Modelling evaporation using an artificial neural network algorithm

This paper investigates the prediction of Class A pan evaporation using the artificial neural network (ANN) technique. The ANN back propagation algorithm has been evaluated for its applicability for predicting evaporation from minimum climatic data. Four combinations of input data were considered and the resulting values of evaporation were analysed and compared with those of existing models. The results from this study suggest that the neural computing technique could be employed successfully in modelling the evaporation process from the available climatic data set. However, an analysis of the residuals from the ANN models developed revealed that the models showed significant error in predictions during the validation, implying loss of generalization properties of ANN models unless trained carefully. The study indicated that evaporation values could be reasonably estimated using temperature data only through the ANN technique. This would be of much use in instances where data availability is limited. Copyright © 2002 John Wiley & Sons, Ltd.     

应用CP网络进行岩性识别

为通过测井解决岩性识别问题，引入了具有分类准确、算法简练等优点的CP（Counter-Propagation)网络。在详细介绍CP网络的网络模型和算法的基础上，结合某油田的实际测井资料，进行了CP网络识别研究。应用结果表明：CP网络训练周期短、识别准确率高、不存在收敛问题。通过试验研究得出结论：CP网络完全可以用于解决岩性识别等问题，具有广阔的应用前景。     

数字遥测地震台网地震速报中文平台

叙述了数字遥测地震台网地震速报中平台程序基本流程和使用特点，程序采用Vi编程方法实现以二维坐标点阵结构显示汉字，与台网的交互软件（EDSP-IAS）中的WaveView程序自动链接运行，该闰台界面操作方便直观，易于定位地震参数，自动速报上网和自动寻呼。     

Estimation of azimuth and slowness of tele-seismic signals recorded by a local seismic network

Introduction The azimuth and slowness are two major features of seismic signals. The accurate estimation of them is quite important for both phase identification and event location. Generally, there are two types of seismic stations, i.e. 3-component stations (3C) and arrays. To estimate the two direc-tional parameters, the polarization analysis (Jurkevics, 1988) is commonly used for 3C stations and the frequency-wavenumber spectrum analysis ( f-k) (Capon, 1969; Kvaerna, Doornbos, 1986) is …     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS*

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN (artificial neural network) retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.     

辽宁省地震前兆台网技术改造概述

“九五”期间实施的《辽宁省地震前兆台网技术改造项目》使辽宁省地震前兆观测技术系统由模拟到数字实现了质的飞跃，本文对项目的技术思路，实施情况，取得的成果及建设特色进行了介绍。     

新疆数字地震前兆台网的数据传输功能分析

为了进一步提高地震前兆数据的传输效率和准确性 ,实现前兆数据采集和管理的自动化 ,对新疆地震局数字化地震前兆台网中心的功能、数据采集原理、数据传输特征进行了分析 ,认为数字化观测技术为地震前兆数据的采集、传输提供了一种高效、可靠的手段     

河南豫北地震台网地区波速的探讨

为了解决河南豫北地区地震的定位问题 ,对豫北台网内的 10个典型地震 ,使用了 7个地震台站的资料 ,用波速比求出横波速度 ;用和达定位法 (有的同时使用高桥法 )进行了精确定位 ,求出震源深度 ;测量了震中至各台的震中距 ,以此反算出了纵波速度。通过计算 ,确定出了较为适合河南豫北地震台网地区的波速。     

Establishment of a Non-Permanent GPS Network to Monitor the Recent NE-SW Deformation in the Granada Basin (Betic Cordillera,Southern Spain)

The Granada Basin (Central Betic Cordillera), one of the most seismically active areas of the Iberian Peninsula, is currently subjected to NW-SE compression and NE-SW extension. The present day extension is accommodated by normal faults with various orientations but particularly with a NW-SE strike. At the surface, these active NW-SE normal faults are mainly concentrated on the NE part of the Basin. In this part we have selected a 15-km long segment where several active normal faults crop out. Using the marine Tortonian rocks as a reference, we have calculated a minimum extensional rate of 0.15-0.30 mm/year. The observed block rotation, the listric geometry of faults at depth and the distribution of seismicity over the whole Basin, indicate that this rate is a minimum value. In the framework of an interdisciplinary research project a non-permanent GPS-network has been established in the central sector of Betic Cordillera to monitor the crustal deformations. The first two observation campaigns were done in 1999 and 2000.