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Journal articles on the topic 'Accurate distribution data'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Wang, Zhao Hong. "Normal Distribution Data Generating Method Based on Cloud Model." Advanced Materials Research 171-172 (December 2010): 385–88. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.385.

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The similar normal distribution is used wildly in the natural science and social science, fuzzy membership degree function which is accurately established seriously reduces the forecast accuracy of such data. Cloud model compare randomness and fuzziness organically, it reveal the relevance between randomness and fuzziness with digital expectations, entropy and hyper entropy, forecast algorithm based on normal cloud model relaxed the requirements of a normal distribution prerequisite and replaced the accurate membership degree function with the membership degree distribution expectation functio

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Sung-Shik Koh, H. Hama, and T. T. Zin. "Accurate Estimation of Missing Data under Noise Distribution." IEEE Transactions on Consumer Electronics 52, no. 2 (2006): 528–35. http://dx.doi.org/10.1109/tce.2006.1649675.

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Trombik, J., and T. Hlásny. "Free European data on forest distribution: overview and evaluation." Journal of Forest Science 59, No. 11 (2013): 447–57. http://dx.doi.org/10.17221/58/2013-jfs.

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A growing need for the evaluation of prospects and sustainability of forest resources calls for the availability of harmonized data on forest distribution. We described and evaluated nine datasets providing such information: Corine LandCover, four European forest maps and four tree species distribution maps. Apart from providing a condensed overview of these datasets, we focused on the match between selected forest maps and forest management plans (FMPs) of Slovakia, which can be thought of as highly accurate information on forest distribution. The degree of match between forest and species ar

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Trumbo, D. R., A. A. Burgett, and J. H. Knouft. "Testing climate-based species distribution models with recent field surveys of pond-breeding amphibians in eastern Missouri." Canadian Journal of Zoology 89, no. 11 (2011): 1074–83. http://dx.doi.org/10.1139/z11-083.

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Species distribution models (SDMs) have become an important tool for ecologists by providing the ability to predict the distributions of organisms based on species niche parameters and available habitat across broad geographic areas. However, investigation of the appropriate extent of environmental data needed to make accurate predictions has received limited attention. We investigate whether SDMs developed with regional climate and species locality data (i.e., within Missouri, USA) produce more accurate predictions of species occurrences than models developed with data from across an entire s

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Liu, Yu, Xiaoping Wang, and Jiaxin Qian. "Crop distribution extraction based on Sentinel data." E3S Web of Conferences 252 (2021): 02081. http://dx.doi.org/10.1051/e3sconf/202125202081.

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Remote sensing identification and classification of crops is the use of remote sensing for estimating crop planting area of timely and accurate monitoring of crop growth and plant diseases and insect pests in advance to make the product output to estimate the key and premise of the study using Sentinel-1 and Sentinel-2 satellite, by random forest algorithm, the traditional optical wavelengths and vegetation index The backward scattering field of red edge information and radar information in feature selection and feature classification, including winter wheat summer corn orchard woodland town w

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Xintao, Xia, Chang Zhen, Zhang Lijun, and Yang Xiaowei. "Estimation on Reliability Models of Bearing Failure Data." Mathematical Problems in Engineering 2018 (2018): 1–21. http://dx.doi.org/10.1155/2018/6189527.

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The failure data of bearing products is random and discrete and shows evident uncertainty. Is it accurate and reliable to use Weibull distribution to represent the failure model of product? The Weibull distribution, log-normal distribution, and an improved maximum entropy probability distribution were compared and analyzed to find an optimum and precise reliability analysis model. By utilizing computer simulation technology and k-s hypothesis testing, the feasibility of three models was verified, and the reliability of different models obtained via practical bearing failure data was compared a

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Lin, Zhidi, Dongliang Duan, Qi Yang, et al. "Data-Driven Fault Localization in Distribution Systems with Distributed Energy Resources." Energies 13, no. 1 (2020): 275. http://dx.doi.org/10.3390/en13010275.

