Log in

Relevant bibliographies by topics / Markov Random Field Model

Contents

Journal articles
Dissertations / Theses
Books
Book chapters
Conference papers
Reports

Academic literature on the topic 'Markov Random Field Model'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Markov Random Field Model.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Markov Random Field Model"

1

Paget, R. "Strong markov random field model." IEEE Transactions on Pattern Analysis and Machine Intelligence 26, no. 3 (2004): 408–13. http://dx.doi.org/10.1109/tpami.2004.1262338.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Ming, Yansheng, and Zhanyi Hu. "Modeling Stereopsis via Markov Random Field." Neural Computation 22, no. 8 (2010): 2161–91. http://dx.doi.org/10.1162/neco_a_00005-ming.

Full text

Abstract:

Markov random field (MRF) and belief propagation have given birth to stereo vision algorithms with top performance. This article explores their biological plausibility. First, an MRF model guided by physiological and psychophysical facts was designed. Typically an MRF-based stereo vision algorithm employs a likelihood function that reflects the local similarity of two regions and a potential function that models the continuity constraint. In our model, the likelihood function is constructed on the basis of the disparity energy model because complex cells are considered as front-end disparity e

APA, Harvard, Vancouver, ISO, and other styles

3

Chatzis, Sotirios P., and Gabriel Tsechpenakis. "The Infinite Hidden Markov Random Field Model." IEEE Transactions on Neural Networks 21, no. 6 (2010): 1004–14. http://dx.doi.org/10.1109/tnn.2010.2046910.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Kent, John T., Kanti V. Mardia, and Alistair N. Walder. "Conditional cyclic Markov random fields." Advances in Applied Probability 28, no. 1 (1996): 1–12. http://dx.doi.org/10.2307/1427910.

Full text

Abstract:

Grenander et al. (1991) proposed a conditional cyclic Gaussian Markov random field model for the edges of a closed outline in the plane. In this paper the model is recast as an improper cyclic Gaussian Markov random field for the vertices. The limiting behaviour of this model when the vertices become closely spaced is also described and in particular its relationship with the theory of ‘snakes' (Kass et al. 1987) is established. Applications are given in Grenander et al. (1991), Mardia et al. (1991) and Kent et al. (1992).

APA, Harvard, Vancouver, ISO, and other styles

5

Kent, John T., Kanti V. Mardia, and Alistair N. Walder. "Conditional cyclic Markov random fields." Advances in Applied Probability 28, no. 01 (1996): 1–12. http://dx.doi.org/10.1017/s0001867800027257.

Full text

Abstract:

Grenander et al. (1991) proposed a conditional cyclic Gaussian Markov random field model for the edges of a closed outline in the plane. In this paper the model is recast as an improper cyclic Gaussian Markov random field for the vertices. The limiting behaviour of this model when the vertices become closely spaced is also described and in particular its relationship with the theory of ‘snakes' (Kass et al. 1987) is established. Applications are given in Grenander et al. (1991), Mardia et al. (1991) and Kent et al. (1992).

APA, Harvard, Vancouver, ISO, and other styles

6

Katakami, Shun, Hirotaka Sakamoto, Shin Murata, and Masato Okada. "Gaussian Markov Random Field Model without Boundary Conditions." Journal of the Physical Society of Japan 86, no. 6 (2017): 064801. http://dx.doi.org/10.7566/jpsj.86.064801.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Ohno, Yoshinori, Kenji Nagata, Tatsu Kuwatani, Hayaru Shouno, and Masato Okada. "Deterministic Algorithm for Nonlinear Markov Random Field Model." Journal of the Physical Society of Japan 81, no. 6 (2012): 064006. http://dx.doi.org/10.1143/jpsj.81.064006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Cressie, Noel, and Subhash Lele. "New models for Markov random fields." Journal of Applied Probability 29, no. 4 (1992): 877–84. http://dx.doi.org/10.2307/3214720.

Full text

Abstract:

The Hammersley–Clifford theorem gives the form that the joint probability density (or mass) function of a Markov random field must take. Its exponent must be a sum of functions of variables, where each function in the summand involves only those variables whose sites form a clique. From a statistical modeling point of view, it is important to establish the converse result, namely, to give the conditional probability specifications that yield a Markov random field. Besag (1974) addressed this question by developing a one-parameter exponential family of conditional probability models. In this ar

APA, Harvard, Vancouver, ISO, and other styles

9

Cressie, Noel, and Subhash Lele. "New models for Markov random fields." Journal of Applied Probability 29, no. 04 (1992): 877–84. http://dx.doi.org/10.1017/s0021900200043758.

