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Journal articles on the topic 'Bayes's method'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Wahyunita, Laili. "Klasifikasi Penyebab Penyalahgunaan Narkoba Dari Berita Online Dengan Menggunakan Naive Bayes." Jurnal ELTIKOM 1, no. 1 (2017): 23–30. http://dx.doi.org/10.31961/eltikom.v1i1.12.

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This research conducted the classification process by applying the method of classification of Naive Bayes. News article document is one form of text data that is not structured so that requires the process of cleaning data and pre-processing first. The Naive Bayes approach is an approach that refers to Bayes's Theorem, where it uses the principle of statistical opportunity to combine previous knowledge. The use of this technique is based on the need of the system to know the probability value of the data to be classified. Waterfall method was used for built this classificaiton system. Accurac

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Utyuganova, V. V., V. S. Serdyuk, and A. I. Fomin. "Prediction and Assessment of the Occupational Risks in the Mining Industry Using the Bayess Theorem." Occupational Safety in Industry, no. 1 (January 2021): 79–87. http://dx.doi.org/10.24000/0409-2961-2021-1-79-87.

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The analysis of existing methods for assessing occupational risks is carried out, and the need for searchinga fundamentally new approach to the assessment and prediction of risks in the mining industry is substantiated. Based on the results of the analysis of modern methods and technologies, it is established that the development of the methodology for assessment and prediction of the occupational risks using Bayes's theorem has significant advantages: simplicity and accessibility for the occupational safety specialists, reproducibility considering many factors of working conditions, as well a

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Zavadskas, Edmundas Kazimieras, Leonas Ustinovičius, Zenonas Turskis, Friedel Peldschus, and Danny Messing. "LEVI 3.0—MULTIPLE CRITERIA EVALUATION PROGRAM FOR CONSTRUCTION SOLUTIONS." JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 8, no. 3 (2002): 184–91. http://dx.doi.org/10.3846/13923730.2002.10531275.

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The paper considers the main methods employed to solve one-sided and two-sided problems of the game theory. For the one-sided problems only the method of solution “distance to the ideal point” is discussed. For the two-sided problems a distinction is made between games with rational behaviour and games against nature. The main principles of the strategies are as follows: simple min-max principle, extended min-max principle, Wald's rule, Savage criterion, Hurwicz's rule, Laplace's rule, Bayes's rule, Hodges-Lehmann rule. The questions transforming the decisionmaking matrix are considered: vecto

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Imai, Kosuke, and Kabir Khanna. "Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records." Political Analysis 24, no. 2 (2016): 263–72. http://dx.doi.org/10.1093/pan/mpw001.

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In both political behavior research and voting rights litigation, turnout and vote choice for different racial groups are often inferred using aggregate election results and racial composition. Over the past several decades, many statistical methods have been proposed to address this ecological inference problem. We propose an alternative method to reduce aggregation bias by predicting individual-level ethnicity from voter registration records. Building on the existing methodological literature, we use Bayes's rule to combine the Census Bureau's Surname List with various information from geoco

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Jevning, R., R. Anand, and M. Biedebach. "Certainty and uncertainty in science: the subjectivistic concept of probability in physiology and medicine." Advances in Physiology Education 267, no. 6 (1994): S113. http://dx.doi.org/10.1152/advances.1994.267.6.s113.

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Most physiological scientists have restricted understanding of probability as relative frequency in a large collection (for example, of atoms). Most appropriate for the relatively circumscribed problems of the physical sciences, this understanding of probability as a physical property has conveyed the widespread impression that the "proper" statistical "method" can eliminate uncertainty by determining the "correct" frequency or frequency distribution. However, many relatively recent developments in the theory of probability and decision making deny such exalted statistical ability. Proponents

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Pang, Xun. "Modeling Heterogeneity and Serial Correlation in Binary Time-Series Cross-sectional Data: A Bayesian Multilevel Model with AR(p) Errors." Political Analysis 18, no. 4 (2010): 470–98. http://dx.doi.org/10.1093/pan/mpq019.

