Littérature scientifique sur le sujet « GAUSSIAN BASED HIGHWAY »
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Articles de revues sur le sujet "GAUSSIAN BASED HIGHWAY"
Xu, Hong Ke, Chao Cai, Hao Chen, Jian Wu Fang et Shu Guang Li. « Research on License Plate Tracking and Detection Based on Optical Flow ». Applied Mechanics and Materials 135-136 (octobre 2011) : 775–80. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.775.
Texte intégralAbdelkader, Eslam Mohammed, Abobakr Al-Sakkaf, Nehal Elshaboury et Ghasan Alfalah. « Hybrid Grey Wolf Optimization-Based Gaussian Process Regression Model for Simulating Deterioration Behavior of Highway Tunnel Components ». Processes 10, no 1 (24 décembre 2021) : 36. http://dx.doi.org/10.3390/pr10010036.
Texte intégralTohti, Gulbahar, Mamtimin Gheni, Yu Feng Chen et Mamatjan Tursun. « Capacity Analysis of Urban Highway Intersections ». Key Engineering Materials 462-463 (janvier 2011) : 1170–75. http://dx.doi.org/10.4028/www.scientific.net/kem.462-463.1170.
Texte intégralZhu, Zixuan, Chenglong Teng, Yingfeng Cai, Long Chen, Yubo Lian et Hai Wang. « Vehicle Safety Planning Control Method Based on Variable Gauss Safety Field ». World Electric Vehicle Journal 13, no 11 (31 octobre 2022) : 203. http://dx.doi.org/10.3390/wevj13110203.
Texte intégralPeng, Tao, Li-li Su, Zhi-wei Guan, Hai-jing Hou, Jun-kai Li, Xing-liang Liu et Yi-ke Tong. « Lane-Change Model and Tracking Control for Autonomous Vehicles on Curved Highway Sections in Rainy Weather ». Journal of Advanced Transportation 2020 (25 novembre 2020) : 1–15. http://dx.doi.org/10.1155/2020/8838878.
Texte intégralZhang, Yule, et Shoulin Zhu. « Study on the Effect of Driving Time on Fatigue of Grassland Road Based on EEG ». Journal of Healthcare Engineering 2021 (8 juillet 2021) : 1–9. http://dx.doi.org/10.1155/2021/9957828.
Texte intégralAghayari, M., P. Pahlavani et B. Bigdeli. « A GEOGRAPHIC WEIGHTED REGRESSION FOR RURAL HIGHWAYS CRASHES MODELLING USING THE GAUSSIAN AND TRICUBE KERNELS : A CASE STUDY OF USA RURAL HIGHWAYS ». ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W4 (27 septembre 2017) : 305–9. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w4-305-2017.
Texte intégralOguri, Y., T. Yamashita, A. Ebihara, N. Kambe et J. Hasegawa. « PIXE MEASUREMENT OF ATMOSPHERIC PARTICULATE MATTER IN A RESIDENTIAL AREA NEAR A MAJOR URBAN HIGHWAY ». International Journal of PIXE 10, no 03n04 (janvier 2000) : 127–35. http://dx.doi.org/10.1142/s0129083500000183.
Texte intégralKorablev, R. A., V. P. Belokurov et S. V. Belokurov. « Influence of anthropogenic impact of vehicles on roadside forest plantations ». IOP Conference Series : Earth and Environmental Science 875, no 1 (1 octobre 2021) : 012079. http://dx.doi.org/10.1088/1755-1315/875/1/012079.
Texte intégralQing, Feng, Yan Zhao, Xingmin Meng, Xiaojun Su, Tianjun Qi et Dongxia Yue. « Application of Machine Learning to Debris Flow Susceptibility Mapping along the China–Pakistan Karakoram Highway ». Remote Sensing 12, no 18 (10 septembre 2020) : 2933. http://dx.doi.org/10.3390/rs12182933.
Texte intégralThèses sur le sujet "GAUSSIAN BASED HIGHWAY"
Zhang, Lin. « Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data ». Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/95040.
