改进的第三代相干算法及应用

在讨论相干技术发展及三代相干算法优缺点的基础上，介绍了改进的第三代相干算法。应用自行开发的相干软件对多个油气勘探和开发区块的三维地震资料进行处理、分析，对相干时窗长度、相关道数等参数对算法效果的影响及相干体对断层、异常地质体的识别，以及解释方法进行了探讨。应用实例证明，改进的第三代相干算法抗干扰能力强，横向分辨率高，不仅适用于倾斜地层，而且对断层尤其对小断层、异常地质体具有较高的检测能力，是油气勘探和开发的一项有效和实用的技术。     

构造性神经网络在测井岩性识别中的应用

测井岩性识别是石油勘探中十分重要的基础工作,准确的岩性识别结果可以为勘探和开发提供可靠的依据。人工神经网络方法可对复杂的高维数据进行非线性映射,在模式识别领域得到越来越广泛的应用。针对传统的BP神经网络算法存在收敛速度慢、隐层数以及隐层节点数难以确定等缺点,研究了一种构造性神经网络学习算法---级联算法（Cascade Correlation Algorithm,简称CC算法）及其在石油工程中的应用。采用该算法对甘肃镇原-泾川地区进行岩性识别研究,通过与BP神经网络的识别结果进行比较,体现出构造性神经网络的优越性。     

Inference and learning in hybrid probabilistic network

This paper proposed a novel hybrid probabilistic network, which is a good tradeoff between the model complexity and learnability in practice. It relaxes the conditional independence assumptions of Naive Bayes while still permitting efficient inference and learning. Experimental studies on a set of natural domains prove its clear advantages with respect to the generalization ability.     

宣钢1260 m3高炉扩容大修改造设计

宣钢l260m^3高炉大修改造时将炉容扩大到l350m^3，对高炉本体系统设备及冷却系统、自动控制及检测系统进行了全面的改造更新，在炉腹、炉腰及炉身下部高热负荷区域采用铜冷却壁，取消炉身中上部铸铁冷却壁凸台，并采用薄内衬等先进、适用、可靠、成熟的技术。     

Research and Design of Network Management Construction Based on Mobile AGENT

The technical characters of mobile agent （MA） originated in the distributional artificial intelligence domain is introduced. A network management construction based on agent （NMCA） is then proposed. The NMCA structure features are elaborated in detail. A prototype design of NMCA is given by using the jKQML programming. The establishment of NMCA platform will be helpful to reduce the correspondence load of network management and improves the efficiency and the expansion ability of network management systems.     

网络环境下高校图书馆期刊资源建设与发展

本文根据电子期刊的定义、特点及图书馆期刊工作所需要面对的问题，就高校图书馆网络环境下期刊工作的设施规划、资料收集、信息开发及读者培训等多方面内容进行了简单探讨，并就如何应对网络环境下图书馆期刊工作的变化提出建议。     

互联网下会计信息系统内部控制研究

网络会计给企业带来利益的同时 ,也给企业内部控制带来新问题。讨论了建立适应互联网环境下会计信息系统的内部控制 ,其措施应基于企业内部和外部的组织与管理、系统开发及网络系统安全控制等方面的问题     

Use of a neural network to link AFM etch patterns to plasma parameters

Plasmas play a critical role in depositing thin films or etching fine patterns while manufacturing integrated circuits. A new model for plasma diagnosis is presented. This was accomplished by linking atomic force microscopy (AFM) to plasma parameters using a neural network. Experimental AFM data were collected during the etching of silicon oxynitride films in C₂F₆ inductively coupled plasma. Surface roughness of etched patterns was characterized by means of discrete wavelet transformation. This led to the construction of three vertical (type I), diagonal (type II), and horizontal (type III) wavelet coefficient-based models. The performance of diagnosis models was evaluated in terms of the prediction and recognition accuracies. Both accuracies were optimized as a function of the number of hidden neurons. Comparisons revealed that the type I model yielded the largest recognition and the smallest prediction error. This was demonstrated even under stricter monitoring conditions. More improved diagnosis is expected by enhancing AFM resolution.     

阳泉市煤矿采空区地质因素对公路的破坏

介绍了阳泉市煤矿采空区对公路建设所造成的危害，对其上覆岩层变形破坏的地质因素及其破坏机理作了分析，指出应该采取各种措施减少对公路的破坏。     

GPRS无线DDN系统与应用

介绍基于GPRS网络无线DDN系统的构成、组网以及在电力系统的应用，同时对传输包长度、效率、时延等参数进行分析。