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The integration of Distributed Energy Resources (DERs) introduces a non-conventional two-way power flow which cannot be captured well by traditional model-based techniques. This brings an unprecedented challenge in terms of the accurate localization of faults and proper actions of the protection system. In this paper, we propose a data-driven fault localization strategy based on multi-level system regionalization and the quantification of fault detection results in all subsystems/subregions. This strategy relies on the tree segmentation criterion to divide the entire system under study into se

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Gao, Nannan, Fen Li, Hui Zeng, Daniël van Bilsen, and Martin De Jong. "Can More Accurate Night-Time Remote Sensing Data Simulate a More Detailed Population Distribution?" Sustainability 11, no. 16 (2019): 4488. http://dx.doi.org/10.3390/su11164488.

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Aging, shrinking cities, urban agglomerations and other new key terms continue to emerge when describing the large-scale population changes in various cities in mainland China. It is important to simulate the distribution of residential populations at a coarse scale to manage cities as a whole, and at a fine scale for policy making in infrastructure development. This paper analyzes the relationship between the DN (Digital number, value assigned to a pixel in a digital image) value of NPP-VIIRS (the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite)

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Yoon, Seong-Sim, Anh Tran Phuong, and Deg-Hyo Bae. "Quantitative Comparison of the Spatial Distribution of Radar and Gauge Rainfall Data." Journal of Hydrometeorology 13, no. 6 (2012): 1939–53. http://dx.doi.org/10.1175/jhm-d-11-066.1.

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Abstract The common statement that a rain gauge network usually provides better observation at specific points while weather radar provides more accurate observation of the spatial distribution of rain field over a large area has never been subjected to quantitative evaluation. The aim of this paper is to evaluate the statement by using some statistical criteria. The Monte Carlo simulation experiment, inverse distance weighting (IDW) interpolation method, and cross-validation technique are used to investigate the relation between the accuracy of the interpolated rainfall and the rain gauge den

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Piltz, Ross O. "Accurate data processing for neutron Laue diffractometers." Journal of Applied Crystallography 51, no. 3 (2018): 635–45. http://dx.doi.org/10.1107/s1600576718005058.

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The factors affecting the accuracy of structural refinements from image-plate neutron Laue diffractometers are analysed. From this analysis, an improved data-processing method is developed which optimizes the intensity corrections for exposure scaling, wavelength distribution, absorption and extinction corrections, and the wavelength/spatial/time dependence of the image-plate detector efficiencies. Of equal importance is an analysis of the sources of uncertainty in the final corrected intensities, without which bias of the merged intensities occurs, due to the dominance of measurements with sm

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Karimi, P., and W. G. M. Bastiaanssen. "Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data." Hydrology and Earth System Sciences Discussions 11, no. 1 (2014): 1073–123. http://dx.doi.org/10.5194/hessd-11-1073-2014.

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Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distribution of actual evapotrans

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Berry, Mari, Brian Peacock, Bobbie Foote, and Lawrence Leemis. "Visual Assessment vs. Statistical Goodness of Fit Tests for Identifying Parent Population." Proceedings of the Human Factors Society Annual Meeting 32, no. 7 (1988): 460–64. http://dx.doi.org/10.1177/154193128803200701.

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Statistical tests are used to identify the parent distribution corresponding to a data set. A human observer looking at a histogram can also identify a probability distribution that models the parent distribution. The accuracy of a human observer was compared to the chi-square test for discrete data and the Kolmogorov-Smirnov and chi-square tests for continuous data. The human observer proved more accurate in identifying continuous distributions and the chi-square test proved to be superior in identifying discrete distributions. The effect of sample size and number of intervals in the histogra

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Wan, Haoming, Yunwei Tang, Linhai Jing, Hui Li, Fang Qiu, and Wenjin Wu. "Tree Species Classification of Forest Stands Using Multisource Remote Sensing Data." Remote Sensing 13, no. 1 (2021): 144. http://dx.doi.org/10.3390/rs13010144.

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The spatial distribution of forest stands is one of the fundamental properties of forests. Timely and accurately obtained stand distribution can help people better understand, manage, and utilize forests. The development of remote sensing technology has made it possible to map the distribution of tree species in a timely and accurate manner. At present, a large amount of remote sensing data have been accumulated, including high-spatial-resolution images, time-series images, light detection and ranging (LiDAR) data, etc. However, these data have not been fully utilized. To accurately identify t

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Kumar, Abhishek, Minho Sung, Jun (Jim) Xu, and Jia Wang. "Data streaming algorithms for efficient and accurate estimation of flow size distribution." ACM SIGMETRICS Performance Evaluation Review 32, no. 1 (2004): 177–88. http://dx.doi.org/10.1145/1012888.1005709.