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This paper proposes a Bayesian generalized linear multilevel model with apth-order autoregressive error process to analyze unbalanced binary time-series cross-sectional (TSCS) data. The model specification is motivated by the generic TSCS data structure and is intended to handle the associated inefficiency and endogeneity problems. It accommodates heterogeneity across units and between time periods in the form of random intercepts and random-effect coefficients. At the same time, itspth-order autoregressive error process, employed either by itself or in concert with other dynamic methods, adeq

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Legiawati, Nenden, Teguh Iman Hermanto, and Yudhi Raymond Ramadhan. "Analisis Sentimen Opini Pengguna Twitter Terhadap Perusahaan Jasa Ekspedisi Menggunakan Algoritma Naïve Bayes Berbasis PSO." JURIKOM (Jurnal Riset Komputer) 9, no. 4 (2022): 930. http://dx.doi.org/10.30865/jurikom.v9i4.4629.

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Expeditions are used in the process of delivering goods or selling them remotely. Twitter has become a social media for information sharing and opinions, including those on the expeditionary services both negative and positive. The solution for the problem which occurs is that of sentiment analysis, helpful in grouping the data and predicting the tweet. The aim of the research to predict sentient tweeted data using a file classification method, naive bayes's algorithm calculated the value of the tweets of the Anteraja expedition service that had the results accuracy 87,77%, precision 76,67%, r

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Peter, Justin R., Alan Seed, and Peter J. Steinle. "Application of a Bayesian Classifier of Anomalous Propagation to Single-Polarization Radar Reflectivity Data." Journal of Atmospheric and Oceanic Technology 30, no. 9 (2013): 1985–2005. http://dx.doi.org/10.1175/jtech-d-12-00082.1.

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Abstract A naïve Bayes classifier (NBC) was developed to distinguish precipitation echoes from anomalous propagation (anaprop). The NBC is an application of Bayes's theorem, which makes its classification decision based on the class with the maximum a posteriori probability. Several feature fields were input to the Bayes classifier: texture of reflectivity (TDBZ), a measure of the reflectivity fluctuations (SPIN), and vertical profile of reflectivity (VPDBZ). Prior conditional probability distribution functions (PDFs) of the feature fields were constructed from training sets for several meteor

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Harries, R. W. J. "A Rational Approach to Radiological Screening in Von Hippel-Lindau Disease." Journal of Medical Screening 1, no. 2 (1994): 88–95. http://dx.doi.org/10.1177/096914139400100205.

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Objectives— To optimise radiological screening in von Hippel-Lindau disease (VHL) while minimising cost and morbidity. Methods— A model of VHL was based on retrospective studies, and Bayes's theorem used to calculate the probability of the gene's presence and the likelihood of further lesions in affected families. A six year follow up was conducted to test the validity of the model. Results— Follow up confirmed the accuracy and validity of the model. Posterior fossa haemangioblastomas occur in 79·2% of VHL cases, supratentorial, retinal and spinal haemangioblastomas in 6·9%, 42·8%, and 22·0%,

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Lee, Kyeongjun. "Bayes and Maximum Likelihood Estimation of Uncertainty Measure of the Inverse Weibull Distribution under Generalized Adaptive Progressive Hybrid Censoring." Mathematics 10, no. 24 (2022): 4782. http://dx.doi.org/10.3390/math10244782.

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The inverse Weibull distribution (IWD) can be applied to a various situations, including applications in reliability and medicine. In a reliability and medicine test, it is generally known that the results of test units may not be recorded. Recently, the generalized adaptive progressive hybrid censoring (GAPHC) scheme was introduced. In this paper, therefore, we consider the classical estimators (maximum likelihood estimator (MLE) and maximum product spacings estimator (MPSE)) and Bayes estimators (BayEsts) of the uncertainty measure of the IWD under GAPHC scheme. We derive the BayEsts of the

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Hodyss, Daniel, Elizabeth Satterfield, Justin McLay, Thomas M. Hamill, and Michael Scheuerer. "Inaccuracies with Multimodel Postprocessing Methods Involving Weighted, Regression-Corrected Forecasts." Monthly Weather Review 144, no. 4 (2016): 1649–68. http://dx.doi.org/10.1175/mwr-d-15-0204.1.

