基于随机系数Logit模型的专利价值评估研究——以主动降噪技术为例

[研究目的]从分析专利价值入手,通过经济学研究方法围绕专利侵权损害赔偿的标准进行定量研究,为评估专利价值提供有意义的知识增量。[研究方法]基于实证产业组织理论,采用随机系数Logit模型,以无线蓝牙耳机主动降噪(ANC)技术作为研究对象,构建该技术遭受侵权的反事实情形来估计经济指标变化,由此评估专利价值及侵权赔偿比例。[研究结论]专利侵权企业的行为产生了反竞争效应,提升了企业垄断势力,挤占了其他耳机企业的生存空间,也对潜在进入企业形成了进入威胁。蓝牙耳机价格中约有4.06%源于ANC专利标识。如果发生ANC专利侵权,赔偿额度应是侵权企业利润的2.6~2.8倍。该方法利用市场数据在均衡框架下评估专利价值,为相关研究提供了新方向。

Farmers' Willingness on Organic Fertilizer Application Based on Logit Model and Influencing Factors——A case of Shandong Province

[Objective] The matter of chemical fertilizer being overused but organic fertilizer being deficiently used causes environment pollution and soil fertility degradation and holds back agricultural sustainable development in China at present.[Method] A survey of 200 farmers selected from Shandong province was conducted in 2008 to identify the factors influencing farmers willingness to use organic fertilizer.[Result] Logit model results showed that the proportion of non-farm income in total income,awareness of...

基于Logit模型的技术供需交易影响因素分析

将技术供方和专利视为整体,将供需双方是否通过某专利交易视为被解释变量,系统研究技术特征、组织实力和供需方多维邻近关系等对技术交易的影响。基于Logit模型对燃料电池领域专利数据实证研究发现:(1)考虑三维特征建立Logit模型,对交易形成预测的精度高达83.3%;(2)技术特征、组织实力特征、多维邻近特征对技术交易均有显著正向影响;(3)多维邻近特征对技术交易的促进程度远高于其他维度特征,供需双方信任是交易形成的关键因素。最后,从建立高质量技术供需数据库、技术交易信任体系、技术交易网络及交易推荐机制等方面提出对策思考。

拥挤信息下基于Logit模型的公共交通 方式选择行为研究

人们对出行方式的舒适性要求越来越高,出行信息能为出行者提供有效帮助。采用正交试验对公共交通方式选择特性变量进行情景组合设计,并结合公共交通出行特征进行问卷调查设计,对提供拥挤信息条件下出行者对公共交通方式选择意愿进行调查,据此建立公共交通方式选择Logit模型。结果表明,拥挤信息对公共交通方式选择有显著影响,对公交出行选择影响较大。

基于随机参数logit的山区高速公路事故严重程度研究

为了探究平曲线、纵曲线、平纵组合线形对山区高速公路交通事故严重程度的影响,首先,统计分析某山区高速公路263 km路段的线形数据和该路段5年内发生的1870起事故,并将其分类;然后,根据调研数据的结构形式,建立随机参数logit模型,进而利用该模型研究组合线形对事故严重程度的影响。结果表明:曲线比例(ROC)、加权曲率(CW)、单元坡度差(ΔS_(2))等因素与仅财产损失事故增加相关,而坡长组合(CSL)与仅财产损失事故减少相关;加权曲率(CW=0.6~0.7)和连续上坡与轻伤事故的事故增加相关,加权曲率(CW=0.3~0.4)、单元坡度差(ΔS_(1))、曲线比例(ROC)等因素与轻伤事故减少相关;曲率变化率(VRC)、单元半径比(CRF,CRB)、弯坡组合(CSR)等因素与重伤或死亡事故增加相关,曲线比例(ROC)与重伤或死亡事故减少相关;组合线形对事故严重程度有着显著影响。

基于Ordered Logit模型的民办高校科研成果转化影响因素研究

为研究民办高校科研成果转化影响因素,在专家访谈和实地调研的基础上,对K高校、C高校、B高校、Z高校等民办高校教师发放调查问卷收集数据,应用Ordered Logit模型对其影响因素进行了实证分析。分析发现,科研经费支持力度与科研成果数量之间呈正相关关系,高校科研平台设置与服务地方经济建设之间呈正相关关系,高校科研管理制度与科研成果转化成效之间呈正相关关系。由此得出结论:我国民办高校科研成果转化与服务地方经济能力有待提升,民办高校科研成果转化的金融支持不够灵活、公共服务平台不够健全,完善民办高校科研管理制度是提高科研成果转化效率的重要保障。