Full text

Abstract:

The Hammersley–Clifford theorem gives the form that the joint probability density (or mass) function of a Markov random field must take. Its exponent must be a sum of functions of variables, where each function in the summand involves only those variables whose sites form a clique. From a statistical modeling point of view, it is important to establish the converse result, namely, to give the conditional probability specifications that yield a Markov random field. Besag (1974) addressed this question by developing a one-parameter exponential family of conditional probability models. In this ar

APA, Harvard, Vancouver, ISO, and other styles

10

Halim, Siana. "APLIKASI MARKOV RANDOM FIELD PADA MASALAH INDUSTRI." Jurnal Teknik Industri 4, no. 1 (2004): 19–25. http://dx.doi.org/10.9744/jti.4.1.19-25.

Full text

Abstract:

Markov chain in the stochastic process is widely used in the industrial problems particularly in the problem of determining the market share of products. In this paper we are going to extend the one in the random field so called the Markov Random Field and applied also in the market share problem with restriction the market is considered as a discrete lattice and Pott's models are going to be used as the potential function. Metropolis sampler is going to be used to determine the stability condition.    Abstract in Bahasa Indonesia :   Rantai Markov dalam proses st

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Markov Random Field Model"

1

Barker, Simon A. "Image segmentation using Markov random field models." Thesis, University of Cambridge, 1998. https://www.repository.cam.ac.uk/handle/1810/272037.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Barker, S. A. "Unsupervised image segmentation using Markov Random Field models." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596368.

Full text

Abstract:

The development of a fully unsupervised algorithm to achieve image segmentation is the central theme of this dissertation. Existing literature falls short of such a goal providing many algorithms capable of solving a subset of this highly challenging problem. Unsupervised segmentation is the process of identifying and locating the constituent regions of an observed image, while having no prior knowledge of the number of regions. The problem can be formulated in a Bayesian framework and through the use of an assumed model unsupervised segmentation can be posed as a problem of optimisation. This

APA, Harvard, Vancouver, ISO, and other styles

3

Kasetkasem, Teerasit. "Image analysis methods based on Markov random field models." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available full text, 2002. http://wwwlib.umi.com/cr/syr/main.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Islam, Mofakharul University of Ballarat. "Unsupervised Color Image Segmentation Using Markov Random Fields Model." University of Ballarat, 2008. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/12827.

Full text

Abstract:

We propose a novel approach to investigate and implement unsupervised segmentation of color images particularly natural color images. The aim is to devise a robust unsu- pervised segmentation approach that can segment a color textured image accurately. Here, the color and texture information of each individual pixel along with the pixel's spatial relationship within its neighborhood have been considered for producing precise segmentation of color images. Precise segmentation of images has tremendous potential in various application domains like bioinformatics, forensics, security and surveilla

APA, Harvard, Vancouver, ISO, and other styles

5

Frondana, Iara Moreira. "Model selection for discrete Markov random fields on graphs." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-02022018-151123/.

Full text

Abstract:

In this thesis we propose to use a penalized maximum conditional likelihood criterion to estimate the graph of a general discrete Markov random field. We prove the almost sure convergence of the estimator of the graph in the case of a finite or countable infinite set of variables. Our method requires minimal assumptions on the probability distribution and contrary to other approaches in the literature, the usual positivity condition is not needed. We present several examples with a finite set of vertices and study the performance of the estimator on simulated data from theses examples. We also

APA, Harvard, Vancouver, ISO, and other styles

6

Islam, Mofakharul. "Unsupervised color image segmentation using Markov Random Fields Model." Thesis, University of Ballarat, 2008. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/53709.