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Abstract Ensemble postprocessing is frequently applied to correct biases and deficiencies in the spread of ensemble forecasts. Methods involving weighted, regression-corrected forecasts address the typical biases and underdispersion of ensembles through a regression correction of ensemble members followed by the generation of a probability density function (PDF) from the weighted sum of kernels fit around each corrected member. The weighting step accounts for the situation where the ensemble is constructed from different model forecasts or generated in some way that creates ensemble members th

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Sokolov, Vladimir Alekseevich. "Probabilistic Analysis of Intermediate Floor Steel and Wooden Structures in the Old Urban Development Building." Applied Mechanics and Materials 633-634 (September 2014): 1140–47. http://dx.doi.org/10.4028/www.scientific.net/amm.633-634.1140.

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The article suggests an approach to determine structural elements technical condition, based on the mathematical probabilistic apparatus of technical diagnostics. Diagnostics are performed using probabilistic methods of complex technical systems conditions recognition. Probabilistic parameters are calculated according to Bayes’s rule. The paper shows a diagnostics example of intermediate floor elements and systems in the old urban development building. Both the suggested method and information theory methods are used during diagnostics.

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Antuchevičienė, Jurgita, Zenonas Turskis, and Edmundas Kazimieras Zavadskas. "MODELLING RENEWAL OF CONSTRUCTION OBJECTS APPLYING METHODS OF THE GAME THEORY." Technological and Economic Development of Economy 12, no. 4 (2006): 263–68. http://dx.doi.org/10.3846/13928619.2006.9637752.

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The paper analyses modelling renewal of construction objects applying methods of the game theory. Rational construction management variants are usually selected under various conditions, using the efficiency criteria. A choice of rational alternatives can be absolutely uncertain when influences of external factors are unknown. In the current paper, selecting of rational renewal variants of derelict buildings from the viewpoint of sustainable development is presented. Sustainable development always involves great uncertainty; accordingly, the methods of the Game Theory are used for a particular

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Pereira, Geraldo Magela da Cruz, Andrew de Paula Ribeiro та Sebastião Martins Filho. "Genomic prediction of ordinal traits via application of the BLASSO and BayesCπ methods in simulated data". Multi-Science Journal 3, № 1 (2020): 1. http://dx.doi.org/10.33837/msj.v3i1.1112.

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This paper aims at evaluating the use of BLASSO and BayesCπ methods for the genomic prediction of ordinal traits, studying factors that influence the performance of the models, and if there is a difference in the ranking of individuals. Genotypic and phenotypic information from a simulated population of 4,100 animals, genotyped by 10k markers (QTL-MAS Workshop) were used. 3,000 animals were used for estimation of the predictive ability and bias accessed through 5-fold cross-validation with five repetitions. The other animals were used as a population of selection. One ANOVA and the Ryan-Einot-

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Ya’acob, Norsuzila, Nik Nur Shaadah Nik Dzulkefli, Mohd Azri Abdul Aziz, Azita Laily Yusof, and Roslan Umar. "A review on features and methods of potential fishing zone." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 3 (2024): 2508. http://dx.doi.org/10.11591/ijece.v14i3.pp2508-2521.

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This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current

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Norsuzila, Ya'acob, Nur Shaadah Nik Dzulkefli Nik, Azri Abdul Aziz Mohd, Laily Yusof Azita, and Umar Roslan. "A review on features and methods of potential fishing zone." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 3 (2024): 2508–21. https://doi.org/10.11591/ijece.v14i3.pp2508-2521.

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This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current

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Shao-Jing, Dong, Zhang Jian-Bo, and Ying He-Ping. "Empirical Baye's Method and Roper Resonance State in Very Light Quark Region." Chinese Physics Letters 20, no. 5 (2003): 626–28. http://dx.doi.org/10.1088/0256-307x/20/5/310.