应用累积比数logit模型和偏比例优势模型分析肺癌手术患者住院费用影响因素

目的阐明累积比数logit模型和偏比例优势模型在有序分类资料中的应用。方法以肺癌手术住院费用的相关因素分析为例,采用累积比数logit模型和偏比例优势模型对肺癌手术住院费用与各相关因素关系进行拟合,通过模型的对数似然值(-2ln L)判断2种模型拟合的优度。结果在自变量不全满足比例优势假定条件时(性别χ^(2)=15.888,P<0.001;手术术式χ^(2)=35.874,P<0.001),2种分析方法拟合结果不同。在不同分割点,住院费用与手术术式关系的差别较大。偏比例优势模型(-2ln L=5797.112)优于累积比数logit模型(-2ln L=5852.420),差异具有统计学意义(P<0.05)。结论有序分类资料的分析,首先应进行比例优势假定条件验证,如果自变量均满足该条件,选择累积比数logit模型,否则采用偏比例优势模型拟合。

基于Logit模型的教育评估系统构建及应用分析

针对现有教育评估模型评价指标覆盖面小、评估精度不足等问题,文中提出构建基于Logit模型的教育评估系统。首先根据评估的对象和范围,将教育评估体系分为四类,再根据目标导向等原则设计评估指标体系;随后,对数据进行预处理,并对自变量进行赋值操作,使其更贴合建模要求;最后基于Logit模型构建教育评估及成绩预测系统。将文中所提模型应用于浙江一所高中进行实证,结果表明,基于Logit模型的教育评估系统具有较好的应用效果,能够评估指标和影响因素同教学评估结果之间的关系,并提供科学的评估和预测结果。

A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.

中国居民收入与家庭碳达峰:基于CGSS数据与多项Logit模型

基于2015年和2018年CGSS家庭微观数据,构建多项Logit模型,实证检验居民收入对家庭碳达峰偏离度的影响。研究发现:居民收入增长对家庭直接碳达峰偏离度和间接碳达峰偏离度均产生显著的促进作用,进而提升家庭部门碳达峰偏离度,且家庭碳达峰偏离水平越低,收入增长产生影响的可能性就越小。异质性分析表明,中西部地区家庭的低碳消费模式较为稳定,东部地区则需关注高碳排放风险,且教育水平提升能够缓解因居民收入增长带来的家庭碳达峰偏离度提升问题。因此,我国政府应引导培养家庭节约集约的绿色生活观念,以推动家庭消费绿色低碳转型和碳达峰碳中和目标的实现。

零膨胀有序logit模型和传统模型在零膨胀等级资料分析中的比较研究

目的对零膨胀有序logit模型展开应用并和传统模型进行比较,探讨其优势和局限性。方法对各自变量进行单因素分析并计算相应的对数似然值、AIC及BIC等模型评价指标,根据这些指标结果依次纳入各自变量并组成不同的自变量集。分别使用有序logit模型、广义有序logit模型和零膨胀有序logit模型基于不同自变量集进行数据拟合,通过比较不同情况下各模型的评价指标及参数估计结果对模型进行评价。结果根据模型评价指标,零膨胀有序logit模型对数据的拟合效果优于其他两种模型。零膨胀有序logit模型对不同自变量集进行拟合时,其参数估计结果高度一致。不同模型的参数估计结果存在一定的差异。结论零膨胀有序logit模型在应用时有着较好的性能。单因素分析的模型评价指标可以用来帮助筛选使得模型性能最优的自变量集。

Impact of Labor Transfer on Agricultural Land Use Conversion at Rural Household Level Based on Logit Model

Since land and labor force are primary resources to be used and controlled by rural households, the allocation of labor forces will influence land uses, and further lead to land use conversion. The present study used the Binary Logit model to investigate the influence of labor force transfer, characteristics of rural households, location, and land market on agricultural land use conversion at rural household level. This study was conducted based on 329 valid questionnaires, which were obtained in Changshu, Rudong, and Tongshan counties, respectively representing the southern, middle and northern areas of Jiangsu Province. The results showed that land market participation, location, zonal difference and labor transfer had strong influences on agricultural land use conversion. The participation of land market had a strong positive effect on land use conversion, especially for the farmland converted to the fishpond. The nearer to the county seat, the more conversion of land use occurred. Particularly, the labor force transfer caused by wage employment decreased this conversion probability, while the labor transfer caused by self-employment led to more conversion; and the increasing of income from labor transfer increased the conversion. Moreover, land use con- versions demonstrated zonal difference, which were more in Rudong and Changshu counties than in Tongshan County, and the factors influencing this conversion were different in the three regions.

农业适度规模经营主体融资意愿及其影响因素研究--基于Logit模型的天津118份调研样本的实证分析

农业适度规模经营主体是带动农业农村现代化、助力乡村全面振兴的主要动能,在未来一定时期内,农业适度规模经营主体在运营中仍面临资金约束的问题,因此需要拓展其融资渠道。本文基于对天津市118份农业适度规模经营主体的调研数据,从融资意愿方面,运用Logit模型分析了影响其融资的主要因素。结果表明,农业适度规模经营主体的融资需求较强,不同的组织形式和经营规模的主体在融资需求上存在显著差异,并且存在融资渠道单一的问题。另外,农业适度规模经营主体的经营者年龄、人员规模、年经营收入和资金需求、经营者对农业融资政策的了解程度、金融机构利率水平等均对其融资意愿产生关键影响。基于实证分析结果,结合实地走访调研资料,本文提出改善经营人员知识结构、提高主体发展水平、优化农业信贷产品等缓释农业适度规模经营主体融资约束的政策建议。

