基于双向长短时循环神经网络的沉积微相自动识别方法——以莺歌海盆地东方B气田为例

莺歌海盆地东方B气田发育浅海重力流海底扇沉积,其砂体分布及叠置关系复杂,使用人工识别的方式进行沉积微相解释工作繁琐且易受主观因素影响。针对该问题,基于双向长短时循环神经网络设计串行网络架构沉积微相识别模型,该模型以测井资料、岩性录井资料为输入,可有效提取不同沉积微相的测井曲线形态特征,并充分考虑相邻沉积微相之间的关联性。将模型应用于该区沉积微相识别工作中,降低了储层非均质性及人工经验带来的影响,提高了识别精度,取得了良好的应用效果。

Ratio-Cum-Product Estimator Using Multiple Auxiliary Attributes in Single Phase Sampling

In this paper, we have proposed a class of ratio-cum-product estimator for estimating population mean of study variable for single phase sampling using multi-auxiliary attributes. The expressions for mean square error are derived. An empirical study is given to compare the performance of the estimator with existing estimators. It has been found that the ratio-cum-product estimator using multiple auxiliary attributes is more efficient than mean per unit, product and ratio estimators using one auxiliary attribute, and Product and Ratio estimators using multiple auxiliary attributes in single phase sampling.

I^2C总线器件与非I^2C总线单片机之间数据传输的软硬件设计

随着计算机技术的发展,I2C总线的应用越来越广泛。I2C是一种简单、双向的二线制同步串行总线,它只需要两根线———串行数据线和串行时钟线就可以在总线与连接器件之间进行数据传送。在介绍了它的工作原理和特点的基础上,阐述了运用C语言模拟I2C总线的程序设计方法,并以AT24C64为例介绍了它与非I2C总线单片机89C2051之间接口的软硬件设计。

低压甲醇合成技术和等温冷管型低压甲醇合成塔

介绍了国内外低压甲醇合成技术的发展现状,论述了等温冷管型低压甲醇合成塔的结构形式、工艺流程和使用特点,总结了该塔的生产应用实例。

Ratio-Cum-Product Estimator Using Multiple Auxiliary Attributes in Two-Phase Sampling

In this paper, we have proposed three classes of ratio-cum-product estimators for estimating population mean of study variable for two-phase sampling using multi-auxiliary attributes for full information, partial information and no information cases. The expressions for mean square errors are derived. An empirical study is given to compare the performance of the estimator with the existing estimator that utilizes auxiliary attribute or multiple auxiliary attributes. The ratio-cum-product estimator in two-phase sampling for full information case has been found to be more efficient than existing estimators and also ratio-cum-product estimator in two-phase sampling for both partial and no information case. Finally, ratio-cum-product estimator in two-phase sampling for partial information case has been found to be more efficient than ratio-cum-product estimator in two-phase sampling for no information case.

Mixture Regression Estimators Using Multi-Auxiliary Variables and Attributes in Two-Phase Sampling

In this paper, we have developed estimators of finite population mean using Mixture Regression estimators using multi-auxiliary variables and attributes in two-phase sampling and investigated its finite sample properties in full, partial and no information cases. An empirical study using natural data is given to compare the performance of the proposed estimators with the existing estimators that utilizes either auxiliary variables or attributes or both for finite population mean. The Mixture Regression estimators in full information case using multiple auxiliary variables and attributes are more efficient than mean per unit, Regression estimator using one auxiliary variable or attribute, Regression estimator using multiple auxiliary variable or attributes and Mixture Regression estimators in both partial and no information case in two-phase sampling. A Mixture Regression estimator in partial information case is more efficient than Mixture Regression estimators in no information case.

Mixture Ratio Estimators Using Multi-Auxiliary Variables and Attributes for Two-Phase Sampling

In this paper, we have proposed three classes of mixture ratio estimators for estimating population mean by using information on auxiliary variables and attributes simultaneously in two-phase sampling under full, partial and no information cases and analyzed the properties of the estimators. A simulated study was carried out to compare the performance of the proposed estimators with the existing estimators of finite population mean. It has been found that the mixture ratio estimator in full information case using multiple auxiliary variables and attributes is more efficient than mean per unit, ratio estimator using one auxiliary variable and one attribute, ratio estimator using multiple auxiliary variable and multiple auxiliary attributes and mixture ratio estimators in both partial and no information case in two-phase sampling. A mixture ratio estimator in partial information case is more efficient than mixture ratio estimators in no information case.

从相关句式的消长看使成式的产生

通过对相关句式此消彼长的动态的考察,窥探使成式的产生时代及其对使成式产生的影响。结论是:两汉时期使动式衰退的同时,受词汇复音化的影响,连动式大量增加,其中一部分被重新分析为使成式。"打汝口破"之类的新兼语式用例较少、发展缓慢,对早期使成式的形成没有直接的影响。

基于双串口单片机的螺旋管外形参数测量数据终端系统

螺旋管的周长、直径等参数对于螺旋管的质量非常重要。详细论述了一种用于螺旋管外形参数在线测量的数据终端系统。该系统采用双串口单片机作为控制器,使用串口1发送可编程控制器(PLC)控制指令并接收PLC的数据,使用串口2将数据保存在U盘,并具有计算、显示等功能。

一种模块化城轨超级电容储能系统及其控制方法

城轨列车的电制动会产生可观的再生制动能量,将多余的再生制动能量进行二次利用可提高系统的节能率。为此,文章提出了一种模块化超级电容储能系统,其基于低压高频变流模块串并联,通过串联系统的直流分压控制,实现了储能系统能量双向流动、充放电电压电流的平稳,并且能使系统快速响应,系统充电响应时间不大于100 ms。基于一套300 kW超级电容储能双向直流变换装置进行了正线挂网验证,结果表明,采用该储能系统后,平均每天节省电量约25 kW·h,节能效果明显。

基于Attention机制的链接预测算法

针对社会网络中链接预测问题,提出了基于注意力(Attention)机制的链接表示及其预测算法.基于待预测节点的共邻关系构建其链接局部网络,设计了基于紧密游走的网络拓扑序列化方法.采用双向循环神经网络(Bi-RNN)对链接序列进行向量编码,以充分挖掘序列相关节点间的上下文依赖信息.通过Attention机制对链接中的节点进行关注和加权,强化重要节点对链接预测任务的贡献,实现链接拓扑特征的自动提取与准确分类预测.实验结果表明,在4种不同类型的社会网络数据集中,该算法的准确率和运算效率都有较大提高且普适性较强.