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18

Nakabayashi, Akio, and Genta Ueno. "An Extension of the Ensemble Kalman Filter for Estimating the Observation Error Covariance Matrix Based on the Variational Bayes’s Method." Monthly Weather Review 145, no. 1 (2016): 199–213. http://dx.doi.org/10.1175/mwr-d-16-0139.1.

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Abstract This paper presents an extension of the ensemble Kalman filter (EnKF) that can simultaneously estimate the state vector and the observation error covariance matrix by using the variational Bayes’s (VB) method. In numerical experiments, this capability is examined for a time-variant observation error covariance matrix, and it is noteworthy that this method works well even when the true observation error covariance matrix is nondiagonal. In addition, two complementary studies are presented. First, the stability of a long-run assimilation is demonstrated when there are unmodeled disturba

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Kubade, Harshad M. "The Overview of Bayes Classification Methods." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 2801–2. http://dx.doi.org/10.31142/ijtsrd15750.

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Karaman, Emre, Mogens S. Lund, and Guosheng Su. "Multi-trait single-step genomic prediction accounting for heterogeneous (co)variances over the genome." Heredity 124, no. 2 (2019): 274–87. http://dx.doi.org/10.1038/s41437-019-0273-4.

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Abstract Widely used genomic prediction models may not properly account for heterogeneous (co)variance structure across the genome. Models such as BayesA and BayesB assume locus-specific variance, which are highly influenced by the prior for (co)variance of single nucleotide polymorphism (SNP) effect, regardless of the size of data. Models such as BayesC or GBLUP assume a common (co)variance for a proportion (BayesC) or all (GBLUP) of the SNP effects. In this study, we propose a multi-trait Bayesian whole genome regression method (BayesN0), which is based on grouping a number of predefined SNP

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Grant, Robert L., Daniel C. Furr, Bob Carpenter, and Andrew Gelman. "Fitting Bayesian item response models in Stata and Stan." Stata Journal: Promoting communications on statistics and Stata 17, no. 2 (2017): 343–57. http://dx.doi.org/10.1177/1536867x1701700206.

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Stata users have access to two easy-to-use implementations of Bayesian inference: Stata's native bayesmh command and StataStan, which calls the general Bayesian engine, Stan. We compare these implementations on two important models for education research: the Rasch model and the hierarchical Rasch model. StataStan fits a more general range of models than can be fit by bayesmh and uses a superior sampling algorithm, that is, Hamiltonian Monte Carlo using the no-U-turn sampler. Furthermore, StataStan can run in parallel on multiple CPU cores, regardless of the flavor of Stata. Given these advant

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赵, 燕. "A Improvement Method of Bayes Bootstrap." Statistics and Application 11, no. 05 (2022): 1264–69. http://dx.doi.org/10.12677/sa.2022.115131.

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Alhayali, Royida A. Ibrahem, Munef Abdullah Ahmed, Yasmin Makki Mohialden, and Ahmed H. Ali. "Efficient method for breast cancer classification based on ensemble hoffeding tree and naïve Bayes." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 2 (2020): 1074. http://dx.doi.org/10.11591/ijeecs.v18.i2.pp1074-1080.

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<p><span>The most dangerous type of cancer suffered by women above 35 years of age is breast cancer. Breast Cancer datasets are normally characterized by missing data, high dimensionality, non-normal distribution, class imbalance, noisy, and inconsistency. Classification is a machine learning (ML) process which has a significant role in the prediction of outcomes, and one of the outstanding supervised classification methods in data mining is Naives Bayess Classification (NBC). Naïve Bayes Classifications is good at predicting outcomes and often outperforms other classifications tec

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Royida, A. Ibrahem Alhayali, Abdullah Ahmed Munef, Makki Mohialden Yasmin, and H. Ali Ahmed. "Efficient method for breast cancer classification based on ensemble hoffeding tree and naïve Bayes." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 2 (2020): 1074–80. https://doi.org/10.11591/ijeecs.v18.i2.pp1074-1080.

