孤北21三维目标处理实例

结合地质目标及处理要求,对孤北21井区三维资料进行了分析。对不同处理目标采取了相应的处理措施,取得了较好的处理效果。     

用人工神经网络实现地震记录中的废道自动切除

切除废道（即道编辑）的工作是地震信号处理中重要而又工作量巨大的一步.本文提出了一种用人工神经网络实现的自动切除方法,所用的神经网络模型为新奇滤波器模型,方法简单实用,切除效果令人满意.文中介绍了方法的原理并给出了几个实验结果.     

瞬变电磁测深法的研究深度

研究发现,瞬变测深法研究深度除了与采样时间(采样间隔,起始和终止采样时间等)有关外,还与信号源强度、大地电导率、系统噪音水平以及仪器观测精度等因素有关,文中对研究深度与这些量之间的关系作了数学描述。     

华北遥测地震台网联网中心信号系统设计与实现

根据世界银行贷款项目——国家部分的总体设计和实施方案的要求,建立华北遥测地震台网联网中心。本文概括介绍了华北联网中心信号汇集与分配系统的设计与实现。     

Monthly suspended sediment load prediction using artificial intelligence: testing of a new random subspace method

ABSTRACT

The predictive capability of a new artificial intelligence method, random subspace (RS), for the prediction of suspended sediment load in rivers was compared with commonly used methods: random forest (RF) and two support vector machine (SVM) models using a radial basis function kernel (SVM-RBF) and a normalized polynomial kernel (SVM-NPK). Using river discharge, rainfall and river stage data from the Haraz River, Iran, the results revealed: (a) the RS model provided a superior predictive accuracy (NSE = 0.83) to SVM-RBF (NSE = 0.80), SVM-NPK (NSE = 0.78) and RF (NSE = 0.68), corresponding to very good, good, satisfactory and unsatisfactory accuracies in load prediction; (b) the RBF kernel outperformed the NPK kernel; (c) the predictive capability was most sensitive to gamma and epsilon in SVM models, maximum depth of a tree and the number of features in RF models, classifier type, number of trees and subspace size in RS models; and (d) suspended sediment loads were most closely correlated with river discharge (PCC = 0.76). Overall, the results show that RS models have great potential in data poor watersheds, such as that studied here, to produce strong predictions of suspended load based on monthly records of river discharge, rainfall depth and river stage alone.     

Investigation of Image Fusion Between High—Resolution Image and Multi—Spectral Image

On the basis of a thorough understanding of the physical characteristics of remote sensing image,this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm.The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China The experimental results show that a perfect image fusion can be built up by using the image analytical solution and reconstruction in the image frequency domain based on the physical characteristics of the image formation.The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.     

2002年5月甘肃省低温多雨天气分析

给出了甘肃省2002年5月的温度、降水、极端最低气温和雨日概况,分析了西太平洋副热带高压阶段性的异常、极涡的位置和强度以及水汽条件和冷空气条件,计算了甘肃省5月降水与太平洋海温的相关性,并与典型相似年份的前兆信号进行了比较。     

小波变换在探地雷达探测地下管线信号处理中的应用

阐述了小波变换的基本理论,给出了小波变换在探地雷达方面的应用实例．认为小波变换时频局域性好,是分析非平稳信号的有效工具之一。实例分析表明,小波方法在城市地下管线探测信号去除噪音分析处理方面具有优异性能。能有效提高探地雷达探测地下管线的精度。     

MIDAS-W: a workstation-based incoherent scatter radar data acquisition system

The Millstone Hill Incoherent Scatter Data Acquisition System (MIDAS) is based on an abstract model of an incoherent scatter radar. This model is implemented in a hierarchical software system, which serves to isolate hardware and low-level software implementation details from higher levels of the system. Inherent in this is the idea that implementation details can easily be changed in response to technological advances. MIDAS is an evolutionary system, and the MIDAS hardware has, in fact, evolved while the basic software model has remained unchanged. From the earliest days of MIDAS, it was realized that some functions implemented in specialized hardware might eventually be implemented by software in a general-purpose computer. MIDAS-W is the realization of this concept. The core component of MIDAS-W is a Sun Microsystems UltraSparc 10 workstation equipped with an Ultrarad 1280 PCI bus analog to digital (A/D) converter board. In the current implementation, a 2.25 MHz intermediate frequency (IF) is bandpass sampled at 1 s intervals and these samples are multicast over a high-speed Ethernet which serves as a raw data bus. A second workstation receives the samples, converts them to filtered, decimated, complex baseband samples and computes the lag-profile matrix of the decimated samples. Overall performance is approximately ten times better than the previous MIDAS system, which utilizes a custom digital filtering module and array processor based correlator. A major advantage of MIDAS-W is its flexibility. A portable, single-workstation data acquisition system can be implemented by moving the software receiver and correlator programs to the workstation with the A/D converter. When the data samples are multicast, additional data processing systems, for example for raw data recording, can be implemented simply by adding another workstation with suitable software to the high-speed network. Testing of new data processing software is also greatly simplified, because a workstation with the new software can be added to the network without impacting the production system. MIDAS-W has been operated in parallel with the existing MIDAS-1 system to verify that incoherent scatter measurements by the two systems agree. MIDAS-W has also been used in a high-bandwidth mode to collect data on the November, 1999, Leonid meteor shower.