In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is ...In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation： to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.展开更多
Offshore wind farm is a key item in green energy and sustainable development. The Taiwan strait owns the world-class wind farm with average wind speed of 12 m/s and a potential for 3000 hours/year of power generation....Offshore wind farm is a key item in green energy and sustainable development. The Taiwan strait owns the world-class wind farm with average wind speed of 12 m/s and a potential for 3000 hours/year of power generation. Compared to wind turbines on land, the offshore wind turbine provide more stable power and less obstacles as well as less power loss. The potential and advantages of offshore wind farm development in the Taiwan strait has become the aims of the Taiwan government policy from now to 2025. This research will collect the historical climate data (wind and wave) of the Taiwan offshore wind farm in the Chan-hwa county. Combined the productivity loss respected to the installation of wind turbine due to different wind speed effect, as well as the productivity loss respected to the construction of pile foundation due to different wave height effect, this study will build up a total project duration forecast system based on the historical climate data of the offshore wind farm. Even the literature views from the experienced projects in North Europe including UK, Netherland and Spain, the climate uncertainty still plays a significant factor of the total construction duration for offshore wind farm. The results of this research can provide a more scientific and reliable duration forecast for future offshore wind farms construction in Taiwan.展开更多
This study reports verification results of hindcast data of four systems in the subseasonal-to-seasonal(S2S)prediction project for major stratospheric sudden warmings(MSSWs)in northern winter from 1998/99 to 2012/13.T...This study reports verification results of hindcast data of four systems in the subseasonal-to-seasonal(S2S)prediction project for major stratospheric sudden warmings(MSSWs)in northern winter from 1998/99 to 2012/13.This report deals with average features across all MSSWs,and possible differences between two MSSW types(vortex displacement and split types).Results for the average features show that stratospheric forecast verifications,when further averaged among the four systems,are judged to be successful for lead times around 10 d or shorter.All systems are skillful for lead times around 5 d,whereas the results vary among the systems for longer lead times.A comparison between the MSSW types overall suggests larger forecast errors or lower skill for MSSWs of the vortex split type,although the differences do not have strong statistical significance for almost all cases.This limitation is likely to at least partly reflect the small sample size of the MSSWs available.展开更多
文摘In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression （PPR） is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation： to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast.
文摘Offshore wind farm is a key item in green energy and sustainable development. The Taiwan strait owns the world-class wind farm with average wind speed of 12 m/s and a potential for 3000 hours/year of power generation. Compared to wind turbines on land, the offshore wind turbine provide more stable power and less obstacles as well as less power loss. The potential and advantages of offshore wind farm development in the Taiwan strait has become the aims of the Taiwan government policy from now to 2025. This research will collect the historical climate data (wind and wave) of the Taiwan offshore wind farm in the Chan-hwa county. Combined the productivity loss respected to the installation of wind turbine due to different wind speed effect, as well as the productivity loss respected to the construction of pile foundation due to different wave height effect, this study will build up a total project duration forecast system based on the historical climate data of the offshore wind farm. Even the literature views from the experienced projects in North Europe including UK, Netherland and Spain, the climate uncertainty still plays a significant factor of the total construction duration for offshore wind farm. The results of this research can provide a more scientific and reliable duration forecast for future offshore wind farms construction in Taiwan.
基金supported by JSPS KAKENHI (Grant No. JP17H01159)
文摘This study reports verification results of hindcast data of four systems in the subseasonal-to-seasonal(S2S)prediction project for major stratospheric sudden warmings(MSSWs)in northern winter from 1998/99 to 2012/13.This report deals with average features across all MSSWs,and possible differences between two MSSW types(vortex displacement and split types).Results for the average features show that stratospheric forecast verifications,when further averaged among the four systems,are judged to be successful for lead times around 10 d or shorter.All systems are skillful for lead times around 5 d,whereas the results vary among the systems for longer lead times.A comparison between the MSSW types overall suggests larger forecast errors or lower skill for MSSWs of the vortex split type,although the differences do not have strong statistical significance for almost all cases.This limitation is likely to at least partly reflect the small sample size of the MSSWs available.