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The most dangerous type of cancer suffered by women above 35 years of age is breast cancer. Breast Cancer datasets are normally characterized by missing data, high dimensionality, non-normal distribution, class imbalance, noisy, and inconsistency. Classification is a machine learning (ML) process which has a significant role in the prediction of outcomes, and one of the outstanding supervised classification methods in data mining is Naives Bayess Classification (NBC). Naïve Bayes Classifications is good at predicting outcomes and often outperforms other classifications techniques. Ones of

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Dong, S. J., T. Draper, I. Horvath, F. X. Lee, Nilmani Mathur, and J. B. Zhang. "Empirical Baye's method and tests in very light quark range from the overlap lattice QCD." Nuclear Physics B - Proceedings Supplements 119 (May 2003): 248–50. http://dx.doi.org/10.1016/s0920-5632(03)01516-0.

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Harsehanto, Ireicca Agustiorini, and M. Didik R. Wahyudi. "Analysis of Personality Characteristic Using the Naïve Bayess Classifier Algorithm (Case Study Official Twitter of Basuki Tjahaja Purnama's and Anies Baswedan)." IJID (International Journal on Informatics for Development) 7, no. 2 (2019): 14. http://dx.doi.org/10.14421/ijid.2018.07203.

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Abstract - This research uses data from social media Twitter based on the results of tweets from user_timeline @basuki_btp and @aniesbaswedan. This study uses 2100 tweet data. Data that has been collected is then pre-processed first and labeled manually. The next process is classification using the Naïve Bayess Classifier Algorithm using the Big Five Personality Theory. Based on the test results using 500 tweet data as training data and 1600 tweet data as testing data. The classification results obtained by using the Naïve Bayes Classifier Method and grouped in the "Big Five" personality group

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Lu, Kezhong, Xiaohua Xiang, Dian Zhang, Rui Mao, and Yuhong Feng. "Localization Algorithm Based on Maximum a Posteriori in Wireless Sensor Networks." International Journal of Distributed Sensor Networks 8, no. 1 (2011): 260302. http://dx.doi.org/10.1155/2012/260302.

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Many applications and protocols in wireless sensor networks need to know the locations of sensor nodes. A low-cost method to localize sensor nodes is to use received signal strength indication (RSSI) ranging technique together with the least-squares trilateration. However, the average localization error of this method is large due to the large ranging error of RSSI ranging technique. To reduce the average localization error, we propose a localization algorithm based on maximum a posteriori. This algorithm uses the Baye's formula to deduce the probability density of each sensor node's distribut

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Alroy, John. "On a conservative Bayesian method of inferring extinction." Paleobiology 42, no. 4 (2016): 670–79. http://dx.doi.org/10.1017/pab.2016.12.

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AbstractFew methods exist that put a posterior probability on the hypothesis that a thing is gone forever given its sighting history. A recently proposed Bayesian method is highly accurate but aggressive, generating many near-zero or near-one probabilities of extinction. Here I explore a Bayesian method called the agnostic equation that makes radically different assumptions and is much more conservative. The method assumes that the overall prior probability of extinction is 50% and that slices of the prior are exponentially distributed across the time series. The conditional probability of the

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Shagidullin, A. R., Yu A. Tunakova, S. V. Novikova, and V. S. Valiev. "Modeling the integral risk assessment for air pollution in the areas of highways by probabilistic methods." Journal of Physics: Conference Series 2134, no. 1 (2021): 012001. http://dx.doi.org/10.1088/1742-6596/2134/1/012001.

