首页|Hebei University Reports Findings in Support Vector Machines (Accurate determina tion of alcohol-based diesels using optimal chemical factors)
Hebei University Reports Findings in Support Vector Machines (Accurate determina tion of alcohol-based diesels using optimal chemical factors)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning - Sup port Vector Machines is the subject of a report. According to news originating f rom Baoding, People’s Republic of China, by NewsRx correspondents, research stat ed, “Sustainable environmental policies and energy crises have led to a trend of blending different alcohols into diesel to partly replace the decreasing fossil fuels. To improve the rapidity and accuracy of determining alcohols exist in me thanol and ethanol diesel, optimal chemical factors (OCF) feature selection sche mes were presented based on different near infrared (NIR) characteristic absorpt ion bands generated by different chemical structure information utilizing suppor t vector machine (SVM).” Our news journalists obtained a quote from the research from Hebei University, “ Through comparative analysis with SVM based on entire spectra, Monte Carlo uninf ormative variable elimination (MC-UVE) spectra and competitive adaptive reweight ed sampling (CARS) spectra, the proposed OCF-SVM not only achieved 100 % accuracy, precision, recall and F-score in classification, but also exhibited th e best performance in prediction analysis with the smallest sum of squares due t o error (SSE), root mean squared error (RMSE), mean absolute percentage error (M APE) and the highest R-square. The overall outcomes indicate that the OCF method based on molecular chemical structures can select more pertinent and interpreta ble spectral features, thereby making the classification and prediction of alcoh ol-based diesels more exact and credible.”
BaodingPeople’s Republic of ChinaAsi aMachine LearningSupport Vector Machines
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