A comparison of model choice strategies for logistic regression

Purpose:The purpose of this study is to develop and compare model choice strategies in context of logistic regression.Model choice means the choice of the covariates to be included in the model.Design/methodology/approach:The study is based on Monte Carlo simulations.The methods are compared in terms of three measures of accuracy:specificity and two kinds of sensitivity.A loss function combining sensitivity and specificity is introduced and used for a final comparison.Findings:The choice of method depends on how much the users emphasize sensitivity against specificity.It also depends on the sample size.For a typical logistic regression setting with a moderate sample size and a small to moderate effect size,either BIC,BICc or Lasso seems to be optimal.Research limitations:Numerical simulations cannot cover the whole range of data-generating processes occurring with real-world data.Thus,more simulations are needed.Practical implications:Researchers can refer to these results if they believe that their data-generating process is somewhat similar to some of the scenarios presented in this paper.Alternatively,they could run their own simulations and calculate the loss function.Originality/value:This is a systematic comparison of model choice algorithms and heuristics in context of logistic regression.The distinction between two types of sensitivity and a comparison based on a loss function are methodological novelties.

基于混合Logit模型的仙女山国家森林公园游客行为的影响因素研究

研究森林公园的游客行为特征及影响因素,有助于促进当地的旅游发展,推动经济可持续增长,为森林公园的高质量发展提供研究基础。以仙女山国家森林公园为例,通过实地调查获取游客的社会经济特征、态度量表及行为特征,运用S-O-R框架构建森林公园游客的行为特征分析框架,利用MIMIC模型拟合行为特征分析框架,引入混合Logit模型探索社会经济特征和态度变量对游客行为的影响。结果表明:(1)仙女山国家森林公园以市内游客为主,多以陪伴家人、休闲度假为主要动机。(2)研究证实了构建的行为分析框架对森林公园游客的行为具有解释效力。(3)各变量对旅游行为的影响依次为主体认知(-0.278)>主体选择(-0.160)>旅游地条件(0.204)>主体感受(0.373)。

Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

Energy-optimal DNN model placement in UAV-enabled edge computing networks

Unmanned aerial vehicle(UAV)-enabled edge computing is emerging as a potential enabler for Artificial Intelligence of Things(AIoT)in the forthcoming sixth-generation(6G)communication networks.With the use of flexible UAVs,massive sensing data is gathered and processed promptly without considering geographical locations.Deep neural networks(DNNs)are becoming a driving force to extract valuable information from sensing data.However,the lightweight servers installed on UAVs are not able to meet the extremely high requirements of inference tasks due to the limited battery capacities of UAVs.In this work,we investigate a DNN model placement problem for AIoT applications,where the trained DNN models are selected and placed on UAVs to execute inference tasks locally.It is impractical to obtain future DNN model request profiles and system operation states in UAV-enabled edge computing.The Lyapunov optimization technique is leveraged for the proposed DNN model placement problem.Based on the observed system overview,an advanced online placement(AOP)algorithm is developed to solve the transformed problem in each time slot,which can reduce DNN model transmission delay and disk I/O energy cost simultaneously while keeping the input data queues stable.Finally,extensive simulations are provided to depict the effectiveness of the AOP algorithm.The numerical results demonstrate that the AOP algorithm can reduce 18.14%of the model placement cost and 29.89%of the input data queue backlog on average by comparing it with benchmark algorithms.

Logit模型的前世与今生

分类问题贯穿了统计学三百余年的发展进程,是统计中基础且重要的问题.许多统计模型被统计学家们创造并运用在分类中,作为分类方法的一种,Logit模型在机器学习、经济预测、数据挖掘、疾病诊断等领域发挥重要的作用.本文将主要介绍该模型起源、发展的故事,以及该模型在当下的用武之地.

基于多项Logit模型的山区高速公路事故致因分析

为分析山区高速长大下坡路段事故严重程度的影响因素,首先对地处陕西省、广西壮族自治区、云南省的典型山区高速公路长大下坡路段的道路交通事故数据进行深度调研,共获取2559条事故数据,然后基于上述事故数据,构建了多项Logit事故严重程度模型,对导致山区高速长大下坡路段交通事故的直接致因进行了分析。分析结果表明:肇事驾驶人超速行驶、违法装载超限、疲劳驾驶、操作不当、违法停车、车辆制动失效对山区高速长大下坡路段伤亡事故有显著影响。研究结果为改善山区公路的运营安全性,从根本上寻求已建成山区高速公路事故频发的有效办法提供了方向。

基于Logit原理的出租车载客选择策略研究

针对机场出租车司机排队载客还是空驶返回市区两种选择行为进行分析,研究影响出租车司机决选择策的相关因素机理,基于Logit原理建立出租车和乘客选择决策模型;然后算出两种选择下的出租车司机的收益,通过收益差异得出司机的合理决策,进而采用旅客和司机等待时间最短作为最好乘车效率的主要依据,给出上车点的最佳位置。