Biometric analysis of lacustrine and riverine populations of Palemonetes antennarius (H. Milne-Edwards, 1837) (Crustacea, Decapoda, Palaemonidae) from north-western Greece

Comparative study of morphometric measurements was undertaken on populations of Palaemonetes antennarius from two freshwater habitat zones (lacustrine pelagic and lacustrine littoral) and from the fluvial littoral habitat zone of three estuaries of north-western Greece. Multivariate statistical analyses (principal component analysis and discriminant function analysis) revealed clear morphometric differences between sexes and sampling sites. The observed differences are expressed mainly thought the measurements related to the body heights (carapace height and second pleon height), as a result of sexual dimorphism, High values for the female body heights seem to be correlated to specific fecundity profile and reproductive strategy. On the other hand, morphometrical variables related mainly to body lengths, such as rostral, telson and pleon lengths, were observed to be correlated to the study sites. Characters related to the summing capacity (telson length, telson width and pleon lengths) were generally found to have higher values in the specimens from habitats with high reophilic profile.     

基于判别分析法的地震砂土液化预测研究

将距离判别分析方法应用于砂土液化的预测问题中,建立了砂土液化预测的距离判别模型。选用震级、研究深度、震中距、标贯击数、地下水位及地震持续时间等6项指标作为判别因子,以大量的工程实例数据作为学习样本进行训练,建立了线性判别函数对待评样本进行了评价。研究结果表明,距离判别分析模型判别砂土液化效果良好,预测准确度高,回判估计误判率低,可望成为砂土液化预测的有效手段。     

我国南海4个青蛤野生群体的形态差异分析

用8个形态性状比较我国南海4个野生青蛤群体间的形态变异。聚类分析表明,湛江群体和汕头群体的形态较接近,海口群体的趋异最大。主成分分析表明,主成分1、2、3的贡献率分别为26.441%、21.104%、15.884%,累计贡献率为63.428%。逐步判别分析结果显示,4个群体形态差异显著(P<0.01)。建立了4群体判别函数,其判别准确率P1为51.4%～71.4%,判别分析准确率P2为60%～75.8%,4群体的综合判别率为64.3%。Mantel-test检验结果表明,我国南海青蛤不同地理群体的欧式距离与地理距离没有明显的相关性(r=0.4227,P=0.3910)。     

长白山玄武岩区地热异常区遥感识别

利用Landsat TM5遥感影像多光谱和热红外数据,对长白山玄武岩区地表温度场进行了反演。在此基础上,综合分析了研究区地表温度场、温泉和地热井分布特征、布格重力场及磁场4个因子,采用判别分析方法建立并验证了判别函数,对研究区地热异常区进行了识别。研究结果表明:研究区地表温度异常区主要分布在长白山天池火山口周围,此外,在区内3个中生代沉积盆地(抚松盆地、松江盆地和长白盆地)也有孤立状的高温区域分布,地表温度异常像素所占比例为2.993%;研究区潜在地热资源异常区可分为环长白山天池火山口区域、松江河—抚松县及二道白河—松江镇一带的抚松盆地和松江盆区、仙人桥地区以及长白县—十四道沟一带的长白盆地区,其中环长白山天池火山口区域地热潜在概率值均大于0.9,最大值达到1.0。该研究为地热异常区的识别提供了一条新的思路。     

Multivariate analysis to investigate Cl distribution in rocks from different settings

Chlorine concentration has been determined by chemical methods in 97 samples of basic rocks collected at Etna volcano (Sicily, Southern Italy), Sao Miguel (Azores Islands), and Lanzarote (Canary Islands). The samples have been processed together with data related to specific magmatic and tectonic conditions, drawn from the literature. Thus, the contents of SiO₂, K₂O, and P₂O₅ of 228 samples have been used to investigate Cl distribution in the considered environments, using principal component analysis. The log-centered variance-covariance matrix has been processed in order to overcome the closure constraints. The results indicate that a clear distinction between continental and oceanic regions can be obtained in the components space. A preliminary discriminant diagram involving chlorine thus can be proposed.     

基本气象资料质量控制综合判别法的研究

对于气象资料质量控制中单项检验为可疑的数据,如何进一步判别它的错误与正确,是气象资料质量控制中的一个重大技术问题.气象资料质量控制综合判别法就是试图解决这个问题而新研制的一种方法.该文概述了气象资料质量控制综合判别法的基本思路、基本内容和步骤;就气象资料质量控制综合判别法在地面气象资料质量控制中的应用举例说明;并进一步阐述了气象资料质量控制综合判别法的加权判别技术.气象资料质量控制综合判别法已在中国气象局气象信息中心气象资料室的地面资料质量控制中得以应用.     

神经网络方法在岩性识别中的应用

在可地浸砂岩型铀矿测井工作中,铀矿地球物理测井方法提供了电阻率、密度、声波等多种地球物理参数。通过采用神经网络方法,利用上述参数．进行钻孔岩性识别的有关研究,确定了B-P网络结构及算法,并进行了初步应用和对比。     

Statistical Interpretation of Webnet Seismograms By Artificial Neural Nets

We employed multilayer perceptrons (MLP), self organizing feature maps (SOFM), and learning vector quantization (LVQ) to reveal and interpret statistically significant features of different categories of waveform parameter vectors extracted from three-component WEBNET velocigrams. In this contribution we present and discuss in a summarizing manner the results of (i) SOFM classification and MLP discrimination between microearthquakes and explosions on the basis of single-station spectral and amplitude parameter vectors, (ii) SOFM/LVQ recognition of initial onset polarities from PV'-waveforms, and (iii) a source mechanism study of the January 1997 microearthquake swarm based on SOFM classification of combined multi-station PV-onset polarity and SH/PVamplitude ratio (CPA) data. Unsupervised SOFM classification of 497 NKC seismograms revealed that the best discriminants are pure spectral parameter vectors for the recognition of microearthquakes (reliability 95% with 30 spectral parameters), and mixed amplitude and spectral parameter vectors for the recognition of explosions (reliability 98% with 41 amplitude and 30 spectral parameters). The optimal MLP, trained with the standard backpropagation error method by one randomly selected half of a set of 312 mixed (7 amplitude and 7 spectral) single-station (NKC) microearthquake and explosion parameter vectors and tested by the other half-set, and vice versa, correctly classified, on average, 99% of all events. From a set of NKC PV-waveform vectors for 375 events, the optimal LVQ net correctly classified, on average, 98% of all up and 97% of all down onsets, and assigned the likely correct polarity to 85% of the onsets that were visually classified as uncertain. Optimal SOFM architectures categorized the CPA parameter vector sets for 145 January 97 events individually for each of five stations (KOC, KRC, SKC, NKC, LAC) quite unambiguously and stable into three statistically significant classes. The nature of the coincidence of these classes among the stations that provided most reliable mechanism-relevant information (KOC, KRC, SKC) points at the occurence of further seven statistically significant subclassses of mechanisms during the swarm. The ten neural classes of focal mechanisms coincide fairly well with those obtained by moment tensor inversion of P and SH polarities and amplitudes extracted from the seismograms interactively. The obtained results, together with those of refined hypocenter location, imply that the focal area consisted of three dominant faults and at least seven subfaults within a volume of not more than 1 km in diameter that likely were seismically activated by vertical stress from underneath.     

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