abstract: Knowing exactly how much solar radiation reaches a particular area is helpful when planning solar energy installations. In recent years the use of renewable energies, especially those related to photovoltaic systems, has had an impressive… read more here.
Keywords: solar radiation; forest solar; optimized random; prediction ... See more keywords