A two-stage algorithm for identification of nonlinear dynamic systems

This paper investigates the two-stage stepwise identification for a class of nonlinear dynamic systems that can be described by linear-in-the-parameters models, and the model has to be built from a very large pool of basis functions or model terms. The main objective is to improve the compactness of the model that is obtained by the forward stepwise methods, while retaining the computational efficiency. The proposed algorithm first generates an initial model using a forward stepwise procedure. The significance of each selected term is then reviewed at the second stage and all insignificant ones are replaced, resulting in an optimised compact model with significantly improved performance. The main contribution of this paper is that these two stages are performed within a well-defined regression context, leading to significantly reduced computational complexity. The efficiency of the algorithm is confirmed by the computational complexity analysis, and its effectiveness is demonstrated by the simulation results.     

我国天然彩棉的研发现状及发展趋势

对天然彩棉的历史、纤维特点、纤维的形态结构及性能作了简要介绍，重点介绍了我国彩棉的研发现状及研发中亟待解决的瓶颈问题，最后对彩棉在我国的发展前景进行了展望。     

可追溯的绿色安全猪肉生产系统研究

现在，养猪生产者滥用激素、微量元素和违禁药物饲养生猪，而消费者却无法识别这种猪肉，严重地威胁着消费者的食品卫生安全。为此，应用射频识别技术，采用综合软件管理，以一维条形码实行三网合一查验的方式来建立猪肉生产卫生安全跟踪系统，是保障消费者食品卫生安全的理想方法。     

基于隐性故障模型和风险理论的关键线路辨识

在大规模电网中，由简单故障触发的电力系统连锁故障常常会引起大停电的灾难性后果。为了研究复杂电网连锁故障的传播机理，同时找出对连锁故障产生重要影响的关键线路，文中基于模拟连锁故障的隐性故障模型和风险理论，提出了复杂电力系统的线路故障风险评估方法，并辨识出了对系统大停电产生重要影响的一系列关键线路。模型考虑了线路过负荷保护、隐性故障、控制策略及系统运行等参数，对IEEE 118节点系统仿真结果表明，在重负荷状态运行下只对辨识出的少量关键线路加以改善，就可以使系统停电概率大幅减小，特别是大停电概率;在临界状态运行下改善少量关键线路，则可以使系统脱离临界状态，避免大停电发生。     

桥梁颤振气动导数识别的迭代法

本文提出一种利用自由振动响应通过年顿－拉夫逊迭代同时识别出桥梁全部8个颤振气动导的方法。此法具有对迭代初值要求不高，识别结果稳定的特点，并具有一定的抗噪声干扰能力。数字仿真与实物试验结果表明本文方法有效，可行。     

Approximate channel identification via δ‐signed correlation

A method of approximate channel identification is proposed that is based on a simplification of the correlation estimator. Despite the numerical simplification (no multiplications or additions are required, only comparisons and an accumulator), the performance of the proposed estimator is not significantly worse than that of the standard correlation estimator. A free (user selectable) parameter moves ‘smoothly’ from a situation with small sum‐squared channel estimation error but hard‐to‐identify channel peaks, to one with a larger sum‐squared estimation error but easy‐to‐identify channel peaks. The proposed estimator is shown to be biased and its behaviour is analysed in a number of situations. Applications of the proposed estimator to sparsity detection, symbol timing recovery and to the initialization of blind equalizers are suggested. Copyright © 2002 John Wiley & Sons, Ltd.     

我国海洋石油钻井平台现状与技术发展分析

海洋油气开发装备产业是直接关系到海洋油气资源开发、影响国家能源稳定和经济安全的战略产业。海洋石油钻井平台是海洋油气开发的关键装备,我国海洋石油装备产业在海洋油气产业持续快速发展的带动下,正处于高速发展的新时期。对我国海洋石油钻井装备产业发展现状及市场需求进行了深入研究,并对海洋石油钻井平台技术特点做了介绍,重点分析了该项技术的发展状况,从钻井平台类型和技术含量等方面指出我国与世界先进海洋石油钻井平台的主要差距,并提出了若干发展建议。     

智能钻井电缆信号传输的研究现状及难点

目前，钻井中井下检测信号的传输主要运用泥浆脉冲、电磁波等方式。随着井深的增加、复杂结构井和欠平衡井的增多以及对传输速度要求的提高，电缆信号传输必然是今后智能钻井的发展方向。通过对半个多世纪来各类电缆信号传输的设计进行归类，详细介绍了其设计原理，提出了电缆信号传输设计的基本要求与难点。     

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。