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Abstract A methodology for calculating the integral risk of atmospheric pollution using Bayes’s theorem is proposed to take into account the action of mobile and stationary emission sources in the influence zones of highways, the response to the impact in the form of accumulation of emission components in depositing media and biological media of the population. At the first stage, the clustering of experimental data arrays was carried out, homogeneous road sections (clusters) were identified. The integral risk was calculated for the selected clusters. The risks of contamination of the investig

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Scheuerer, Michael, Scott Gregory, Thomas M. Hamill, and Phillip E. Shafer. "Probabilistic Precipitation-Type Forecasting Based on GEFS Ensemble Forecasts of Vertical Temperature Profiles." Monthly Weather Review 145, no. 4 (2017): 1401–12. http://dx.doi.org/10.1175/mwr-d-16-0321.1.

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Abstract A Bayesian classification method for probabilistic forecasts of precipitation type is presented. The method considers the vertical wet-bulb temperature profiles associated with each precipitation type, transforms them into their principal components, and models each of these principal components by a skew normal distribution. A variance inflation technique is used to de-emphasize the impact of principal components corresponding to smaller eigenvalues, and Bayes’s theorem finally yields probability forecasts for each precipitation type based on predicted wet-bulb temperature profiles.

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Sunandi, Etis, Khairil Anwar Notodiputro, and Bagus Sartono. "A STUDY OF GENERALIZED LINEAR MIXED MODEL FOR COUNT DATA USING HIERARCHICAL BAYES METHOD." MEDIA STATISTIKA 14, no. 2 (2021): 194–205. http://dx.doi.org/10.14710/medstat.14.2.194-205.

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Poisson Log-Normal Model is one of the hierarchical mixed models that can be used for count data. Several estimation methods can be used to estimate the model parameters. The first objective of this study was to examine the performance of the parameter estimator and model built using the Hierarchical Bayes method via Markov Chain Monte Carlo (MCMC) with simulation. The second objective was applied the Poisson Log-Normal model to the West Java illiteracy Cases data which is sourced from the Susenas data on March 2019. In 2019, the incidence of illiteracy is a very rare occurrence in West Java P

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KALAYCIOĞLU, Oya. "Üç Düzeyli Hiyerarşik Modelleri Tahmin Etmek İçin Kullanılan Maksimum Olabilirlik ve Bayesçi Yöntemlerin Performansı: Karşılaştırmalı Bir Çalışma." Turkiye Klinikleri Journal of Biostatistics 12, no. 3 (2020): 252–60. http://dx.doi.org/10.5336/biostatic.2020-78912.

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Upendra, Singh, and P. Puttewar S. "Quantitative determination of vanadium in Bayer's liquor and vanadium sludge using ICP-AES." Journal of Indian Chemical Society Vol. 90, Nov 2013 (2013): 2127–31. https://doi.org/10.5281/zenodo.5792773.

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Analytical Research Division, Jawaharlal Nehru Aluminium Research Development & Design Centre, Amravati Road, Wadi, Nagpur-440 023, Maharashtra, India <em>E-mail </em>: singhu1970@rediffmail.com   Fax : 91-7104-220942 Quantification of vanadium (as V<sub>2</sub>O<sub>5</sub>) in Bayer liquor (Spent) and precipitated vanadium sludge have been done using ICP-AES and classical methods. Samples were prepared by acid digestion technique for the complete dissolution of free as well as bound vanadium in highly alkaline samples. Concentration of vanadium in spent liquor was obtained

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Yanuar, Ferra, Rahmatika Fajriyah, and Dodi Devianto. "SMALL AREA ESTIMATION METHOD WITH EMPIRICAL BAYES BASED ON BETA BINOMIAL MODEL IN GENERATED DATA." MEDIA STATISTIKA 14, no. 1 (2020): 1–9. http://dx.doi.org/10.14710/medstat.14.1.1-9.

