Research from Center for Medical Science Has Provided New Study Findings on Mach ine Learning (ELMOPP: an application of graph theory and machine learning to tra ffic light coordination)
Research from Center for Medical Science Has Provided New Study Findings on Mach ine Learning (ELMOPP: an application of graph theory and machine learning to tra ffic light coordination)
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on artificial intelligence have been published. According to news reporting out of Virginia, United States, by NewsRx editors, research stated, “Purpose - This paper presents the Edge Loa d Management and Optimization through Pseudoflow Prediction (ELMOPP) algorithm, which aims to solve problems detailed in previous algorithms; through machine le arning with nested long short-term memory (NLSTM) modules and graph theory, the algorithm attempts to predict the near future using past data and traffic patter ns to inform its real-time decisions and better mitigate traffic by predicting f uture traffic flow based on past flow and using those predictions to both maximi ze present traffic flow and decrease future traffic congestion.”
Key words
Center for Medical Science/Virginia/Un ited States/North and Central America/Algorithms/Cyborgs/Emerging Technologi es/Machine Learning/Mathematical Theories
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