Full text

Abstract:

We propose a novel approach to investigate and implement unsupervised segmentation of color images particularly natural color images. The aim is to devise a robust unsu- pervised segmentation approach that can segment a color textured image accurately. Here, the color and texture information of each individual pixel along with the pixel's spatial relationship within its neighborhood have been considered for producing precise segmentation of color images. Precise segmentation of images has tremendous potential in various application domains like bioinformatics, forensics, security and surveilla

APA, Harvard, Vancouver, ISO, and other styles

7

Islam, Mofakharul. "Unsupervised color image segmentation using Markov Random Fields Model." University of Ballarat, 2008. http://archimedes.ballarat.edu.au:8080/vital/access/HandleResolver/1959.17/15694.

Full text

Abstract:

We propose a novel approach to investigate and implement unsupervised segmentation of color images particularly natural color images. The aim is to devise a robust unsu- pervised segmentation approach that can segment a color textured image accurately. Here, the color and texture information of each individual pixel along with the pixel's spatial relationship within its neighborhood have been considered for producing precise segmentation of color images. Precise segmentation of images has tremendous potential in various application domains like bioinformatics, forensics, security and surveilla

APA, Harvard, Vancouver, ISO, and other styles

8

Manggala, Putra. "On Markov random field models for spatial data: towards a practitioners toolbox." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114270.

Full text

Abstract:

In the era of big data, data sets have been growing very large, and interest for algorithms and computation framework that handle such large scales is increasing. The number of computing cores per chip has also increased. Instead of developing ingenious ways of speeding up convergences and obtaining better approximations for a smaller subclass of the problems, it is interesting to simply "throw more cores" at exact algorithms and get a speed-up which scales accordingly. This allows practitioners who are not specialists to use the algorithms more efficiently. The MapReduce framework is one of t

APA, Harvard, Vancouver, ISO, and other styles

9

Liang, Dong Cowles Mary Kathryn. "Issues in Bayesian Gaussian Markov random field models with application to intersensor calibration." Iowa City : University of Iowa, 2009. http://ir.uiowa.edu/etd/400.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Liang, Dong. "Issues in Bayesian Gaussian Markov random field models with application to intersensor calibration." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/400.

Full text

Abstract:

A long term record of the earth's vegetation is important in studies of global climate change. Over the last three decades, multiple data sets on vegetation have been collected using different satellite-based sensors. There is a need for methods that combine these data into a long term earth system data record. The Advanced Very High Resolution Radiometer (AVHRR) has provided reflectance measures of the entire earth since 1978. Physical and statistical models have been used to improve the consistency and reliability of this record. The Moderated Resolution Imaging Spectroradiometer (MODIS) has

APA, Harvard, Vancouver, ISO, and other styles

More sources

Books on the topic "Markov Random Field Model"

1

Li, S. Z. Markov random field modeling in computer vision. Springer-Verlag, 1995.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

2

Li, S. Z. Markov random field modeling in image analysis. 3rd ed. Springer, 2009.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

3

Peschanskiy, Aleksey. Semi-Markov models of prevention of unreliable single-channel service system with losses. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1870597.

Full text

Abstract:

The monograph examines various maintenance strategies of a single-channel system with losses and unreliable recoverable service device under the assumption of a general type of random variables describing random processes occurring in the system. The apparatus for constructing models of the functioning of the system are semi-Markov processes with a measurable phase space of states and phase enlargement algorithms. Stationary probabilistic and economic indicators of the system are explicitly determined and the tasks of optimal frequency of maintenance of the device are solved. For researc

APA, Harvard, Vancouver, ISO, and other styles

4

Li, S. Z. Markov Random Field Modeling in Computer Vision. Springer Japan, 1995. http://dx.doi.org/10.1007/978-4-431-66933-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Li, Stan Z. Markov Random Field Modeling in Image Analysis. Springer Japan, 2001. http://dx.doi.org/10.1007/978-4-431-67044-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Korn, Christopher A. Markov random field textures and applications in image processing. Naval Postgraduate School, 1997.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

7

Rychkov, Slava. Lectures on the Random Field Ising Model. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-42000-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Zhou, Peifang. Application of Markov random field theory to image coding and motion estimation. National Library of Canada = Bibliothèque nationale du Canada, 1993.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

9

Newman, M. E. J. Monte Carlo study of the random-field Ising model. Cornell Theory Center, Cornell University, 1995.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

10

Yakimovich, Sergey, and Yuriy Efimov. Modeling and scientific research tools in the timber industry based on LabVIEW. INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/1851518.

