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Dynamic train dwell time forecasting:a hybrid approach to address the influence of passenger flow fluctuations

Railway engineering Science 2023年第4期31卷 351-369页

作者： Zishuai Pang Liwen Wang Shengjie Wang Li Li Qiyuan Peng School of Transportation and Logistics Southwest Jiaotong UniversityChengdu 610031China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong UniversityChengdu 610031China

Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between *** estimation of these factors is essential to decision-making for train delay reduction,train dispatching,and station capacity *** the present study,we aim to propose a train dwell time model based on an averaging mechanism and dynamic updating to address the challenges in the train dwell time prediction problem(e.g.,dynamics over time,heavy-tailed distribution of data,and spatiotemporal relationships of factors)for real-time train *** averaging mechanism in the present study is based on multiple state-of-the-art base predictors,enabling the proposed model to integrate the advantages of the base predictors in addressing the challenges in terms of data attributes and data ***,considering the influence of passenger flow on train dwell time,we use a dynamic updating method based on exponential smoothing to improve the performance of the proposed method by considering the real-time passenger amount fluctuations(e.g.,passenger soars in peak hours or passenger plunges during regular periods).We conduct experiments with the train operation data and passenger flow data from the Chinese high-speed railway *** results show that due to the advantages over the base predictors,the averaging mechanism can more accurately predict the dwell time at stations than its counterparts for different prediction horizons regarding predictive errors and ***,the experimental results show that dynamic smoothing can significantly improve the accuracy of the proposed model during passenger amount changes,i.e.,15.4%and 15.5%corresponding to the mean absolute error and root mean square error,*** on the proposed predictor,a feature importance analysis shows that the planned dwell time and arrival delay are the two most important factors to dwell ***,planned time has positive influen

关键词： Train operations Dwell time Passenger flow Averaging mechanism Dynamic smoothing

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Immobilized ZnO based nanostructures and their environmental applications

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Progress in Natural Science:Materials International 2021年第6期31卷 821-834页

作者： Wei Gaoa Yangsi Liu Junzhe Dong Department of Chemical and Materials Engineering The University of Auckland Key Laboratory of Advanced Functional Materials Ministry of Education Faculty of Materials and Manufacturing Beijing University of Technology National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing Guyue New Materials Research Institute Beijing University of Technology

In the research of semiconductor metal oxides, zinc oxide(ZnO) nanomaterials have been committed to design and exploration because of their unique physical and chemical properties. ZnO has many structural characteristics and has considerable practical applications in the field of environmental technology. However, ZnO nanomaterials used for environmental functions are often presented in the form of powders. After use, they need to go through recovery processes such as centrifugation and filtration, which is also easy to cause secondary *** above problems can be avoided by fixing ZnO nanostructures on substrates to form easily movable ***, we present a review of our work and some others on the different synthetic strategies, formation mechanism, modification, performance and diversifications of immobilized ZnO based nanostructures, and highlight their photocatalytic related activities for environmental remediation. Various immobilized ZnO based nanostructures including nanorod arrays, 3D nanostructures, and composite heterostructures have been focused. We hope it may serve as a useful reference for researchers interested in immobilized semiconductor nanostructures and their photocatalysis and other environmental applications.

关键词： ZnO Nanostructure Immobilization Photocatalysis Environmental application

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Detection of scab in wheat ears using in situ hyperspectral data and support vector machine optimized by genetic algorithm

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International Journal of Agricultural and Biological engineering 2020年第2期13卷 182-188页

作者： Linsheng Huang Hansu Zhang Chao Ruan Wenjiang Huang Tingguang Hu Jinling Zhao National Engineering Research Center for Agro-Ecological Big Data Analysis&Application Anhui UniversityHefeiChina Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina

A new method was proposed to extract sensitive features and to construct a monitoring model for wheat scab based on in situ hyperspectral data of wheat ears to achieve effective prevention and control and provide theoretical support for its large-scale *** sensitive features were selected through correlation analysis and wavelet *** features were as follows:three original bands of 350-400 nm,500-600 nm,and 720-1000 nm;three vegetation indices of modified simple ratio(MSR),normalized difference vegetation index,and structural independent pigment index;and two wavelet features of WF01 and *** combining the selected sensitive features with support vector machine(SVM)and SVM optimized by genetic algorithm(GASVM),a total of 16 monitoring models were built,and the monitoring accuracies of the two types of models were *** ability of the monitoring models built by GASVM to identify scab was better than that of SVM algorithm under the same characteristic *** the 16 models,MSR combined with GASVM had an overall accuracy of 75%and a Kappa coefficient of *** can be used to monitor wheat scab and its application can improve the accuracy of disease monitoring.

关键词： wheat scab hyperspectral data correlation analysis genetic algorithm wavelet transform support vector machine

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An improved cellular automata model of traffic flow with look-ahead potential

An improved cellular automata model of traffic flow with loo...

