检索结果-南通市图书馆

Modelling method of inter-building movement for campus-scale occupancy simulation:A case study

第三届中国卫星导航学术年会

作者： Lei WANG, Jiming GUO, Lili SHENSchool of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan,China

Tropospheric path delay would be one of main error source in medium and long distance baseline processing. Due to complexity of Troposphere variation, it is very hard to model the troposphere delay;the most commonly used method is estimate tropospheric path delay residuals of correction model during data processing. In this paper, Kalman filter was used in relative positioning;meanwhile, troposphere wet path delay residuals were estimated with stochastic process method. The influence of different pre-fit constraint on troposphere delay estimation was discussed;impact of troposphere wet delay residuals on relative positioning was also presented.

关键词： Relative Positioning Tropospheric Delay Estimation stochastic process Kalman Filter

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

Building Simulation 2023年第3期16卷 461-481页

作者： Mingya Zhu Yiqun Pan Zejun Wu Zhizhong Huang Risto Kosonen School of Mechanical Engineering Tongji UniversityShanghaiChina Sino-German College of Applied Sciences Tongji UniversityShanghaiChina Department of Mechanical Engineering Aalto UniversityEspooFinland College of Urban Construction Nanjing Tech UniversityNanjingChina

As an important factor in the investigation of building energy consumption,occupant behavior(OB)has been widely studied on the building level.However so far,studies of OB modelling on the district scale remain limited.Indeed,district-scale OB modelling has been facing the challenges from the scarcity of district-scale data,modelling methods,as well as simulation application.This study initiates the extrapolation of occupancy modelling methodology from building level to district scale through proposing modelling methods of inter-building movements.The proposed modelling methods utilize multiple distribution fittings and Bayesian network to upscale the event description methods from inter-zone movement events at the building level to inter-building movement events at the district level.This study provides a framework on the application of the proposed modelling methods for a university campus in the suburbs of Shanghai,taking advantages of data sensing,monitoring and survey techniques.With the collected campus-scale occupancy data,this paper defines five patterns of inter-building movement.One pattern represents the dominated inter-building movement events for one kind of students in their daily campus life.Based on the quantitative descriptions for various inter-building movement events,this study performs the stochastic simulation for the campus district,using Markov chain models.The simulation results are then validated with the campus-scale occupancy measurement data.Furthermore,the impact of inter-building movement modelling methods on building energy demand is evaluated for the library building,taking the deterministic occupancy schedules suggested by current building design standard as a baseline.

关键词： occupancy modelling event description inter-building movement stochastic process transition probability campus buildings data acquisition

Disturbance-level-dependent post-disturbance succession in a Eurasian steppe

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Life Sciences) 2022年第1期65卷 142-150页

作者： Junjie Yang Minjie Xu Shuang Pang Lili Gao Zijia Zhang Zhiping Wang Yunhai Zhang Xingguo Han Ximei Zhang State Key Laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of SciencesBeijing 100093China Key Laboratory of Dryland Agriculture Ministry of AgricultureInstitute of Environment and Sustainable Development in AgricultureChinese Academy of Agricultural SciencesBeijing 100081China

Anthropogenic disturbances may decrease as we take measures to control them.However,the patterns and mechanisms of postdisturbance ecosystem succession have rarely been studied.Here we reported that disturbance level determined the importance of stochastic relative to deterministic changes in ecosystem components(plant community composition,soil microbial community composition,and soil physicochemical indices),and thus predefined the pattern of post-disturbance ecosystem succession.We proposed a theoretical framework with five disturbance levels corresponding to distinct succession patterns.We conducted a nitrogen addition experiment in a temperate steppe,monitored these ecosystem components during"disturbance"treatment(2010-2014)and post-treatment"succession"(2014-2018).The disturbance level experienced by each component in each treatment was inferred by fitting the observed succession patterns into the theoretical framework.The mean disturbance level of these components was found to increase quadratically with nitrogen addition rate.This was because increasing nitrogen addition reduced the importance of stochastic relative to deterministic changes in these components,and these changes had a quadratic relationship with disturbance level.Overall,our results suggested that by monitoring the importance of stochastic relative to deterministic changes in an ecosystem,we can estimate disturbance levels and predict succession patterns,as well as propose disturbance-level-dependent strategies for post-disturbance restoration.