Full text

Abstract:

The textbook describes the methods of modeling and modern theory of industrial experiment in relation to the timber industry: model design, test preparation, selection of measuring instruments and experiment planning, data processing methods and their analysis. For practical consolidation of the material, laboratory work on experimental studies of random processes of longitudinal sawing of wood based on LabVIEW and spectral analysis is presented. Meets the requirements of the federal state educational standards of higher education of the latest generation. For bachelors and masters in the fiel

APA, Harvard, Vancouver, ISO, and other styles

More sources

Book chapters on the topic "Markov Random Field Model"

1

Kasetkasem, Teerasit. "Markov Random Field Models." In Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-05605-9_7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Li, S. Z. "Discontinuity-Adaptivity Model and Robust Estimation." In Markov Random Field Modeling in Computer Vision. Springer Japan, 1995. http://dx.doi.org/10.1007/978-4-431-66933-3_4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Xiong, Taisong, and Yuanyuan Huang. "Robust Markov Random Field Model for Image Segmentation." In Lecture Notes in Electrical Engineering. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0539-8_21.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Liu, Zhi-Qiang, Jinhai Cai, and Richard Buse. "Markov Random Field Model for Recognizing Handwritten Digits." In Handwriting Recognition. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44850-1_5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Kim, Daehwan, Ki-Hong Kim, Gil-Haeng Lee, and Daijin Kim. "Dynamic Markov Random Field Model for Visual Tracking." In Computer Vision – ECCV 2012. Workshops and Demonstrations. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33885-4_21.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Pardo, J. M., D. Cabello, and J. Heras. "A Markov random field model for bony tissue classification." In Image Analysis and Processing. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63508-4_144.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Li, S. Z. "Markov random field models in computer vision." In Computer Vision — ECCV '94. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/bfb0028368.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Li, S. Z. "Low Level MRF Models." In Markov Random Field Modeling in Computer Vision. Springer Japan, 1995. http://dx.doi.org/10.1007/978-4-431-66933-3_2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Li, S. Z. "High Level MRF Models." In Markov Random Field Modeling in Computer Vision. Springer Japan, 1995. http://dx.doi.org/10.1007/978-4-431-66933-3_5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Yu, Stella X., Tai Sing Lee, and Takeo Kanade. "A Hierarchical Markov Random Field Model for Figure-Ground Segregation." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44745-8_9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Markov Random Field Model"

1

Takahashi, Haruhisa. "Variational phasor mean field model for Markov random fields." In 2007 9th International Symposium on Signal Processing and Its Applications (ISSPA). IEEE, 2007. http://dx.doi.org/10.1109/isspa.2007.4555531.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Chatzis, Sotirios P., and Gabriel Tsechpenakis. "The infinite Hidden Markov random field model." In 2009 IEEE 12th International Conference on Computer Vision (ICCV). IEEE, 2009. http://dx.doi.org/10.1109/iccv.2009.5459177.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Metzler, Donald, and W. Bruce Croft. "A Markov random field model for term dependencies." In the 28th annual international ACM SIGIR conference. ACM Press, 2005. http://dx.doi.org/10.1145/1076034.1076115.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Caraffa, Laurent, and Jean-Philippe Tarel. "Markov Random Field model for single image defogging." In 2013 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2013. http://dx.doi.org/10.1109/ivs.2013.6629596.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Katzer, Mathias, Franz Kummert, and Gerhard Sagerer. "A Markov Random Field model of microarray gridding." In the 2003 ACM symposium. ACM Press, 2003. http://dx.doi.org/10.1145/952532.952551.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Ying Dong and Jim Ji. "Phase unwrapping using region-based Markov Random Field model." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5627494.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Shi, Yonggang, Yong Yuan, Xueping Zhang, and Zhiwen Liu. "Markov Random Field model based multimodal medical image registration." In 2012 11th International Conference on Signal Processing (ICSP 2012). IEEE, 2012. http://dx.doi.org/10.1109/icosp.2012.6491582.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Chen, Ting-Li. "A Markov Random Field Model for Medical Image Denoising." In 2009 2nd International Conference on Biomedical Engineering and Informatics. IEEE, 2009. http://dx.doi.org/10.1109/bmei.2009.5305737.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Li, Min, and Truong Nguyen. "Markov Random Field Model-Based Edge-Directed Image Interpolation." In 2007 IEEE International Conference on Image Processing. IEEE, 2007. http://dx.doi.org/10.1109/icip.2007.4379100.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Cooper, P. R., Seungseok Hyun, and P. Yuen. "A Markov random field model of subjective contour perception." In Proceedings of 13th International Conference on Pattern Recognition. IEEE, 1996. http://dx.doi.org/10.1109/icpr.1996.547242.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Markov Random Field Model"