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2021 China Automation Congress, CAC 2021

作者： Ma, Xiao Liu, Yu-Hu School of Mathematics Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9781665426473

This paper presents an improved automata model for traffic flow based upon models for cellular automata and traffic flow. The proposed model is concerned with the headway and multiple velocities. The proposed model enforces the stochastic rules for moving a car on the basis of traffic in front of it. Rules for updating the velocity of car relies upon the location of the car as well as front traffic and their velocities. In particular, by using numerical simulations, the model proposed in this study can reach the steady-state more quickly for random perturbations. © 2021 IEEE

关键词： Cellular automata

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Prediction of high-speed train delay propagation based on causal text information

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Railway engineering Science 2023年第1期31卷 89-106页

作者： Qianyi Liu Shengjie Wang Zhongcan Li Li Li Jun Zhang Chao Wen National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong UniversityChengdu 610031China China Railway Chengdu Group Co. LtdChengdu 610031China

The delay-causing text data contain valuable information such as the specific reasons for the delay,location and time of the disturbance,which can provide an efficient support for the prediction of train delays and improve the guidance of train control *** on the train operation data and delay-causing data of the Wuhan-Guangzhou high-speed railway,the relevant algorithms in the natural language processing field are used to process the delay-causing text *** also integrates the train operatingenvironment information and delay-causing text information so as to develop a cause-based train delay propagation prediction *** Word2vec model is first used to vectorize the delay-causing text description after word *** mean model or the term frequency-inverse document frequency-weighted model is then used to generate the delay-causing sentence vector based on the original word ***,the train operating-environment features and delay-causing sentence vector are input into the extreme gradient boosting(XGBoost)regression algorithm to develop a delay propagation prediction *** this work,4 text feature processing methods and 8 regression algorithms are *** results demonstrate that the XGBoost regression algorithm has the highest prediction accuracy using the test features processed by the continuous bag of words and the mean *** with the prediction model that only considers the train-operating-environment features,the results show that the prediction accuracy of the model is significantly improved with multi-ple regression algorithms after integrating the delay-causing feature.

关键词： High-speed rail Delay propagation Cause of delay Word2vec Natural language processing

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Dynamic visual simulation of marine vector field based on LIC——a case study of surface wave field in typhoon condition

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Journal of Oceanology and Limnology 2019年第6期37卷 2025-2036页

作者： LIU Zhendong LIU Haixing SU Tianyun JIA Zhen LI Xinfang ZHOU Lin SONG Zhuanling First Institute of Oceanography(FIO) Ministry of Natural Resources(MNR)Qingdao 266061China Laboratory for Regional Oceanography and Numerical Modelling Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Qingdao 266061China

Line integral convolution(LIC)is a useful visualization technique for a vector ***,the output image produced by LIC has many problems in a marine vector *** focus on the visual quality improvement when LIC is applied in the ocean steady and unsteady flow field in the following *** a white noise is used as the input in a steady flow field,interpolation is used to turn the discrete white noise into continuous white noise to solve the problem of ***"cross"high-pass filtering is used to enhance the textures of streamlines to be more concentrated and continuity strengthened for each *** a sparse noise is used as the input in a steady flow field,we change the directions of background sparse noise according to the directions of vector field to make the streamlines clearer and *** addition,we provide a random initial phase for every streamline to avoid the pulsation effect during *** velocities of vector field are encoded in the speed of the same length streamlines so that the running speed of streamlines can express flow ***,to solve the problem of obvious boundaries when stitching image,we change the streamline tracking *** a white noise is used as an input in an unsteady flow field,double value scattering is used to enhance the contrast of streamlines;moreover,the"cross"high-pass filtering is also adopt instead of two-dimensional high-pass ***,we apply the above methods to a case of the surface wave field in typhoon *** experimental results show that applying the methods can generate high-quality wave images and ***,it is helpful to understand and study waves in typhoon condition to avoid the potential harm of the waves to people's lives and property.

关键词： line integral convolution(LIC) wave data visualization steady and unsteady marine flow field

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The research of forecasting model of automobile parts recycling cost based on data intelligence 2019

The research of forecasting model of automobile parts recycl...

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2019 International Conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2019

作者： Fan, Bo Cai, Yueshun School of Information Science and Technology Southwest Jiaotong University National Engineering Laboratory of Industrial Big-Data Application Technology CASIC ChengDu China

ISBN: (纸本)9781450372022

In view of the problem of reducing the cost control of the used parts in the after-sales service cost analysis process of the automobile enterprises, the multi-dimensional intelligent analysis of the used business data is carried out by extracting and cleaning the relevant business data resources of the used parts. This paper proposes a method based on data intelligence for cost forecasting, which assists enterprises in mining valuable information and knowledge contained in used parts data, making the used parts business data intelligent and realizing the value-added of used parts data. The management of used parts recycling is an important value link for automotive enterprises to reduce costs and increase efficiency, and is the key to building a reverse supply chain coordination architecture and achieving circular economy. There are many factors influencing the cost of recycling used parts, and too much interference will affect the forecasting effect. Therefore, before establishing the corresponding used parts recovery cost prediction model, the data should be decomposed into a stable time series, so that the prediction results are more accurate. This paper compares several typical prediction algorithms, uses the theory of empirical mode decomposition to preprocess the business data of used parts data, then builds the ARMA model, selects the ARMA model parameters through the AIC information criterion, and designs the supplier's used parts recycling cost prediction model. And the model is validated using the used piece business data piece data to predict the cost of the supplier's used parts recovery and provide support for the actual business system. © 2019 Association for Computing Machinery.