关键词： disturbance grassland microbial diversity nitrogen deposition restoration stochastic process succession

A Probabilistic Framework for Temporal Cognitive Diagnosis in Online Learning Systems

在线全文

学校读者我要写书评

暂无评论

Journal of Computer Science & Technology 2023年第6期38卷 1203-1222页

作者：刘嘉聿汪飞马海平黄振亚刘淇陈恩红苏喻 School of Data Science University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Cognitive Intelligence Hefei 230088China Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of China Hefei 230026China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China School of Computer Science and Artificial Intelligence Hefei Normal UniversityHefei 230061China

Cognitive diagnosis is an important issue of intelligent education systems,which aims to estimate students'proficiency on specific knowledge concepts.Most existing studies rely on the assumption of static student states and ig-nore the dynamics of proficiency in the learning process,which makes them unsuitable for online learning scenarios.In this paper,we propose a unified temporal item response theory(UTIRT)framework,incorporating temporality and random-ness of proficiency evolving to get both accurate and interpretable diagnosis results.Specifically,we hypothesize that stu-dents'proficiency varies as a Wiener process and describe a probabilistic graphical model in UTIRT to consider temporali-ty and randomness factors.Furthermore,based on the relationship between student states and exercising answers,we hy-pothesize that the answering result at time k contributes most to inferring a student's proficiency at time k,which also re-flects the temporality aspect and enables us to get analytical maximization(M-step)in the expectation maximization(EM)algorithm when estimating model parameters.Our UTIRT is a framework containing unified training and inferenc-ing methods,and is general to cover several typical traditional models such as Item Response Theory(IRT),multidimen-sional IRT(MIRT),and temporal IRT(TIRT).Extensive experimental results on real-world datasets show the effective-ness of UTIRT and prove its superiority in leveraging temporality theoretically and practically over TIRT.

关键词： cognitive diagnosis probabilistic graphical model item response theory(IRT) stochastic process expectation maximization(EM)algorithm

Automatic modeling algorithm of stochastic error for inertial sensors

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Control Theory and Technology 2024年第1期22卷 81-91页

作者： Luodi Zhao Long Zhao School of Automation Science and Electrical Engineering Beihang UniversityBeijing100191China Digital Navigation Center Beihang UniversityBeijing100191China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing100191China

This paper proposes an automatic algorithm to determine the properties of stochastic processes and their parameters for inertial error. The proposed approach is based on a recently developed method called the generalized method of wavelet moments (GMWM), whose estimator was proven to be consistent and asymptotically normally distributed. This algorithm is suitable mainly (but not only) for the combination of several stochastic processes, where the model identification and parameter estimation are quite difficult for the traditional methods, such as the Allan variance and the power spectral density analysis. This algorithm further explores the complete stochastic error models and the candidate model ranking criterion to realize automatic model identification and determination. The best model is selected by making the trade-off between the model accuracy and the model complexity. The validation of this approach is verified by practical examples of model selection for MEMS-IMUs (micro-electro-mechanical system inertial measurement units) in varying dynamic conditions.

关键词： GMWM stochastic process Inertial sensor Sensor calibration Error model Allan variance

Grey-based approach for estimating software reliability under nonhomogeneous Poisson process

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2022年第2期33卷 360-369页

作者： LIU Xiaomei XIE Naiming College of Economics and Management Nanjing University of Aeronautics and AstronauticsNanjing 211106China College of Science Jiujiang UniversityJiujiang 332005China

Due to the randomness and time dependence of the factors affecting software reliability, most software reliability models are treated as stochastic processes, and the non-homogeneous Poisson process(NHPP) is the most used one.However, the failure behavior of software does not follow the NHPP in a statistically rigorous manner, and the pure random method might be not enough to describe the software failure behavior. To solve these problems, this paper proposes a new integrated approach that combines stochastic process and grey system theory to describe the failure behavior of software. A grey NHPP software reliability model is put forward in a discrete form, and a grey-based approach for estimating software reliability under the NHPP is proposed as a nonlinear multi-objective programming problem. Finally, four grey NHPP software reliability models are applied to four real datasets, the dynamic R-square and predictive relative error are calculated. Comparing with the original single NHPP software reliability model, it is found that the modeling using the integrated approach has a higher prediction accuracy of software reliability. Therefore, there is the characteristics of grey uncertain information in the NHPP software reliability models, and exploiting the latent grey uncertain information might lead to more accurate software reliability estimation.

关键词： software reliability model stochastic process uncertainty system non-homogeneous Poisson process grey system theory

stochasticity dominates assembly processes of soil nematode metacommunities on three Asian mountains

