首页|Data on Machine Learning Detailed by Researchers at Kunming University (Multiobj ective Optimization of Diesel Particulate Filter Regeneration Conditions Based O n Machine Learning Combined With Intelligent Algorithms)
Data on Machine Learning Detailed by Researchers at Kunming University (Multiobj ective Optimization of Diesel Particulate Filter Regeneration Conditions Based O n Machine Learning Combined With Intelligent Algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – New research on Machine Learning is the subject o f a report. According to news reporting originatingin Kunming, People’s Republi c of China, by NewsRx journalists, research stated, “To reduce dieselemissions and fuel consumption and improve DPF regeneration performance, a multiobjective optimizationmethod for DPF regeneration conditions, combined with nondominated sorting genetic algorithms (NSGAIII)and a back propagation neural network (BPN N) prediction model, is proposed. In NSGA-III, DPFregeneration temperature (T4 and T5), O 2 , NO x , smoke, and brake-specific fuel consumption (BSFC)are opti mized by adjusting the engine injection control parameters.”
KunmingPeople’s Republic of ChinaAsi aAlgorithmsCyborgsEmerging TechnologiesMachine LearningKunming Univers ity
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