Texte intégralPHD
AGGARWAL, ANCHAL. « SENSITIVE ANALYSIS OF CALINE 4 HIGHWAY DISPERSION MODEL UNVER MIXED TRAFIC CONDITIONS ». Thesis, 2012. http://dspace.dtu.ac.in:8080/jspui/handle/repository/13911.
Texte intégralRapid urbanization and industrialization of cities have increased the vehicular traffic leading to increase in air pollution in urban areas. It has been estimated that in India road traffic contributes approximately 70% of air pollution in urban areas. To reduce the impacts of air pollution due to vehicular traffic, it is important to manage and improve the quality of air in such urban areas. Air pollution dispersion models are used to effectively and efficiently plan the management (environment management plan) of vehicular traffic pollution on particular area/ road corridor, along with monitoring of air pollutants. They not only aid in determining the present influenced area/ affected due to vehicular traffic pollution but also help in identifying the future scenarios under different traffic and meteorological conditions made by these models. Vehicular pollution modeling involves air pollution prediction estimates by simulating impact of emissions from vehicular activities in a given region under specified traffic and meteorological conditions. Throughout the world, including India the prediction of vehicular pollutant concentrations along highways and roads are carried out by using various Gaussian-based highway dispersion models. Based on the Gaussian dispersion model, several prediction models have been developed to predict vehicular pollution levels along the highways. The most popular amongst various highway dispersion models, are the CALINE model (latest being CALINE 4). CALINE 4 developed by Benson (1984) is extensively used throughout the world (including India) for various vehicular pollution estimate/ prediction along the highways. The CALINE 4 Model uses various inputs (viz., Traffic Volume, Emission Factor, Road geometry, Wind Speed, Wind Direction, Background Concentration) to predict the air pollution concentrations at pre-identified receptor locations along the highway. The present study focuses on sensitivity analysis of CALINE-4 model which is the fourth version simple line source Gaussian plume dispersion model. Ashram Chowk – CRRI highway Corridor of NH-2 was selected as the area of study. Inputs data (viz. traffic volume, traffic compositions, meteorological data etc.) required for CALINE 4 model was collected from field surveys data. Emission factors provided by CPCB (2000) and ARAI (2007) were used to estimate Weighted Emission Factor (WEF) to account for mixed traffic conditions. The CO concentration due to traffic along the xiii Ashram Chowk – CRRI highway corridor was predicted at the pre-identified receptor locations. The dispersion of CO concentrations was found to be present upto a distance of 150m from the edge of the mixing zone width (road width+3m on each side of the road). The predicted CO concentrations in all the cases (viz., 1-hour Standard Case Run Conditions, 1-hour Worse Case Run Conditions) were within the National Ambient Air Quality Standard, 2009 (NAAQS, 2009) (i.e. 2 mg/m3 for 8 hours and 4 mg/m3 for 1 hour for CO). The regression coefficient (r2) between predicted and observed 1-hour CO concentrations using CPCB emission factors for Standard Case Run Condition was 0.65 and for Worse Case Run Condition was 0.76. Similarly, the regression coefficient (r2) between predicted and observed 1-hour CO concentrations using ARAI emission factors for Standard Case Run Condition was 0.60 and for Worse Case Run Condition was 0.73. A sensitivity analysis of the CALINE 4 model had been performed to identify the most influential variables. CALINE 4 model was found to be relatively sensitive to wind angle (s) for small receptor distances. The highest CO concentrations were observed by a wind angle of ~10° as measured from the road centerline. Wind speed had a considerable effect, e.g., predicted CO concentrations were dropped by 75% - 80% as wind speed increased from 0.5 to 5 m/s. From unstable to stable conditions, average increase in CO concentration was 43%. The model consistently predicts lower CO concentrations for greater highway widths. This effect was most apparent for receptors near the roadway edge. Roadway height (from receptor location at ground level) had very less effect for small change in height but has considerable effect for more deeper or elevated roadway height. Sensitive Analysis of CALINE 4 had also revealed that among various input variable, source strength, wind speed, highway width and median width were most significant input variable and wind direction, roadway height, distance of receptor to roadway and atmospheric stability were the less significant input variables. Surface Roughness and Mixing height had negligible effect on predicted CO concentrations.
