Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingoriginating from Hunan, People’s Rep ublic of China, by NewsRx correspondents, research stated, “Consideringthe hydr ation reaction of cement, a finite element model(FEM) of the coupling of tempera tureand humidity field and chemical field in the early age of the double-block ballastless track structure wasestablished, and a field monitoring test on the early age of track slab was carried out with the newlyconstructed FuzhouXiamen high-speed railway line as a case to verify the correctness of the FEM. Basedon the official meteorological data from China Meteorological Administration (CMA) and the FEM, thedataset of vertical temperature and humidity gradients in the early age of the track slab was constructed,and five machine learning training models, namely, machine learning (MLR), multivariate polynomial regression(MPR) , support vector regression (SVR), random forest (RF), and gradient boosted regr ession(GBR), were adopted to train the temperature gradient model and humidity gradient model for the earlyage of the track slab.”
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