板翅式换热器综合性能优化的设计方法

应用给定换热器结构材料而使换热量最大的两侧换热表面的最佳匹配准则和使可用能损失率最小的最佳运行参数准则。利用两个准则间的关系 ,采用迭代的方式完成换热器的优化设计 ,使换热器的设计达到材料省、换热效果好及运行费用低的目的 ,且能在设计阶段实现。     

SAMPLING REMOTELY SENSED IMAGERY FOR STORAGE,RETRIEVAL, AND RECONSTRUCTION*

A major difficulty in remote sensing is handling the many data from sensors aboard aircraft and satellites. In this paper we identify an optimal procedure for sampling remotely sensed data before their storage or on their retrieval. The procedure depends on spatial correlation in the scene and uses kriging to estimate values that have been lost. An example in which data from an airborne multispectral scanner could be diminished to only about one tenth without serious loss of precision illustrates the method.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.     

模糊划分矩阵在岩土参数概率分布中的应用

讨论如何在小样本条件下用已有的过程经验与试验资料确定岩土参数概率分布,用模糊划分矩阵与BAYES方法相结合,给出由小样本试验数据确定岩土参数的概率分布。     

Evolution of the luminosity function and colours of galaxies in a Λ cold dark matter universe

The luminosity function of galaxies is derived from a cosmological hydrodynamic simulation of a Λ cold dark matter universe with the aid of a stellar population synthesis model. At     , the resulting B -band luminosity function has a flat faint-end slope of     with the characteristic luminosity and the normalization in fair agreement with observations, while the dark matter halo mass function is steep with a slope of     . The colour distribution of galaxies also agrees well with local observations. We also discuss the evolution of the luminosity function, and the colour distribution of galaxies from     to 5. A large evolution of the characteristic mass in the stellar mass function as a result of number evolution is compensated by luminosity evolution; the characteristic luminosity increases only by 0.8 mag from     to 2, and then declines towards higher redshift, while the B -band luminosity density continues to increase from     to 5 (but only slowly at     .     

Constraints on a quintessence model from gravitational lensing statistics

Constraints on an exact quintessence scalar-field model with an exponential potential are derived from gravitational lens statistics. An exponential potential can account for data from both optical quasar surveys and radio-selected sources. Based on the Cosmic Lens All-Sky Survey (CLASS) sample, lensing statistics provides, for the pressureless matter density parameter, an estimate of  Ω_M0= 0.31^+0.12_−0.14  .