关键词： Cost reduction

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Comprehensive recovery of W,V,and Ti from spent selective reduction catalysts

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Rare Metals 2023年第10期42卷 3518-3531页

作者： Li-Wen Ma Xiao-Li Xi Jia-Peng Chen Fan Guo Zi-Jie Yang Zuo-Ren Nie Key Laboratory of Advanced Functional Materials Ministry of EducationFaculty of Materials and ManufacturingBeijing University of TechnologyBeijing100124China Collaborative Innovation Center of Capital Resource-Recycling Material Technology Beijing University of TechnologyBeijing100124China National Engineering Laboratory for Industrial Big-Data Application Technology Beijing University of TechnologyBeijing100124China

In this study,spent WO_(3)/V_(2)O_(5)-TiO_(2) catalysts used for selective catalytic reduction were treated by a hydrometallurgical process to comprehensively recover valuable metallic elements,such as W,V,and *** and Si impurities were preferentially removed by selective micro wave-assisted alkali leaching.W and V were leached by enhanced high-pressure leaching with efficiencies estimated at 95% and 81%.The leaching of W and V followed the nuclear shrinkage model controlled by the combination of product layer diffusion and interfacial chemical reaction.A synergistic extraction was applied to separate W and V using an extractant mixture of di-(2-ethylhexyl)phosphoric acid P204 and the primary amine *** extraction efficiencies of V and W reached 86.5% and 6.3%,respectively,with a separation coefficient(V/W) of *** product was precipitated after extraction to yield ammonium paratung state(APT) and NH_(4)VO_(3).The TiO_(2)catalyst carrier residue meets commercial specifications for *** comprehensive recovery process with the characteristics of high-pressure leaching and synergistic extraction realizes the resourceful utilization of the spent catalysts.

关键词： Spent selective catalytic reduction(SCR)catalysts Microwaveleaching Pressure leaching Synergistic extraction Comprehensive recovery

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A data-driven approach for recommending UI element layout

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Science China(Information Sciences) 2020年第9期63卷 61-63页

作者： Yonghao LONG Xiangping CHEN Yuting XIE School of Information Science and Technology National Engineering Research Center of Digital LifeSun Yat-sen University Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion School of Communication and Design Sun Yat-sen University

Dear editor,Smartphones and tablets with rich graphical user interfaces (GUI) are becoming increasingly popular. GUI design plays an important role in offering a smooth user experience. The complexity of the apps often depends on the user interface (UI)[1]with minor data processing or data processing delegates to the backend component.

关键词： UI development Software mining Layout recommendation data-driven development Intelligent Software Development

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Learning Human-Written Commit Messages to Document Code Changes

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Journal of Computer Science & technology 2020年第6期35卷 1258-1277页

作者： Yuan Huang Nan Jia Hao-Jie Zhou Xiang-Ping Chen Zi-Bin Zheng Ming-Dong Tang National Engineering Research Center of Digital Life School of Data and Computer ScienceSun Yat-sen University Guangzhou 510006China School of Information Engineering Hebei GEO UniversityShijiazhuang 050031China Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion School of Communication and DesignSun Yat-sen UniversityGuangzhou 510006China School of Information Science and Technology Guangdong University of Foreign StudiesGuangzhou 510006China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou 510006China

Commit messages are important complementary information used in understanding code changes. To address message scarcity, some work is proposed for automatically generating commit messages. However, most of these approaches focus on generating summary of the changed software entities at the superficial level, without considering the intent behind the code changes (e.g., the existing approaches cannot generate such message:"fixing 'null' pointer exception"). Considering developers often describe the intent behind the code change when writing the messages, we propose ChangeDoc, an approach to reuse existing messages in version control systems for automatical commit message generation. Our approach includes syntax, semantic, pre-syntax, and pre-semantic similarities. For a given commit without messages, it is able to discover its most similar past commit from a large commit repository, and recommend its message as the message of the given commit. Our repository contains half a million commits that were collected from SourceForge. We evaluate our approach on the commits from 10 projects. The results show that 21.5% of the recommended messages by ChangeDoc can be directly used without modification, and 62.8% require minor modifications. In order to evaluate the quality of the commit messages recommended by ChangeDoc, we performed two empirical studies involving a total of 40 participants (10 professional developers and 30 students). The results indicate that the recommended messages are very good approximations of the ones written by developers and often include important intent information that is not included in the messages generated by other tools.

关键词： commit message recommendation code syntax similarity code semantic similarity code change comprehension

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