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Weld, Christopher, and Lawrence Leemis. "Mixed-type distribution plots." Information Visualization 18, no. 3 (2018): 311–17. http://dx.doi.org/10.1177/1473871618756584.

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Plotting is among the most effective ways to quickly and accurately describe a probability distribution. It makes often complex information accessible, enabling intuition for respective outcomes at a glance. Matters complicate, however, for mixed-type distributions. Mixed-type distributions contain both continuous and discrete components, and accurately portraying those on a single axis can prove difficult—misleading intuition as a consequence of pulling two otherwise disjoint components into focus together. This article examines the challenges of maintaining the simple, concise, and accurate

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Chan, Jennifer S. K., S. T. Boris Choy, and Udi E. Makov. "Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-t Distribution." ASTIN Bulletin 38, no. 01 (2008): 207–30. http://dx.doi.org/10.2143/ast.38.1.2030411.

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This paper presents a Bayesian approach using Markov chain Monte Carlo methods and the generalized-t (GT) distribution to predict loss reserves for the insurance companies. Existing models and methods cannot cope with irregular and extreme claims and hence do not offer an accurate prediction of loss reserves. To develop a more robust model for irregular claims, this paper extends the conventional normal error distribution to the GT distribution which nests several heavy-tailed distributions including the Student-t and exponential power distributions. It is shown that the GT distribution can be

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Chan, Jennifer S. K., S. T. Boris Choy, and Udi E. Makov. "Robust Bayesian Analysis of Loss Reserves Data Using the Generalized-t Distribution." ASTIN Bulletin 38, no. 1 (2008): 207–30. http://dx.doi.org/10.1017/s0515036100015142.

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This paper presents a Bayesian approach using Markov chain Monte Carlo methods and the generalized-t (GT) distribution to predict loss reserves for the insurance companies. Existing models and methods cannot cope with irregular and extreme claims and hence do not offer an accurate prediction of loss reserves. To develop a more robust model for irregular claims, this paper extends the conventional normal error distribution to the GT distribution which nests several heavy-tailed distributions including the Student-t and exponential power distributions. It is shown that the GT distribution can be

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Wang, Ao, Zongkai Zhang, Xiaoming Lei, Ye Xia, and Limin Sun. "All-Weather Thermal Simulation Methods for Concrete Maglev Bridge Based on Structural and Meteorological Monitoring Data." Sensors 21, no. 17 (2021): 5789. http://dx.doi.org/10.3390/s21175789.

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Thermal energy exchange induces non-uniform temperature distribution on the concrete bridge structures, leading to variation of static and dynamic properties of structural systems. The finite element method can facilitate thermal simulation and predict the structural temperature distribution based on heat flow theories. Previous studies mainly focused on the daytime with sunny weather, and the effects of solar shadow distribution were not fully considered or even ignored. In this paper, a systematic all-weather thermal simulation method was proposed to investigate the temperature distributions

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Jeffrey, Benjamin, David M. Aanensen, Nicholas J. Croucher, and Samir Bhatt. "Predicting the future distribution of antibiotic resistance using time series forecasting and geospatial modelling." Wellcome Open Research 5 (August 19, 2020): 194. http://dx.doi.org/10.12688/wellcomeopenres.16153.1.

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Background: Increasing antibiotic resistance in a location may be mitigated by changes in treatment policy, or interventions to limit transmission of resistant bacteria. Therefore, accurate forecasting of the distribution of antibiotic resistance could be advantageous. Two previously published studies addressed this, but neither study compared alternative forecasting algorithms or considered spatial patterns of resistance spread. Methods: We analysed data describing the annual prevalence of antibiotic resistance per country in Europe from 2012 – 2016, and the quarterly prevalence of antibiotic

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Alzeley, Omar, Ehab M. Almetwally, Ahmed M. Gemeay, Huda M. Alshanbari, E. H. Hafez, and M. H. Abu-Moussa. "Statistical Inference under Censored Data for the New Exponential-X Fréchet Distribution: Simulation and Application to Leukemia Data." Computational Intelligence and Neuroscience 2021 (August 29, 2021): 1–16. http://dx.doi.org/10.1155/2021/2167670.

