首页|Findings from Changzhou University in the Area of Support Vector Machines Report ed (A Combination Model for Displacement Prediction of High Arch Dams Stacking F ive Kinds of Temperature Factors)
Findings from Changzhou University in the Area of Support Vector Machines Report ed (A Combination Model for Displacement Prediction of High Arch Dams Stacking F ive Kinds of Temperature Factors)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Support Vector Machine s is the subject of a report. Accordingto news reporting originating in Jiangsu , People’s Republic of China, by NewsRx journalists, researchstated, “The stati cally indeterminate characteristics of arch dams highlight the temperature defor mationeffect, making accurate modelling of this effect a key issue in improving the performance of displacementmonitoring models. In this paper, causal interp retation ability and prediction accuracy of five kinds oftemperature deformatio n modelling factors, including seasonal harmonic function, segmented average previous air temperature, air temperature hysteresis correction factor, principal c omponents and shape featureclustering-based principal components of measured da m temperatures, are compared.”
JiangsuPeople’s Republic of ChinaAsi aEmerging TechnologiesMachine LearningSupport Vector MachinesVector Mach inesChangzhou University
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