四川旱涝震灾害的人工神经网络外推预测

选取旱、涝、震灾害之间的一步转移概率作为Ｂ－Ｐ人工神经网络训练样本的输入信息，建立了四川旱、涝、震的人工神经网络灾型预测模型。Ｂ－Ｐ网络模型应用于实例预测结果与用主分量分析法的趋势预测结果精度接近。     

Color-Redshift Relations and Photometric Redshift Estimations of Quasars in Large Sky Surveys

With a recently constructed composite quasar spectrum and the X2 minimization technique, we describe a general method for estimating the photometric redshifts of a large sample of quasars by deriving theoretical color-redshift relations and comparing the theoretical colors with the observed ones. We estimated the photometric redshifts from the 5-band SDSS photometric data of 18678 quasars in the first major data release of SDSS and compared them with their spectroscopic redshifts. The difference is less than 0.1 for 47% of the quasars and less than 0.2 for 68%. Based on the calculation of the theoretical color-color diagrams of stars, galaxies and quasars both on the SDSS system and on the BATC system, we expect that we would be able to select candidates of high redshift quasars more efficaciously with the latter than with the former, provided the BATC survey can detect objects with magnitudes fainter than 21.     

A new algorithm for the detection of intercluster galaxy filaments using galaxy orientation alignments

We present a new algorithm for detecting intercluster galaxy filaments based upon the assumption that the orientations of constituent galaxies along such filaments are non-isotropic. We apply the algorithm to the 2dF Galaxy Redshift Survey catalogue and find that it readily detects many straight filaments between close cluster pairs. At large intercluster separations  (≫15  h ⁻¹ Mpc)  , we find that the detection efficiency falls quickly, as it also does with more complex filament morphologies. We explore the underlying assumptions and suggest that it is only in the case of close cluster pairs that we can expect galaxy orientations to be significantly correlated with filament direction.     

Short time-scale variability in the Faint Sky Variability Survey

We present the V -band variability analysis of the point sources in the Faint Sky Variability Survey on time-scales from 24 min to tens of days. We find that about one per cent of the point sources down to   V = 24  are variables. We discuss the variability-detection probabilities for each field depending on field sampling, amplitude and time-scale of the variability. The combination of colour and variability information allows us to explore the fraction of variable sources for different spectral types. We find that about 50 per cent of the variables show variability time-scales shorter than 6 h. The total number of variables is dominated by main-sequence sources. The distribution of variables with spectral type is fairly constant along the main sequence, with 1 per cent of the sources being variable, except at the blue end of the main sequence, between spectral types F0 and F5, where the fraction of variable sources increases to about 2 per cent. For bluer sources, above the main sequence, this percentage increases to about 3.5. We find that the combination of the sampling and the number of observations allows us to determine the variability time-scales and amplitudes for a maximum of 40 per cent of the variables found. About a third of the total number of short time-scale variables found in the survey were not detected in either B or/and I band. These show a similar variability time-scale distribution to that found for the variables detected in all three bands.