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In reliability studies, the best fitting of lifetime models leads to accurate estimates and predictions, especially when these models have nonmonotone hazard functions. For this purpose, the new Exponential-X Fréchet (NEXF) distribution that belongs to the new exponential-X (NEX) family of distributions is proposed to be a superior fitting model for some reliability models with nonmonotone hazard functions and beat the competitive distribution such as the exponential distribution and Frechet distribution with two and three parameters. So, we concentrated our effort to introduce a new novel mod

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Stojmirović, Aleksandar, and Yi-Kuo Yu. "Robust and accurate data enrichment statistics via distribution function of sum of weights." Bioinformatics 26, no. 21 (2010): 2752–59. http://dx.doi.org/10.1093/bioinformatics/btq511.

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Schumm, Walter R. "How Accurately Could Early (622-900 C.E.) Muslims Determine the Direction of Prayers (Qibla)?" Religions 11, no. 3 (2020): 102. http://dx.doi.org/10.3390/rel11030102.

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Debate has arisen over the ability of Muslim architects in the first two centuries of Islam to determine true qiblas accurately. Some believe that they had such a capability, while others think not. The argument could be more complex—perhaps some architects could, while others could not; perhaps their accuracy changed over time or over greater distances from qibla targets. Here, we investigated how the accurate qiblas of 60 mosques or related structures were, using data from Daniel Gibson’s books and websites. Contrasts were drawn between theories that the qiblas of early mosques were—or were

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Karimi, P., and W. G. M. Bastiaanssen. "Spatial evapotranspiration, rainfall and land use data in water accounting – Part 1: Review of the accuracy of the remote sensing data." Hydrology and Earth System Sciences 19, no. 1 (2015): 507–32. http://dx.doi.org/10.5194/hess-19-507-2015.

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Abstract. The scarcity of water encourages scientists to develop new analytical tools to enhance water resource management. Water accounting and distributed hydrological models are examples of such tools. Water accounting needs accurate input data for adequate descriptions of water distribution and water depletion in river basins. Ground-based observatories are decreasing, and not generally accessible. Remote sensing data is a suitable alternative to measure the required input variables. This paper reviews the reliability of remote sensing algorithms to accurately determine the spatial distrib

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Hennessy, Andrew, Kenneth Clarke, and Megan Lewis. "Generative Adversarial Network Synthesis of Hyperspectral Vegetation Data." Remote Sensing 13, no. 12 (2021): 2243. http://dx.doi.org/10.3390/rs13122243.

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New, accurate and generalizable methods are required to transform the ever-increasing amount of raw hyperspectral data into actionable knowledge for applications such as environmental monitoring and precision agriculture. Here, we apply advances in generative deep learning models to produce realistic synthetic hyperspectral vegetation data, whilst maintaining class relationships. Specifically, a Generative Adversarial Network (GAN) is trained using the Cramér distance on two vegetation hyperspectral datasets, demonstrating the ability to approximate the distribution of the training samples. Ev

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Menzel, Peter. "Constrained indicator data resampling — A parameter constrained irregular resampling method for scattered point data." GEOPHYSICS 81, no. 2 (2016): F17—F26. http://dx.doi.org/10.1190/geo2015-0220.1.

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Resampling of high-resolution data sets is often required for real-time applications in geosciences, e.g., interactive modeling and 3D visualization. To support interactivity and real-time computations, it is often necessary to resample the data sets to a resolution adequate to the application. Conventional resampling approaches create uniformly distributed results, which are not always the best possible solution for particular applications. I have developed a new resampling method called constrained indicator data resampling (CIDRe). This method results in irregular point distributions that a

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Feng, Jie, Yong Li, Fengli Xu, and Depeng Jin. "A Bimodal Model to Estimate Dynamic Metropolitan Population by Mobile Phone Data." Sensors 18, no. 10 (2018): 3431. http://dx.doi.org/10.3390/s18103431.

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Accurate, real-time and fine-spatial population distribution is crucial for urban planning, government management, and advertisement promotion. Limited by technics and tools, we rely on the census to obtain this information in the past, which is coarse and costly. The popularity of mobile phones gives us a new opportunity to investigate population estimation. However, real-time and accurate population estimation is still a challenging problem because of the coarse localization and complicated user behaviors. With the help of the passively collected human mobility and locations from the mobile

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Jung, Chol-Hee, Daniel Park, Peter Georgeson, et al. "sEst: Accurate Sex-Estimation and Abnormality Detection in Methylation Microarray Data." International Journal of Molecular Sciences 19, no. 10 (2018): 3172. http://dx.doi.org/10.3390/ijms19103172.

