Failure Impact,Availability and Cost Analysis of PONs Based on a Network Geometric Model

Passive Optical Networks(PONs)are considered as the preferred solution for broadband fibre-based access networks.This is because PONs present low cost deployment,low energy consumption and also meet high bandwidth demands from end users.In addition,end users expect a high availability for access networks,while operators are more concerned about reducing the failure impact(number of clients affected by failures).Moreover,operators are also interested in reducing the cost of the access network.This paper provides a deep insight into the consequences that the physical topology and design decisions cause on the availability,the failure impact and the cost of a PON.In order to do that,the physical layout of the PON deployment area is approximated by a network geometric model.A PON deployed according to the geometric model is then assessed in terms of failure impact,availability and cost.This way,the effects of different design decisions and the physical layout on these three parameters are evaluated.In addition,the tradeoffs between availability,failure impact and cost caused by planning decisions and the physical topology are identified and pinpointed.

Impact of Enforcement of Right of Communication through Information Network

On 27 October 2001, the Standing Committee of the People's Congress reviewed and passed the Amendment to the Copyright Law of the People's Republic of China. In Article 10 of the amended Copyright Law as of 2001 has been incorporated a new subject matter under the copyright protection: the right of communication through information network, that is, the right to make a work available to the public by wire or by wireless means, so that people may have access to the work from a place and at a time individu...

Comparative Analysis of Machine Learning Models for Customer Churn Prediction in the U.S. Banking and Financial Services: Economic Impact and Industry-Specific Insights

Customer churn poses a significant challenge for the banking and finance industry in the United States, directly affecting profitability and market share. This study conducts a comprehensive comparative analysis of machine learning models for customer churn prediction, focusing on the U.S. context. The research evaluates the performance of logistic regression, random forest, and neural networks using industry-specific datasets, considering the economic impact and practical implications of the findings. The exploratory data analysis reveals unique patterns and trends in the U.S. banking and finance industry, such as the age distribution of customers and the prevalence of dormant accounts. The study incorporates macroeconomic factors to capture the potential influence of external conditions on customer churn behavior. The findings highlight the importance of leveraging advanced machine learning techniques and comprehensive customer data to develop effective churn prevention strategies in the U.S. context. By accurately predicting customer churn, financial institutions can proactively identify at-risk customers, implement targeted retention strategies, and optimize resource allocation. The study discusses the limitations and potential future improvements, serving as a roadmap for researchers and practitioners to further advance the field of customer churn prediction in the evolving landscape of the U.S. banking and finance industry.

A Study of Chinese College Students’ View on the Latest Network Catchwords

随着网络技术的迅猛发展,人们对网络的研究也风生水起。互联网是一个虚拟社区,它和现实社会有着直接的割不断的联系。在虚拟社区中,人与人交往离不开网络语言。本文主要研究中国大学生对网络流行语的态度并总结了网络语言的发展前景。

Role of Energy Storage on Distribution Transformer Loading in Low Voltage Distribution Network

Energy storage (ES) is a form of media that store one form of energy to be utilized at another time. Importance of ES is comprehended while intermittent nature of renewable energy (RE) generation increases and integration into the grid becomes viable in terms of economics and environment. However, technical analysis should be carried out before large scale integration into the grid. Some utilities experienced in Europe and expressed concern about issues in integrating large scale renewable energy in the areas of harmonics, voltage regulation, network protection and islanding. In Australia, distribution network (DN) is not robust compared to the European grid;moreover loads are largely distributed over large geographical areas. Installation of RE such as roof top solar photovoltaic (PV) is increasing in Australia which also boosted by the governments incentives to the individual owners. It is therefore obvious that large scale PV integration into the Australian grid is imminent. The intermittent characteristic of solar PV is expected to have greater impacts on DN in Australia compared to the DN in Europe. Therefore this paper investigated the impacts of solar PV on low voltage (LV) DN where loads connected through distribution transformer (DT) and finally further investigation was conducted with the deployment of ES into the respective load centers. It was found that storage reduced the overall peak load condition on the DT, and also reduced the energy fluctuation in the DN. It was also found that storage improved the voltage regulation on the LV side of DT and stabilized node voltage.

