Three-dimensional gravity inversion based on the mass property model is very popular in recent years. The time and efficiency of inversion algorithms is relative to the magnitude of the target mesh. One approach is to...Three-dimensional gravity inversion based on the mass property model is very popular in recent years. The time and efficiency of inversion algorithms is relative to the magnitude of the target mesh. One approach is to search over the entire solution space for a more refined result. However, the inversion will be difficult with the increased parameters in the large search space and the number of computations increases exponentially. ｜n this paper, we propose a novel approach based on the frequency characteristics of the density distribution over the mesh. The purposes of our study are to reduce the parameters of three- dimensional gravity inversion and to lighten the image quality of the inversion result. The results show that the new method can expedite the inversion processing and get a better geological interpretation than tradition methods.展开更多
The available electricity generated by a wind power generation system depends on mean wind speed, standard deviation of wind speed and the location of installation. Since year-to-year variation on annual mean wind spe...The available electricity generated by a wind power generation system depends on mean wind speed, standard deviation of wind speed and the location of installation. Since year-to-year variation on annual mean wind speed is hard to predict, wind speed variations during a year can be well characterized in terms of a probability distribution function, as well Weibull distribution has been one of the most commonly used, accepted and recommended distribution to determine wind energy potential. In this study, the two Weibull parameters of the wind speed distribution function （the shape parameter k （dimensionless） and the scale parameter c （m/s））, were computed from the wind speed data for Algerian east coastal regions, recording over a 1 l-year period （1995-2005）. It was found that the numerical values of both Weibull parameters （k and c） vary over a wide range. The yearly values ofk range from 1.20 to 1.94, while those of c are in the range from 4.31 to 1.94. To minimize the uncertainties of statistical calculation, a spatial representation indicating distribution and occurrence frequency the direction from which the wind comes, appears a very primordial step. Over the whole valid data during the study period, the compass shows that there is no dominant direction marked. However, we can identify a preferred wind direction. The statistical results correspond to the analysis of the rose compass.展开更多
Price volatility in stock market brings potential profile positions to the traders. How to predict the direction of the stock market or stock price becomes the primary job for traders＇ trading model. We are looking f...Price volatility in stock market brings potential profile positions to the traders. How to predict the direction of the stock market or stock price becomes the primary job for traders＇ trading model. We are looking for the direction of the market in a given timeframe. High-frequency traders will consider the potential profile-out position in millisecond level. Long-term holder will look into month time scale. For most of average traders, the ideal timeframe will be on daily base. In this paper, for a non-news trading day, the author will introduce statistics method to predict the stock prices and bid-ask spread for day trading.展开更多
基金supported by the Key Project Fund of the Chinese Academy of Sciences under grant number (kzcx2-yw-203-01)the Major State Basic Research Development Program of China(973 Program,Grant No.2007CB41170404)
文摘Three-dimensional gravity inversion based on the mass property model is very popular in recent years. The time and efficiency of inversion algorithms is relative to the magnitude of the target mesh. One approach is to search over the entire solution space for a more refined result. However, the inversion will be difficult with the increased parameters in the large search space and the number of computations increases exponentially. ｜n this paper, we propose a novel approach based on the frequency characteristics of the density distribution over the mesh. The purposes of our study are to reduce the parameters of three- dimensional gravity inversion and to lighten the image quality of the inversion result. The results show that the new method can expedite the inversion processing and get a better geological interpretation than tradition methods.
文摘The available electricity generated by a wind power generation system depends on mean wind speed, standard deviation of wind speed and the location of installation. Since year-to-year variation on annual mean wind speed is hard to predict, wind speed variations during a year can be well characterized in terms of a probability distribution function, as well Weibull distribution has been one of the most commonly used, accepted and recommended distribution to determine wind energy potential. In this study, the two Weibull parameters of the wind speed distribution function （the shape parameter k （dimensionless） and the scale parameter c （m/s））, were computed from the wind speed data for Algerian east coastal regions, recording over a 1 l-year period （1995-2005）. It was found that the numerical values of both Weibull parameters （k and c） vary over a wide range. The yearly values ofk range from 1.20 to 1.94, while those of c are in the range from 4.31 to 1.94. To minimize the uncertainties of statistical calculation, a spatial representation indicating distribution and occurrence frequency the direction from which the wind comes, appears a very primordial step. Over the whole valid data during the study period, the compass shows that there is no dominant direction marked. However, we can identify a preferred wind direction. The statistical results correspond to the analysis of the rose compass.
文摘Price volatility in stock market brings potential profile positions to the traders. How to predict the direction of the stock market or stock price becomes the primary job for traders＇ trading model. We are looking for the direction of the market in a given timeframe. High-frequency traders will consider the potential profile-out position in millisecond level. Long-term holder will look into month time scale. For most of average traders, the ideal timeframe will be on daily base. In this paper, for a non-news trading day, the author will introduce statistics method to predict the stock prices and bid-ask spread for day trading.