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DNA methylation influences predisposition, development and prognosis for many diseases, including cancer. However, it is not uncommon to encounter samples with incorrect sex labelling or atypical sex chromosome arrangement. Sex is one of the strongest influencers of the genomic distribution of DNA methylation and, therefore, correct assignment of sex and filtering of abnormal samples are essential for the quality control of study data. Differences in sex chromosome copy numbers between sexes and X-chromosome inactivation in females result in distinctive sex-specific patterns in the distributio

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Zhirnov, A. A., and O. B. Kudrjashova. "Peculiarities of data processing for optical measurements of disperse parameters of bimodal media." Computer Optics 43, no. 4 (2019): 692–98. http://dx.doi.org/10.18287/2412-6179-2019-43-4-692-698.

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This study is focused on enhancing the informativity of optical measurement techniques for particulate matter. The problem is that the description of particulate matter with bimodal and multimodal distributions by an a priori defined analytical function of particle size distribution (for example, a log-normal distribution) is not accurate enough. Here, we explore if experimental data can be approximated by a multivariable function of particle size distribution instead of using the a priori defined log-normal distribution. For the comparison of the approximation results, experiments are conduct

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Zhao, Licheng, Yun Shi, Bin Liu, Ciara Hovis, Yulin Duan, and Zhongchao Shi. "Finer Classification of Crops by Fusing UAV Images and Sentinel-2A Data." Remote Sensing 11, no. 24 (2019): 3012. http://dx.doi.org/10.3390/rs11243012.

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Accurate crop distribution maps provide important information for crop censuses, yield monitoring and agricultural insurance assessments. Most existing studies apply low spatial resolution satellite images for crop distribution mapping, even in areas with a fragmented landscape. Unmanned aerial vehicle (UAV) imagery provides an alternative imagery source for crop mapping, yet its spectral resolution is usually lower than satellite images. In order to produce more accurate maps without losing any spatial heterogeneity (e.g., the physical boundary of land parcel), this study fuses Sentinel-2A an

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Smith, Bruce R., Christophe M. Herbinger, and Heather R. Merry. "Accurate Partition of Individuals Into Full-Sib Families From Genetic Data Without Parental Information." Genetics 158, no. 3 (2001): 1329–38. http://dx.doi.org/10.1093/genetics/158.3.1329.

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Abstract Two Markov chain Monte Carlo algorithms are proposed that allow the partitioning of individuals into full-sib groups using single-locus genetic marker data when no parental information is available. These algorithms present a method of moving through the sibship configuration space and locating the configuration that maximizes an overall score on the basis of pairwise likelihood ratios of being full-sib or unrelated or maximizes the full joint likelihood of the proposed family structure. Using these methods, up to 757 out of 759 Atlantic salmon were correctly classified into 12 full-s

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Ito, T., T. Kato, K. Takagishi, S. Okabe, and D. Sano. "Bayesian modeling of virus removal efficiency in wastewater treatment processes." Water Science and Technology 72, no. 10 (2015): 1789–95. http://dx.doi.org/10.2166/wst.2015.402.

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Left-censored datasets of virus density in wastewater samples make it difficult to evaluate the virus removal efficiency in wastewater treatment processes. In the present study, we modeled the probabilistic distribution of virus removal efficiency in a wastewater treatment process with a Bayesian approach, and investigated how many detect samples in influent and effluent are necessary for accurate estimation. One hundred left-censored data of virus density in wastewater (influent and effluent) were artificially generated based on assumed log-normal distributions and the posterior predictive di

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Tomz, Michael, Joshua A. Tucker, and Jason Wittenberg. "An Easy and Accurate Regression Model for Multiparty Electoral Data." Political Analysis 10, no. 1 (2002): 66–83. http://dx.doi.org/10.1093/pan/10.1.66.