SYNTHESIS,CHARACTERIZATION AND PROPERTIES OF ORGANOCLAYMODIFIED POLYSULFONE/EPOXY INTERPENETRATING POLYMER NETWORK NANOCOMPOSITES

Organoclay-modified hydroxylterminated polysulfone (PSF)/epoxy interpenetrating network nanocomposites (oM-PSF/EP nanocomposites) were prepared by adding organophilic montmorillonite (oMMT) to interpenetrating polymer networks (IPNs) of polysulfone and epoxy resin (PSF/EP) using diaminodiphenylmethane (DDM) as curing agent.The mechanical properties like tensile strength,tensile modulus,flexural strength,flexural modulus and impact properties of the nanocomposites were studied as per ASTM standards.Different...

Study of Detecting Impact Damage for Composite Material Based on Intelligent Sensor

A system of impact damage detection for composite material structures by using an intelligent sensor embedded in composite material is described. In the course of signal processing, wavelet transform has the exceptional property of temporal frequency localization, whereas Kohonen artificial neural networks have excellent characteristics of self-learning and fault-tolerance. By combining the merits of abstracting time-frequency domain eigenvalues and improving the ratio of signal to noise in this system, impact damage in composite material can be properly recognized.

Structural Analysis and Static Simulation of Coastal Planktonic Networks

The coastal marine habitats are often characterized by high biological activity. Therefore, monitoring programs and conservation plans of coastal environments are needed. So, in order to contribute to decision making process of the Brazilian Information System of Coastal Management, this paper presents a preliminary analysis of the effects of simulated deletions of individual organisms within a planktonic network as knowledge acquisition platform. An in situ scanning flow cytometer was used to data acquisition. A static and undirected food web is generated and represented by a fuzzy graph structure. Our results show through a series of indices the main changes of these networks. It was also verified similar traits and properties with other food webs found in the literature.

雷达转台液压系统可靠性影响评价预测研究

针对当前雷达液压系统可靠性合理建模及影响评价体系难以构建及评估的现状,以某典型机载雷达转台液压系统为研究对象,提出一种基于危害性分析的可靠性影响评价预测方法。利用模糊判断矩阵以获得指标的权重系数,对可靠性进行建模仿真分析,从而为准确预测系统的可靠性提供理论支撑。在此基础上,通过对转台液压系统故障原因进行全面梳理,构建了液压系统可靠性影响评价体系。运用Elman网络,结合实证分析对可靠性影响评价模型进行预测,为雷达转台液压系统故障的综合分析提供了整体解决方案。这也为进一步提高雷达液压系统的可靠性提供了合理思路。该研究可为雷达其他分系统可靠性分析提供参考。

Application of SimaPro7 on Al-Hilla City Sewerage Network, Iraq

SimaPro is a software package designed to make a valuable contribution for analyzing the environmental impact on products during their whole life cycle. A huge amount of knowledge about the environment is built into the program and database, enabling to analyze a product with a minimum of specialized knowledge. In this study, SimaPro was used to analyze and evaluate the impacts that resulted from sewerage network in Al-Hilla city, Iraq. The results of Life Cycle Assessment (LCA) showed that sewerage network had an impact and damage on the environment by 291 points for every cubic meter of collect wastewater. The most potential environmental impacts were global warming, respiratory inorganics and non-renewable energy, contributing to the sewerage network. The study also showed that most of the effects were as a result of energy consumption in the pumping of wastewater, pipes used and diesel using for network operation.

弧齿锥齿轮动力特性分析及其神经网络控制

针对含间隙锥齿轮系统动力学特性转迁及其控制问题,提出了基于胞元映射理论的参数解域结构和基于径向基函数神经网络的控制方法。采用集中质量法建立了7自由度弧齿锥齿轮动力学模型,基于胞元映射理论构建了频率和负载参数平面,采用伪不动点延续追踪算法求解了系统的分岔、齿面冲击、脱啮、齿背接触和动载特性转迁规律,分析发现频率和齿面冲击是影响周期分岔的主要因素,随负载增大其脱啮、冲击减弱,动载系数增大。针对平面中系统混沌现象,设计了参数反馈控制器、基于Poincaré截面欧氏距离构造适应度函数,用自适应引力搜索算法对控制器参数进行优化,从而实现了系统混沌、拟周期和周期运动向周期轨道有效控制。

