Excel2000在工程造价管理中的应用

Excel2000主要是用来管理、组织和处理各种各样的数据.本文主要介绍了Excel2000在工程造价管理方面发挥的功能,从而方便地减轻了繁杂的计算工作问题.     

情报网络对生产／流通过程中的库存的影响

本文通过建立独立型、垂直型和综合型3种模型,从订货方式和服务水平两个侧面,分析、考察了在生产/流通系统中建立情报网络而对系统中的库存所产生的影响。并据此提出了“失连库存”的新概念,对其进行了定量的分析和评价。本文得到的结论不仅在多阶层库存理论的研究上是必不可少的,而且对我国发展管理信息系统等现代化管理技术都具有指导意义。     

航线收益管理的边际分析方法

 本文首先综述了航线运输收益管理中两票价等级的最优运营方法的历史与现状,指出了各个经典公式的限制条件和公式推导的不严密性。然后,利用边际分析方法详细推导了一个新的最优座位安排的通用公式,对该领域的传统公式作了重要更正。最后,通过实例分析、计算并与传统公式相比,表明新公式在理论上较为完善,在工程上也实用、简便。     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

Mapping Regolith and Gossan for Mineral Exploration in the Eastern Kumaon Himalaya,India using hyperion data and object oriented image classification

Crystalline in the Kumaon Himalaya, India near Askot area is a prominent site of the base metal mineralization and gossanised surface. This area is hosted by the sulphides and sulphates of Cu, Pb, Zn and Au and Ag mineralization with the altered rocks like sericite chlorite schist, gneiss etc. Due to the deep weathering this area is also a good illustration site of the gossanised outcrop.     

基于多尺度 3D-2D卷积神经网络的高光谱图像分类

设计提出了 1种针对高光谱图像分类任务的 3D-MSCNN模型。在 PCA降维的基础上,利用 3D空谱特征提 取网络和 2D多尺度特征提取网络实现高光谱图像特征提取,充分发挥高光谱图像空谱信息价值,增强对不同尺度 地表覆盖的表达能力。最后,利用 Softmax分类损失函数实现高光谱图像分类任务。实验结果表明,本文算法在 In. dian Pines和 Pavia University数据集上都取得了较好的分类效果。与 CD-CNN、3D-CNN、SS-Net和 HybirdSN等方法相 比,本文算法能够有效提升总体精度、平均精度和 Kappa系数等客观评价指标。     

Collaborative image compression and classification with multi-task learning for visual Internet of Things

Widespread deployment of the Internet of Things(Io T) has changed the way that network services are developed, deployed, and operated. Most onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io T. Typically, the sender would compress images, and then through the communication network, the receiver would decode images, and then analyze the images for applications. However, image compression and semantic inference are generally conducted separately, and t...     

低温推进剂加注液位信号智能处理技术研究

低温加注系统是运载火箭发射场地面支持设备的重要组成部分,包括低温介质的储存、运输、供给、控制以及安全等内容。由于低温推进剂本身存在低温沸腾、易挥发的特性,其加注过程十分复杂,为满足新一代运载火箭推进剂精准的加注要求,需要实时准确监测加注过程中贮箱内的液位高度。本文针对火箭地面加注过程的液位信号数据,对其三角波电压和线性波电压的特征进行分析、提取,基于BP（Back Propagation,反向传播）神经网络算法完成对不同加注状态的识别检测,并应用于传感器节数判别,优化了液位计算算法,降低了节数人为干预需求,提高了液位测量准确性。经实验测试验证,该方法可有效识别低温加注状态,识别准确率达到90%以上,用于液位信号处理中可显著提升液位高度计算的准确性。     

基于理想解的模拟调制识别分析

利用排序待判决信号特征逼近各候选调制方式理想解的程度来实现调制方式识别,该方法不需要确定判决门限,运算量较小。以基本的模拟调制方式为对象,深入分析其识别性能,考察各权值系数对识别概率的影响,可以发现:一般各调制方式均只会被误判成其他某一种调制方式,且不同权值系数对判决结果的影响程度相差较大。因此,可以针对调制方式误判类型寻求新的特征参数,探求最优权值系数来进一步提升所提方法的识别性能。     

基于S-PSO分类算法的故障诊断方法

将监控数据的已知状态作为先验类别标签,构造出新的有监督的粒子群优化(S-PSO)分类算法,并对设备进行故障诊断。为提高故障诊断的准确率,降低随机性对分类算法的影响,提出了新的基于动态邻域的自适应探测更新(ADU-DN)的干预更新策略来拓展粒子搜索整个解空间的能力,引导粒子自适应地跳出局部最优区域,确保获得全局最优解;同时设计出基于最小类内距离、最大类间距离和训练样本最大分类精度的适应度函数,使得输出的最优类别中心兼顾了这3个因素,增强了分类算法在故障诊断中的通用性和容错性,提高了测试样本的分类精度。S-PSO分类算法有效克服了聚类算法只考虑数据间相似性特征、不考虑数据蕴含的物理意义以及不能很好指导样本分类的缺陷。对GE90发动机孔探图像纹理特征分类进行了对比研究,研究数据表明:S-PSO分类算法表现出了较强的鲁棒性,在故障诊断中的分类精度高于支持向量机(SVM)和常用神经网络模型。