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Katz and King have previously proposed a statistical model for multiparty election data. They argue that ordinary least-squares (OLS) regression is inappropriate when the dependent variable measures the share of the vote going to each party, and they recommend a superior technique. Regrettably, the Katz-King model requires a high level of statistical expertise and is computationally demanding for more than three political parties. We offer a sophisticated yet convenient alternative that involves seemingly unrelated regression (SUR). SUR is nearly as easy to use as OLS yet performs as well as t

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Löhner, Rainald, and Harbir Antil. "Determination of volumetric material data from boundary measurements." International Journal of Numerical Methods for Heat & Fluid Flow 30, no. 11 (2020): 4837–63. http://dx.doi.org/10.1108/hff-12-2019-0931.

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Purpose The purpose of this study is to determine the possibility of an accurate assessment of the spatial distribution of material properties such as conductivities or impedances from boundary measurements when the governing partial differential equation is a Laplacian. Design/methodology/approach A series of numerical experiments were carefully performed. The results were analyzed and compared. Findings The results to date show that while the optimization procedure is able to obtain spatial distributions of the conductivity k that reduce the cost function significantly, the resulting conduct

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Yoneda, Kiyoshi. "Elevator Trip Distribution for Inconsistent Passenger Input-Output Data." Decision Making in Manufacturing and Services 1, no. 2 (2007): 175–90. http://dx.doi.org/10.7494/dmms.2007.1.2.175.

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Accurate traffic data are the basis for group control of elevators and its performance evaluation by trace driven simulation. The present practice estimates a time series of inter-floor passenger traffic based on commonly available elevator sensor data. The method demands that the sensor data be transformed into sets of passenger input-output data which are consistent in the sense that the transportation preserves the number of passengers. Since observation involves various behavioral assumptions, which may actually be violated, as well as measurement errors, it has been necessary to apply dat

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Gayrard, Emeline, Cédric Chauvière, Hacène Djellout, and Pierre Bonnet. "MODELING EXPERIMENTAL DATA WITH POLYNOMIALS CHAOS." Probability in the Engineering and Informational Sciences 34, no. 1 (2018): 14–26. http://dx.doi.org/10.1017/s026996481800030x.

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Given a raw data sample, the purpose of this paper is to design a numerical procedure to model this sample under the form of polynomial chaos expansion. The coefficients of the polynomial are computed as the solution to a constrained optimization problem. The procedure is first validated on samples coming from a known distribution and it is then applied to raw experimental data of unknown distribution. Numerical experiments show that only five coefficients of the Chaos expansions are required to get an accurate representation of a sample.

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Juba, Brendan, and Hengxuan Li. "More Accurate Learning of k-DNF Reference Classes." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 4385–93. http://dx.doi.org/10.1609/aaai.v34i04.5864.

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In machine learning, predictors trained on a given data distribution are usually guaranteed to perform well for further examples from the same distribution on average. This often may involve disregarding or diminishing the predictive power on atypical examples; or, in more extreme cases, a data distribution may be composed of a mixture of individually “atypical” heterogeneous populations, and the kind of simple predictors we can train may find it difficult to fit all of these populations simultaneously. In such cases, we may wish to make predictions for an atypical point by selecting a suitabl

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Khan, I., D. Shan, and Q. Li. "Modal Parameter Identification Of Cable Stayed Bridge Based On Exploratory Data Analysis." Archives of Civil Engineering 61, no. 2 (2015): 3–22. http://dx.doi.org/10.1515/ace-2015-0011.

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AbstractIn order to identify the modal parameters of civil structures it is vital to distinguish the defective data from that of appropriate and accurate data. The defects in data may be due to various reasons like defects in the data collection, malfunctioning of sensors, etc. For this purpose Exploratory Data Analysis (EDA) was engaged to envisage the distribution of sensor’s data and to detect the malfunctioning with in the sensors. Then outlier analysis was performed to remove those data points which may disrupt the accurate data analysis. Then Data Driven Stochastic Sub-space Identificati

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Mao, Yeying, Zhengyu Huang, Changsen Feng, Hui Chen, Qiming Yang, and Junchang Ma. "An Early Warning Method of Distribution System Fault Risk Based on Data Mining." Mathematical Problems in Engineering 2020 (December 2, 2020): 1–10. http://dx.doi.org/10.1155/2020/8880661.

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Accurate warning information of potential fault risk in the distribution network is essential to the economic operation as well as the rational allocation of maintenance resources. In this paper, we propose a fault risk warning method for a distribution system based on an improved RelieF-Softmax algorithm. Firstly, four categories including 24 fault features of the distribution system are determined through data investigation and preprocessing. Considering the frequency of distribution system faults, and then their consequences, the risk classification method of the distribution system is pres

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Ward, M. J., and A. M. Zambone. "The U.S. Federal Data-Collection Process for Children and Youths who are Deaf-Blind." Journal of Visual Impairment & Blindness 86, no. 10 (1992): 429–34. http://dx.doi.org/10.1177/0145482x9208601006.