国家水网构建与生态安全保障辩证关系探析

国家水网建设和水生态安全保障是当前和今后一个时期水利行业的核心工作,准确认识两者的辩证关系,对于促进水利高质量发展、为中国式现代化提供高标准水安全保障具有重要意义。从国家水网建设与我国生态安全总体格局、北方生态屏障区保护修复、缺水地区河湖生态环境复苏、地下水超采区治理恢复、河湖水质改善、重要湿地及其生物多样性保护等六个方面的关系阐述了国家水网对于保障国家生态安全的重要作用。科学解析了国家水网规划、建设与运行对生态安全保障可能带来的影响,提出协同推进国家水网建设与生态安全保障的措施建议:优化国家生态安全保障整体格局,明晰重点区域生态安全保障水资源需求;在国家水网框架内,开展国家水生态网整体规划与建设;维护和发挥地下水应急储备水源功能,构建立体国家水网;加强水网内部源头减排与属地治理,建设清洁水网;发挥国家战略储备水源区作用,降低集中调水对长江流域的影响;加强水工程全生命期绿色技术研发与应用。

新形势下网络教学模式在环境影响评价课程中的应用

环境影响评价是环境专业的核心课程,其内容涉及广泛、实用性强,但传统教学模式很难达到高标准的教学目的。该文对传统教学模式存在的问题进行梳理分析及讨论,同时“互联网+”教育模式逐渐出现在大众视野。该文基于“互联网+”技术和思维,探讨有效的新型教学模式,该模式激发同学们的学习热情,重新构建教学过程。结合新形势下网络发展,加强环境影响评价课程的教学建设,加强学生对课程深度及广度的认知与延伸,进而提高学生能力和课堂教学质量。

基于组合权重法的云南省地质灾害灾情年度评价及预测

为合理评价云南省地质灾害灾情年度等级,探寻地质灾害的时序发展规律,并预测未来年份地质灾害灾情等级,本文选取死亡失踪人数、直接经济损失、灾情数量3个影响因素作为权重指标,采用层次分析法与熵权法相结合的组合权重法对1991—2020年地质灾害灾情年度等级进行评价。利用差分自回归积分移动平均模型(autoregressive inte-grated moving average method,ARIMA)和BP(back propagation)神经网络模型2种方法,对2021年、2022年、2023年灾情等级进行对比预测和验证。研究表明:地质灾害灾情年度具有5年的周期性变化特征,BP神经网络预测结果准确性更高,根据BP神经网络预测2023年为较轻灾年,从2019年开始地质灾害灾情年度等级有加重的趋势。

HVD分解和GA-BP神经网络结合的井架钢结构损伤识别

针对井架钢结构冲击载荷振动信号非线性、非平稳性对损伤识别的干扰问题,提出了一种基于希尔伯特振动分解(Hilbert Vibration Decomposition,HVD)与遗传算法优化的神经网络(Genetic BP Neural Networks,GA-BP)相结合的智能故障诊断方法。首先,利用HVD分解的方法处理冲击载荷作用下的加速度非平稳振动信号;其次,由斯皮尔曼相关系数选取HVD分解后的最优(Intrinsic Mode Function,IMF)分量,以最优IMF分量能量变化率构造特征向量;最后,通过特征向量建立数据集进行神经网络训练,完成信号的特征学习和故障分类。利用ZJ70型井架钢结构模型进行冲击载荷作用下的单处损伤和多处损伤的不同工况实验验证,结果表明:对于单处损伤位置识别率达到90%,多处损伤位置识别率高达96%,利用HVD分解与GA-BP神经网络相结合的方法具有较好的稳定性,能够准确判断出井架钢结构损伤位置,具有一定的实际应用价值。

