Statistical relational learning constructs statistical models from relational databases, combining relational learning and statistical learning. Its strong ability and special property make statistical relational lear...Statistical relational learning constructs statistical models from relational databases, combining relational learning and statistical learning. Its strong ability and special property make statistical relational learning become one of the important areas in machine learning research.In this paper,the general concepts and characters of statistical relational learning are presented firstly.Then some major branches of this newly emerging field are discussed,including logic and rule-based approaches,frame and object-oriented approaches,functional programming-based approaches.After that several methods of applying rough set in statistical relational learning are described,such as gRS-ILP and VPRSILP. Finally some applications of statistical relational leaning are briefly introduced and some future directions of statistical relational learning and the application of rough set in this area are pointed out.展开更多
Shear velocity is an important index for evaluating soil dynamic properties of the site. In this paper, the statistical relation of shear velocity with soil properties is set up by statistical analysis of shear veloci...Shear velocity is an important index for evaluating soil dynamic properties of the site. In this paper, the statistical relation of shear velocity with soil properties is set up by statistical analysis of shear velocities and relevant soil properties measured in Tianjin and Shanghai. The obtained formula has some referential value for the evaluation and classification of the site in offshore areas of China.展开更多
Using the divergence term appearing in the Lagrangian of the teleparallel equivalent of general relativity （TEGR）, we calculate the thermodynamic quantities of four tetrads＇ spacetime reproducing Lense-Thirring （L...Using the divergence term appearing in the Lagrangian of the teleparallel equivalent of general relativity （TEGR）, we calculate the thermodynamic quantities of four tetrads＇ spacetime reproducing Lense-Thirring （LT） metric. We also investigate the first law of thermodynamics and the quantum statistical relation.展开更多
The Zhoubi Suanjing, one of the most important ancient Chinese books on mathematical astronomy, was compiled about 100 BC in the Western Han dynasty （BC 206 - AD 23）. We study the gnomon shadow lengths for the 24 so...The Zhoubi Suanjing, one of the most important ancient Chinese books on mathematical astronomy, was compiled about 100 BC in the Western Han dynasty （BC 206 - AD 23）. We study the gnomon shadow lengths for the 24 solar terms as recorded in the book. Special attention is paid to the so-called law of ‘cun qian li’, which says the shadow length of a gnomon of 8 chi （about 1.96 m） high will increase （or decrease） 1 cun （1/10chi） for every 10001i （roughly 400kin） the gnomon moves northward （or south- ward）. From these data, one can derive the time and location of the observations. The resuits, however, do not fit historical facts. We suggest that compilers of the Zhoubi Suanjing must have modified the original data according to the law of ‘cun qian li’. Through reversing the situation, we recovered the original data, our analysis of which reveals the best possible observation time as 564 BC and the location of observation as 35.78° N latitude. We conclude that this must be the earliest records of solar meridian observations in China. In the meantime, we give the errors of solar altitudes for the 24 solar terms. The average deviation is 5.22°, and the mean absolute deviation is 5.52°, signifying the accuracy of astronomical calculations from that time.展开更多
A good model can extract useful information about the target＇s state from observations effectively. There are many models used to tracking a, maneuvering target such as constant-velocity （CV） model, Singer accelera...A good model can extract useful information about the target＇s state from observations effectively. There are many models used to tracking a, maneuvering target such as constant-velocity （CV） model, Singer acceleration model （zero-mean first-order Markov model） and current model （mean-adaptive acceleration model）, etc. While due to the complexity of maneuvering target, to seek the target model which can get better performance is still a subject worthy of study. Based on statistics relation between the autocormlation function and the covariance of Markov random processing, this paper develops a model which can adaptively adjust system parameters on line. Simulations show the good estimation performance get by the model developed here, and comparing CV, Singer and current models, the model can adaptively get the model parameter while tracking the trajectory and needn＇t doing several tests to obtain a priori parameter.展开更多
文摘Statistical relational learning constructs statistical models from relational databases, combining relational learning and statistical learning. Its strong ability and special property make statistical relational learning become one of the important areas in machine learning research.In this paper,the general concepts and characters of statistical relational learning are presented firstly.Then some major branches of this newly emerging field are discussed,including logic and rule-based approaches,frame and object-oriented approaches,functional programming-based approaches.After that several methods of applying rough set in statistical relational learning are described,such as gRS-ILP and VPRSILP. Finally some applications of statistical relational leaning are briefly introduced and some future directions of statistical relational learning and the application of rough set in this area are pointed out.
文摘Shear velocity is an important index for evaluating soil dynamic properties of the site. In this paper, the statistical relation of shear velocity with soil properties is set up by statistical analysis of shear velocities and relevant soil properties measured in Tianjin and Shanghai. The obtained formula has some referential value for the evaluation and classification of the site in offshore areas of China.
文摘Using the divergence term appearing in the Lagrangian of the teleparallel equivalent of general relativity （TEGR）, we calculate the thermodynamic quantities of four tetrads＇ spacetime reproducing Lense-Thirring （LT） metric. We also investigate the first law of thermodynamics and the quantum statistical relation.
基金supported by the National Natural Science Foundation of China(Grant Nos.10973022 and 10873039)
文摘The Zhoubi Suanjing, one of the most important ancient Chinese books on mathematical astronomy, was compiled about 100 BC in the Western Han dynasty （BC 206 - AD 23）. We study the gnomon shadow lengths for the 24 solar terms as recorded in the book. Special attention is paid to the so-called law of ‘cun qian li’, which says the shadow length of a gnomon of 8 chi （about 1.96 m） high will increase （or decrease） 1 cun （1/10chi） for every 10001i （roughly 400kin） the gnomon moves northward （or south- ward）. From these data, one can derive the time and location of the observations. The resuits, however, do not fit historical facts. We suggest that compilers of the Zhoubi Suanjing must have modified the original data according to the law of ‘cun qian li’. Through reversing the situation, we recovered the original data, our analysis of which reveals the best possible observation time as 564 BC and the location of observation as 35.78° N latitude. We conclude that this must be the earliest records of solar meridian observations in China. In the meantime, we give the errors of solar altitudes for the 24 solar terms. The average deviation is 5.22°, and the mean absolute deviation is 5.52°, signifying the accuracy of astronomical calculations from that time.
基金supported by the National Natural Science Foundation of China (61273002, 60971119)
文摘A good model can extract useful information about the target＇s state from observations effectively. There are many models used to tracking a, maneuvering target such as constant-velocity （CV） model, Singer acceleration model （zero-mean first-order Markov model） and current model （mean-adaptive acceleration model）, etc. While due to the complexity of maneuvering target, to seek the target model which can get better performance is still a subject worthy of study. Based on statistics relation between the autocormlation function and the covariance of Markov random processing, this paper develops a model which can adaptively adjust system parameters on line. Simulations show the good estimation performance get by the model developed here, and comparing CV, Singer and current models, the model can adaptively get the model parameter while tracking the trajectory and needn＇t doing several tests to obtain a priori parameter.