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Obtaining accurate counts of children who are deaf-blind is important for planning resource distribution and program development and implementation. Yet accuracy has been difficult to achieve for a number of reasons. This article reports the results of policy research that examined various strategies implemented by the U.S. federal government to obtain data on child counts and the issues related to this effort and its outcomes.

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Myles, JP, GM Price, N. Hunter, M. Day, and SW Duffy. "A potentially useful distribution model for dietary intake data." Public Health Nutrition 6, no. 5 (2003): 513–19. http://dx.doi.org/10.1079/phn2003459.

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AbstractBackground:Conventional mixed models for the analysis of diet diary data have introduced several simplifying assumptions, such as that of a single standard deviation for within-person day-to-day variation which is common to all individuals.Objective:We developed a model in which the within-person standard deviation was allowed to differ from person to person.Design:The model was demonstrated using data on daily retinol intake from the Dietary and Nutritional Survey of British Adults. The data were from 7-day weighed dietary diaries. Estimation was performed by Markov chain Monte Carlo.

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Angelliaume, Sébastien, Luke Rosenberg, and Matthew Ritchie. "Modeling the Amplitude Distribution of Radar Sea Clutter." Remote Sensing 11, no. 3 (2019): 319. http://dx.doi.org/10.3390/rs11030319.

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Ship detection in the maritime domain is best performed with radar due to its ability to surveil wide areas and operate in almost any weather condition or time of day. Many common detection schemes require an accurate model of the amplitude distribution of radar echoes backscattered by the ocean surface. This paper presents a review of select amplitude distributions from the literature and their ability to represent data from several different radar systems operating from 1 GHz to 10 GHz. These include the K distribution, arguably the most popular model from the literature as well as the Paret

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Bailey, James M., and Keith M. Gregg. "A Technique for Population Pharmacodynamic Analysis of Concentration-Binary Response Data." Anesthesiology 86, no. 4 (1997): 825–35. http://dx.doi.org/10.1097/00000542-199704000-00013.

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Background Pharmacodynamic data frequently consist of the binary assessment (a "yes" or "no" answer) of the response to a defined stimulus (verbal stimulus, intubation, skin incision, and so on) for multiple patients. The concentration-effect relation is usually reported in terms of C50, the drug concentration associated with a 50% probability of drug effect, and a parameter the authors denote gamma, which determines the shape of the concentration-probability of effect curve. Accurate estimation of gamma, a parameter describing the entire curve, is as important as the estimation of C50, a sing

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Chen, Y., Z. Liu, W. Zhang, C. Qiao, and H. Gu. "EXTRACTION OF LEAF ANGLE DISTRIBUTION FROM AN INDIVIDUAL BROADLEAF TREE USING TERRESTRIAL LASER SCANNING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 957–62. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-957-2019.

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<p><strong>Abstract.</strong> The angular distribution of leaves is a key vegetation structural parameter for evaluating the reflection and transmission of solar radiation through vegetation canopies. Accurate extraction of Leaf Angle Distribution (LAD) is of great importance in estimating other vegetation structural parameters such as the canopy clumping and leaf area index. However, field measurement of LAD is time-consuming, labour-intensive and subjective. In most studies, LAD is assumed to follow the spherical distribution assumption within canopy which may lead to consi

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Jargowsky, Paul A., and Christopher A. Wheeler. "Estimating Income Statistics from Grouped Data: Mean-constrained Integration over Brackets." Sociological Methodology 48, no. 1 (2018): 337–74. http://dx.doi.org/10.1177/0081175018782579.

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Researchers studying income inequality, economic segregation, and other subjects must often rely on grouped data—that is, data in which thousands or millions of observations have been reduced to counts of units by specified income brackets. The distribution of households within the brackets is unknown, and highest incomes are often included in an open-ended top bracket, such as “$200,000 and above.” Common approaches to this estimation problem include calculating midpoint estimators with an assumed Pareto distribution in the top bracket and fitting a flexible multiple-parameter distribution to

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Yang, Yixin, Xin Lü, Jian Ma, and Han Qiao. "A Robust Factor Analysis Model for Dichotomous Data." Journal of Systems Science and Information 2, no. 5 (2014): 437–50. http://dx.doi.org/10.1515/jssi-2014-0437.