Chapitres de livres sur le sujet "GAUSSIAN BASED HIGHWAY"
Scott, Jennifer, et Miroslav Tůma. « Sparse Matrix Ordering Algorithms ». Dans Nečas Center Series, 135–61. Cham : Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-25820-6_8.
Texte intégralLittle, Max A. « Linear-Gaussian systems and signal processing ». Dans Machine Learning for Signal Processing, 187–264. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198714934.003.0007.
Texte intégralPathak, Vishwambhar. « Autonomous Market Segments Estimation Using Density Conscious Artificial Immune System Learner ». Dans Advances in Business Information Systems and Analytics, 110–35. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2234-8.ch006.
Texte intégralZhu, Meng, et Atta Badii. « Cross-Modal Semantic-Associative Labelling, Indexing and Retrieval of Multimodal Data ». Dans Multiple Sensorial Media Advances and Applications, 234–57. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-821-7.ch012.
Texte intégralErman, Burak, et James E. Mark. « Overview and Some Fundamental Information ». Dans Structures and Properties of Rubberlike Networks. Oxford University Press, 1997. http://dx.doi.org/10.1093/oso/9780195082371.003.0003.
Texte intégralActes de conférences sur le sujet "GAUSSIAN BASED HIGHWAY"
Zhang, Mingheng, Zhengxian Guo, Zhaoyang Liu et Xing Wan. « Research of Driving Fatigue Detection Based on Gaussian Mixture Hidden Markov Model ». Dans 3rd International Forum on Connected Automated Vehicle Highway System through the China Highway & Transportation Society. 400 Commonwealth Drive, Warrendale, PA, United States : SAE International, 2020. http://dx.doi.org/10.4271/2020-01-5158.
Texte intégralLiu, Wenjun, Yulin Zhai, Guang Chen et Alois Knoll. « Gaussian Process based Model Predictive Control for Overtaking Scenarios at Highway Curves ». Dans 2022 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2022. http://dx.doi.org/10.1109/iv51971.2022.9827233.
Texte intégralShinn, Tyler, Richard Carpenter et Roger C. Fales. « State Estimation Techniques for Axial Piston Pump Health Monitoring ». Dans ASME/BATH 2015 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/fpmc2015-9621.
Texte intégralMamann, Hadriel, Thomas Nieddu, Mathieu Bozzio, Félix Hoffet, Félix Garreau de Loubresse, Eleni Diamanti, Alban Urvoy et Julien Laurat. « Quantum cryptographic protocol implementation using a highly-efficient cold-atom-based quantum memory ». Dans CLEO : Fundamental Science. Washington, D.C. : Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_fs.2023.ff2a.3.
Texte intégralLi, Meng, Mohammad Kazem Sadoughi, Zhen Hu et Chao Hu. « System Reliability Analysis Using Hybrid Gaussian Process Model ». Dans ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-98173.
Texte intégralLeahu, Haralambie, Michael Kaisers et Tim Baarslag. « Automated Negotiation with Gaussian Process-based Utility Models ». Dans Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California : International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/60.
Texte intégralZhao, Wentian, Shaojie Wang, Zhihuai Xie, Jing Shi et Chenliang Xu. « GAN-EM : GAN Based EM Learning Framework ». Dans Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California : International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/612.
Texte intégralGuo, Tuan, Jacques Albert, Chengkun Chen, Alexei Ivanov et Albane Laronche. « Highly accurate micro-displacement measurement based on Gaussian-chirped tilted fiber Bragg grating ». Dans 19th International Conference on Optical Fibre Sensors, sous la direction de David D. Sampson. SPIE, 2008. http://dx.doi.org/10.1117/12.785637.
Texte intégralLi, Guang, et J. Quincy Brown. « Optimizing Imaging Throughput and Resolution in Light Sheet Microscopy Using Deep-learning-based Beam Shape Translation ». Dans Novel Techniques in Microscopy. Washington, D.C. : Optica Publishing Group, 2023. http://dx.doi.org/10.1364/ntm.2023.ntu1c.3.
Texte intégralLin, Po Ting, Wei-Hao Lu et Shu-Ping Lin. « A Comprehensive Investigation of Ensembles of Gaussian-Based and Gradient-Based Transformed Reliability Analyses : When and How to Use Them ». Dans ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59151.
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