1

Harms, Steven. A centered bivariate Markov random field model for mixed-response lattice data. Iowa State University, 2019. http://dx.doi.org/10.31274/cc-20240624-17.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Thompson, Theodore J., James P. Boyle, and Douglas J. Hentschel. Markov Chains for Random Urinalysis 1: Age-Test Model. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada263274.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Streso, Katy, and Francesco Lagona. Hidden Markov random field and FRAME modelling for TCA-image analysis. Max Planck Institute for Demographic Research, 2005. http://dx.doi.org/10.4054/mpidr-wp-2005-032.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Boyle, James P., Douglas J. Hentschel, and Theodore J. Thompson. Markov Chains for Random Urinalysis II: Age-Test Model with Absorbing State. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada265557.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

David P. Belanger. The random-field Ising model at high magnetic concentration. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/838773.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Heasler, Patrick G. Development of a Random Field Model for Gas Plume Detection in Multiple LWIR Images. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/1133250.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Goodwin, Peter, and Rebecca Molinari. Phragmites Mapping and Modeling in Great Salt Lake Wetlands at the Bear River Migratory Bird Refuge, Utah. Utah Geological Survey, 2024. http://dx.doi.org/10.34191/ri-287.

Full text

Abstract:

Phragmites (Phragmites australis ssp. australis) threatens Great Salt Lake wetlands by readily displacing desirable native vegetation, degrading habitats, and diverting water from the lake and surrounding wetlands through increased evapotranspiration water loss. Understandably, land managers around the Great Salt Lake consider phragmites control a top priority and invest significant resources to treat and eradicate phragmites. Effective phragmites control relies on accurate mapping to identify possible treatment and follow up areas, and to clearly distinguish between phragmites and native vege

APA, Harvard, Vancouver, ISO, and other styles

8

Huang, Lei, Meng Song, Hui Shen, et al. Deep learning methods for omics data imputation. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48221.

Full text

Abstract:

One common problem in omics data analysis is missing values, which can arise due to various reasons, such as poor tissue quality and insufficient sample volumes. Instead of discarding missing values and related data, imputation approaches offer an alternative means of handling missing data. However, the imputation of missing omics data is a non-trivial task. Difficulties mainly come from high dimensionality, non-linear or nonmonotonic relationships within features, technical variations introduced by sampling methods, sample heterogeneity, and the non-random missingness mechanism. Several advan

APA, Harvard, Vancouver, ISO, and other styles

9

Ukkusuri, Satish, Lu Ling, Tho V. Le, and Wenbo Zhang. Performance of Right-Turn Lane Designs at Intersections. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317277.

Full text

Abstract:

Right-turn lane (RTL) crashes are among the most key contributors to intersection crashes in the US. Different right turn lanes based on their design, traffic volume, and location have varying levels of crash risk. Therefore, engineers and researchers have been looking for alternative ways to improve the safety and operations for right-turn traffic. This study investigates the traffic safety performance of the RTL in Indiana state based on multi-sources, including official crash reports, official database, and field study. To understand the RTL crashes' influencing factors, we introduce a rand

APA, Harvard, Vancouver, ISO, and other styles

10

Parkins and Leis. L51654 Spatial Densities of Stress-Corrosion Cracks in Line-Pipe Steels. Pipeline Research Council International, Inc. (PRCI), 1992. http://dx.doi.org/10.55274/r0010367.

Full text

Abstract:

There was a need to define the spatial density of stress-corrosion crack arrays that develop in operating gas-transmission pipelines and in laboratory test specimens of line-pipe steel, to improve understanding of the factors that control the density and provide data to test models of pipeline cracking. Within the broad definition of crack density are included the locations, numbers, lengths, depths, and degree of linkage of cracks. An analysis has been conducted of location, numbers, lengths, depths, and degree of linkage of stress-corrosion crack colonies in samples from the field and from l

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!