基于专利合作网络的弱链接效应研究

合作研发能够促进创新要素的流动与分享,被普遍认为是提升企业创新效率的有效途径。现有研究关于合作与技术创新绩效的讨论通常局限于研发主体层面,而且仅聚焦于单个研发机构在合作网络中的节点属性特征而忽略了其链路特征。受社会网络弱链接理论启发,本文基于生物医药领域2015年及之前的24017条合作专利构建逐年合作网络,探究专利合作网络中的弱链接效应。以每个合作专利为研究对象,首先,计算每对合作机构在此前合作网络中的链路强度指标,并据此区分强弱链接。其次,将链路状态和链路强度作为解释变量,将专利影响力、颠覆性和市场价值作为被解释变量,采用回归分析研究合作关系强弱对专利创新绩效的影响。从描述性统计结果来看,生物制药领域中弱链接合作比例逐年降低,位于各创新绩效指标前25%的弱链接专利表现均略高于强链接专利。控制相关变量后,回归结果显示,链路状态与链路强度对专利颠覆性均有显著负向影响,而对专利影响力和专利市场价值则有显著正向效应。这表明生物制药领域的弱链接合作有利于提升专利颠覆性、突破技术瓶颈,但难以被现有技术体系所接受,在推向市场过程中存在阻力。相反地,只有建立稳固的强链接合作关系才能使合作产出具备实际应用价值,提高技术影响力和市场价值。

基于仿生算法联合优化BP的燃煤发热量预测

【目的】燃煤发热量的精准预测和评价是煤质分析和热工计算的重要基础,目前神经网络预测燃煤发热量的模型虽能有效拟合非线性关系,但存在易陷入局部最小值、收敛速度慢等问题。【方法】为精准预测煤炭在工业锅炉燃烧过程中的发热量,提出一种由仿生算法FA-GA联合优化BP神经网络的燃煤发热量预测方法。将774组燃煤锅炉常用煤的工业分析及元素分析数据进行预处理,根据平均影响值对煤质指标进行特征变量筛选,最终建立FA-GA-BP的发热量预测模型,并从误差评价指标、迭代次数等方面对优化算法寻优能力和模型预测精度进行了检验。【结果】经过特征变量筛选后模型的预测精度提升至0.956 1;FA-GA联合算法与单一优化算法FA、GA、PSO相比,迭代次数显著减少,算法的全局搜索能力得到有效提升;FA-GA-BP模型与单一优化模型FA-BP、GA-BP、PSO-BP以及目前常用的发热量模型MLR和SVR相比,精度更高,相关系数可达0.984 5.【结论】FA-GA算法优化BP模型,针对燃煤锅炉中来自不同地区、不同煤种的发热量预测具有良好的效果,在理论上满足了工业误差要求。改进后的燃煤发热量预测模型可为有效监测入炉煤质实时变化提供一种新方法。

考虑双维波动性的地铁冲击负荷网储协同平抑策略

地铁列车频繁启停使其牵引负荷出现短时间大幅度的冲击,容易导致变压器绝缘加速老化、引发主变过载风险。针对这一问题,本文提出一种协同网储的地铁负荷冲击优化策略。首先,基于地铁负荷时序特性剖析冲击性负荷形成机理,建立考虑功率曲线特征的双维波动性指标,定量描述冲击程度。其次,分别以系统经济性最优与负荷冲击最小为上下层目标,建立网架拓扑与储能装置协调控制的双层优化模型,求解最优开关变动及储能调度策略。最后,以上海某地铁线路实际供电负荷为例,结合多场景进行验证分析,结果表明所提方法能有效平抑冲击性负荷,实现供电可靠性与经济性的提升。

复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析

建立了一种复合材料蜂窝夹芯结构低速冲击后压缩强度的可靠性与灵敏度分析方法。利用ABAQUS有限元分析软件和VUMAT子程序建立了蜂窝夹芯结构冲击后压缩渐进损伤失效分析模型,并通过试验验证模型的有效性;在此基础上,利用Python语言对模型中材料力学性能和面板厚度、蜂窝芯子厚度进行参数化;采用径向基神经网络代理模型替代渐进损伤失效分析模型;基于蒙特卡洛法进行冲击后压缩强度的可靠性分析;分别采用基于方差和基于失效概率的方法进行参数的灵敏度分析,并研究参数的变异系数对结构可靠性的影响。结果表明:在外载荷低于10000 N,结构失效概率小于0.00017的情况下,当外载荷达到12700 N时,结构失效概率达到0.9;面板的力学性能、面板厚度、蜂窝芯厚度对冲击后压缩强度的影响较大;冲击后压缩强度的变异系数随着参数变异系数的增大而增大。