Establishment and analysis of global gridded Tm-Ts relationship model

In ground-based GPS meteorology, Tm is a key parameter to calculate the conversion factor that can convert the zenith wet delay（ZWD） to precipitable water vapor（PWV）. It is generally acknowledged that Tm is in an approximate linear relationship with surface temperature Ts, and the relationship presents regional variation. This paper employed sliding average method to calculate correlation coefficients and linear regression coefficients between Tm and Ts at every 2°× 2.5° grid point using Ts data from European Centre for Medium-Range Weather Forecasts（ECMWF） and Tm data from ＂GGOS Atmosphere＂, yielding the grid and bilinear interpolation-based Tm Grid model. Tested by Tm and Ts grid data, Constellation Observation System of Meteorology, Ionosphere, and Climate（COSMIC） data and radiosonde data, the Tm Grid model shows a higher accuracy relative to the Bevis Tm-Ts relationship which is widely used nowadays. The Tm Grid model will be of certain practical value in high-precision PWV calculation.

M5 Model Tree to Predict Temporal Evolution of Clear-Water Abutment Scour

Scour is a natural phenomenon that is created by the rivers streams or the flood which brings about transferring or eroding of bed materials. To have accurate and safe erosion control structures design, maximum scour depth in downstream of the structures gains specific significance. In the current study, M5 model tree as remedy data mining approaches is suggested to estimate the scour depth around the abutments. To do this, Kayaturk laboratory data (2005), with different hydraulic conditions, are used. Then, the results of M5 model were also compared with genetic programming (GP) and pervious empirical results to investigate the applicability, ability, and accuracy of these procedures. To examine the accuracy of the results yielded from the M5 and GP procedures, two performance indicators (determination coefficient (R2) and root mean square error (RMSE)) were used. The comparison test of results clearly shows that the implementation of M5 technique sounds satisfactory regarding the performance indicators (R2 = 0.944 and RMSE = 0.126) with less deviation from the numerical values. In addition, M5 tree model, by presenting relationships based on liner regression, has good capability to estimate the depth of scour abutment for engineers in practical terms.

Evaluation of the geopotential value W_0^(LVD) of China

Estimation of the zero-height geopotential value W_0^（LVD） for the CVD（China Vertical Datum） plays a fundamental role in the connection of traditional height reference systems into a global height system.Estimation the W_0^（LVD） of China is based on the computation of the mean geopotential offset between the value W_0= 62636856.0 m^2 s^（-2）, selected as reference in this study, and the unknown geopotential value W_0^（LVD）. This estimation is based on the combination of ellipsoidal heights, levelled heights（referring to the CVD）, and some physical parameters, such as geopotential values, gravity values, and geoid undulations.The geoid undulations derived from the GGM（Global Geopotential Models）. This combination is performed through three approaches： The first one is based on the theory of Molodensky, and the second one compares levelled heights and geopotential values derived from the GGMs, while the third one analyses the differences between GPS/Levelling and GGMs geoid undulations. The approaches are evaluated at 65 benchmarks（BMs） covered around Qingdao where the tide gauge is used to observe the local mean sea level of China. The results from three approaches are very similar. Furthermore, the W_0^（LVD）determined for the China local vertical datum was 62636852.9462 m^2 s^（-2）, indicates a bias of about3.0538 m^2/s^（-2） compared to the conventional value of 62636856.0 m^2 s^（-2）.

Presentation of regression analysis,GP and GMDH models to predict the pedestrian density in various urban facilities

In this study,the relationship between space mean speed(SMS),flow rate and density of pedestrians was investigated in different pedestrian facilities,including 1 walkway,2 sidewalks,2 signalized crosswalks and 2 mid-block crosswalks.First,statistical analysis was performed to investigate the normality of data and correlation of variables.Regression analysis was then applied to determine the relationship between SMS,flow rate,and density of pedestrians.Finally,two prediction models of density were obtained using genetic programming(GP)and group method of data handling(GMDH)models,and k-fold and holdout cross-validation methods were used to evaluate the models.By the use of regression analysis,the mathematical relationships between variables in all facilities were calculated and plotted,and the best relationships were observed in flow rate-density diagrams.Results also indicated that GP had a higher R2 than GMDH in the prediction of pedestrian density in terms of flow rate and SMS,suggesting that GP was better able to model SMS and pedestrian density.Moreover,the application of k-fold cross-validation method in the models led to better performances compared to the holdout cross-validation method,which shows that the prediction models using k-fold were more reliable.Finally,density relationships in all facilities were obtained in terms of SMS and flow rate.