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AbstractFactor analysis is widely used in psychology, sociology and economics, as an analytically tractable method of reducing the dimensionality of the data in multivariate statistical analysis. The classical factor analysis model in which the unobserved factor scores and errors are assumed to follow the normal distributions is often criticized because of its lack of robustness. This paper introduces a new robust factor analysis model for dichotomous data by using robust distributions such as multivariatet-distribution. After comparing the fitting results of the normal factor analysis model a

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Jiao, Tan, Xue Hui Wen, and Xiang Wang. "Study on Probability Distribution Models of the Subgrade Continuous Compaction Indicator." Applied Mechanics and Materials 438-439 (October 2013): 1060–64. http://dx.doi.org/10.4028/www.scientific.net/amm.438-439.1060.

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The paper based on the site of a subgrade compaction test data, used the continuous compaction indicator CMV as the analysis variable, filtered the date based on the influencing factors of CMV, and used the common probability models for statistical analysis,finally got the probability distribution models with which the CMV data comply, then chose the most accurate distribution model. The result showed that the lognormal distribution was the most accurate distribution. After being examined in two other test sections, the lognormal distribution was also the most accurate distribution. It provide

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Häussling Löwgren, Bartolomeus, Joris Weigert, Erik Esche, and Jens-Uwe Repke. "Uncertainty Analysis for Data-Driven Chance-Constrained Optimization." Sustainability 12, no. 6 (2020): 2450. http://dx.doi.org/10.3390/su12062450.

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In this contribution our developed framework for data-driven chance-constrained optimization is extended with an uncertainty analysis module. The module quantifies uncertainty in output variables of rigorous simulations. It chooses the most accurate parametric continuous probability distribution model, minimizing deviation between model and data. A constraint is added to favour less complex models with a minimal required quality regarding the fit. The bases of the module are over 100 probability distribution models provided in the Scipy package in Python, a rigorous case-study is conducted sel

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Cheng, Weiping, Gang Xu, Hongji Fang, and Dandan Zhao. "Study on Pipe Burst Detection Frame Based on Water Distribution Model and Monitoring System." Water 11, no. 7 (2019): 1363. http://dx.doi.org/10.3390/w11071363.

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This paper describes an infrastructure to detect burst events in a water distribution network, which we illustrate using the Guangzhou water distribution system (WDS). We consider three issues: The feasibility and capability of accurate detection, the layout and design of the monitoring infrastructure, and the burst event detection algorithm. Background noise is identified by analyzing the monitored data. A burst event can be accurately detected only when the impact of the burst can be differentiated from the background noise. We hypothesize that there is a minimum pipe diameter below which ac

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Yu, Sheng, Yumeng Ma, Jessica Gronsbell, et al. "Enabling phenotypic big data with PheNorm." Journal of the American Medical Informatics Association 25, no. 1 (2017): 54–60. http://dx.doi.org/10.1093/jamia/ocx111.

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Abstract Objective Electronic health record (EHR)-based phenotyping infers whether a patient has a disease based on the information in his or her EHR. A human-annotated training set with gold-standard disease status labels is usually required to build an algorithm for phenotyping based on a set of predictive features. The time intensiveness of annotation and feature curation severely limits the ability to achieve high-throughput phenotyping. While previous studies have successfully automated feature curation, annotation remains a major bottleneck. In this paper, we present PheNorm, a phenotypi

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Dmowska, Anna, and Tomasz F. Stepinski. "Racial Dot Maps Based on Dasymetrically Modeled Gridded Population Data." Social Sciences 8, no. 5 (2019): 157. http://dx.doi.org/10.3390/socsci8050157.

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Racial geography, mapping spatial distributions of different racial groups, is of keen interest in a multiracial society like the United States. A racial dot map is a method of visualizing racial geography, which depicts spatial distribution, population density, and racial mix in a single, easy-to-understand map. Because of the richness of information it carries, the dot map is an excellent tool for visual analysis of racial distribution. Presently-used racial dot maps are based on the Census data at the tract or the block level. In this paper, we present a method of constructing a more spatia

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