在线全文

学校读者我要写书评

暂无评论

Pedosphere 2023年第2期33卷 331-342页

作者： Shuqi ZOU Jonathan ADAMS Zhi YU Nan LI Dorsaf KERFAHI Binu TRIPATHI Changbae LEE Teng YANG Itumeleng MOROENYANE Xing CHEN Jinsoo KIM Hyun Jeong KWAK Matthew Chidozie OGWU Sang-Seob LEE Ke DONG Department of Integrative Biotechnology Sungkyunkwan University300 Chuncheon-DongSuwon 16419(Korea) School of Geographic and Oceanographic Sciences Nanjing UniversityNanjing 210008(China) Key laboratory of Ministry of Education for Environment Change and Resources Use in Beibu Gulf Guangxi Key Laboratory of Earth Surface Processes and Intelligent SimulationNanning Normal University175 East Mingxiu RoadNanning 530001(China) School of Natural Sciences Department of Biological SciencesKeimyung UniversityDaegu 42601(Korea) Korea Polar Research Institute Incheon 21990(Korea) Department of Forestry Environment and SystemsKookmin UniversitySeoul 02707(Korea) State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of Sciences71 East Beijing RoadNanjing 210008(China) Institut National Recherche Scientifique Institut Armand-Frappier SantéBiotechnologie531 Boulevard des PrairiesLaval H7V1B7(Canada) College of Life Science and Technology Guangxi University100 Daxue RoadNanning 530004(China) Department of Biological Sciences Kyonggi University154-42 Gwanggyosan-roYeongtong-guSuwon-siGyeonggi-do 16227(Korea) School of Biological Sciences Seoul National University1 Gwanak-roSeoul 08826(Korea)

Nematodes play an important role in ecosystems;however,very little is known about their assembly processes and the factors influencing them.We studied nematode communities in bulk soils from three Asian mountain ecosystems to determine the assembly processes of free-living nematode metacommunities and their driving factors.On each mountain,elevations span a range of climatic conditions with the potential to reveal assembly processes that predominate across multiple biomes.A phylogenetic null modeling framework was used to analyze 18S rRNA gene amplicons to quantify various assembly processes.We found that phylogenetic turnover between nematode communities on all mountains was dominated by stochastic processes,with“undominated processes”being the most predominant stochastic factor.Elevation has a significant impact on the relative importance of deterministic and stochastic processes.A variety of climatic and edaphic variables significantly influenced the variations in community assembly processes with elevation,even though their impacts were not consistent between the mountains.Overall,our results indicate that free-living nematode metacommunities in a wide range of environments are largely structured by stochastic processes rather than by niche-based deterministic processes,suggesting that metacommunities of soil free-living nematodes may respond to climate change in a largely unpredictable way.

关键词： climate change ecological drift elevation gradient environmental stress stochastic process

Generalized degradation reliability model considering phase transition

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2022年第3期33卷 748-758页

作者： ZHANG Ao WANG Zhihua WU Qiong LIU Chengrui School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China Institute of Spacecraft System Engineering China Academy of Space TechnologyBeijing 100094China Beijing Institute of Control Engineering Beijing 100094China

Aiming to evaluate the reliability of phase-transition degrading systems,a generalized stochastic degradation model with phase transition is constructed,and the corresponding analytical reliability function is formulated under the concept of the first hitting time.The phase-varying stochastic property and the phase-varying nonlinearity are considered simultaneously in the proposed model.To capture the phase-varying stochastic pro-perty,a Wiener process is adopted to model the non-monotonous degradation phase,while a Gamma process is utilized to model the monotonous one.In addition,the phase-varying non-linearity is captured by different transformed time scale functions.To facilitate the practical application of the proposed model,identification of phase model type and estimation of model parameters are discussed,and the initial guesses for parameters optimization are also given.Based on the constructed model,two simulation studies are carried out to verify the analytical reliability function and analyze the influence of model misspecification.Finally,a practical case study is conducted for illustration.

关键词： degradation phase transition reliability stochastic process nonlinearity

stochastic dynamic simulation of railway vehicles collision using data-driven modelling approach

在线全文

学校读者我要写书评

暂无评论

Railway Engineering Science 2022年第4期30卷 512-531页

作者： ShaodiDong Zhao Tang Michelle Wu Jianjun Zhang State Key Laboratory of Traction Power Southwest Jiaotong UniversityChengdu 610031China National Centre for Computer Animation Bournemouth UniversityDorsetUK

Using stochastic dynamic simulation for railway vehicle collision still faces many challenges,such as high modelling complexity and time-consuming.To address the challenges,we introduce a novel data-driven stochastic process modelling(DSPM)approach into dynamic simulation of the railway vehicle collision.This DSPM approach consists of two steps:(i)process description,four kinds of kernels are used to describe the uncertainty inherent in collision processes;(ii)solving,stochastic variational inferences and mini-batch algorithms can then be used to accelerate computations of stochastic processes.By applying DSPM,Gaussian process regression(GPR)and finite element(FE)methods to two collision scenarios(i.***.lead car colliding with a rigid wall,and the lead car colliding with another lead car),we are able to achieve a comprehensive analysis.The comparison between the DSPM approach and the FE method revealed that the DSPM approach is capable of calculating the corresponding confidence interval,simultaneously improving the overall computational efficiency.Comparing the DSPM approach with the GPR method indicates that the DSPM approach has the ability to accurately describe the dynamic response under unknown conditions.Overall,this research demonstrates the feasibility and usability of the proposed DSPM approach for stochastic dynamics simulation of the railway vehicle collision.

关键词： Dynamic simulation Railway vehicle collision stochastic process Data-driven stochastic process modelling