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Small Area Estimation is one of the methods that can be used to estimate parameters in an area that has a small population. This study aims to estimate the value of the binary data parameter using the direct estimation method and an indirect estimation method by using the Empirical Bayes approach. To illustrate the method, we consider three conditions: direct estimator, empirical Bayes (EB) with auxiliary variables, and empirical Bayes without auxiliary variables. The smaller value of Mean Square Error is used to determine the better method. The results showed that the indirect estimation meth

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Yanuar, Ferra, Putri Trisna Sari, and Yudiantri Asdi. "IDENTIFICATION OF RAINFALL DISTRIBUTION IN WEST SUMATERA AND ASSESSMENT OF ITS PARAMETERS USING BAYES METHOD." MEDIA STATISTIKA 13, no. 2 (2020): 161–69. http://dx.doi.org/10.14710/medstat.13.2.161-169.

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One distribution of rainfall data is a lognormal distribution with location parameters and scale parameters . This study aims to estimate the mean and variance of rainfall data in several selected cities and regencies in West Sumatra. Parameter estimation is estimated by using maximum likelihood estimation (direct method) and Bayes method. This study resulted that the Bayes method produces a better predictive value with a smaller variance value than with direct estimation. It was concluded that the estimation by the Bayes method was a better estimator method than the direct estimation.

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Andreas, Andreas, and Lusia Permata Sari Hartanti. "Webpage Classification Using Naïve Bayes Classifier and Information Retrieval Method to Block the Pornography Contents." International Journal of Future Computer and Communication 6, no. 4 (2017): 153–57. http://dx.doi.org/10.18178/ijfcc.2017.6.4.509.

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Shi, Xu, Xiao Wang, Lu Jin, et al. "Bayesian identification of differentially expressed isoforms using a novel joint model of RNA-seq data." PLOS Computational Biology 21, no. 1 (2025): e1012750. https://doi.org/10.1371/journal.pcbi.1012750.

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We develop a Bayesian approach, BayesIso, to identify differentially expressed isoforms from RNA-seq data. The approach features a novel joint model of the sample variability and the deferential state of isoforms. Specifically, the within-sample variability and the between-sample variability of each isoform are modeled by a Poisson-Lognormal model and a Gamma-Gamma model, respectively. Using a Bayesian framework, the differential state of each isoform and the model parameters are jointly estimated by a Markov Chain Monte Carlo (MCMC) method. Extensive studies using simulation and real data dem

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Bishop, Craig H., and Kevin T. Shanley. "Bayesian Model Averaging’s Problematic Treatment of Extreme Weather and a Paradigm Shift That Fixes It." Monthly Weather Review 136, no. 12 (2008): 4641–52. http://dx.doi.org/10.1175/2008mwr2565.1.

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Abstract Methods of ensemble postprocessing in which continuous probability density functions are constructed from ensemble forecasts by centering functions around each of the ensemble members have come to be called Bayesian model averaging (BMA) or “dressing” methods. Here idealized ensemble forecasting experiments are used to show that these methods are liable to produce systematically unreliable probability forecasts of climatologically extreme weather. It is argued that the failure of these methods is linked to an assumption that the distribution of truth given the forecast can be sampled

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Ramana, P. V. "Naïve Bayesto Machine Learning Approach for Structural Dynamic Complications." Proceedings of the 12th Structural Engineering Convention, SEC 2022: Themes 1-2 1, no. 1 (2022): 1283–91. http://dx.doi.org/10.38208/acp.v1.652.

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Learning is one of the most powerful concepts in artificial intelligence research. It allows a system to learn from its environment and automatically modify its behavior to suit its needs. On par with human champions, the world’s best computer backgammon player is a computer program that learns by playing against itself. The learning algorithm and available data set limit computer learning. Several techniques are available to perform machine learning. Decision trees, the naïve Bayes approach, and the more general Bayes net approach are a few choices. The naïve Bayes approach is an instance of

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Shevchuk, E. P., V. A. Plotnikov, and G. S. Bektasova. "Study of Diffusion Boride Bayers of Steel 20, Obtained by the Micro-Arc Surface." Izvestiya of Altai State University, no. 4(114) (September 9, 2020): 59–63. http://dx.doi.org/10.14258/izvasu(2020)4-09.

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We discuss the results of the study of carbon steel 20 boriding performed by the micro-arc chemical-thermal treatment of a mixture containing iron and boric acid. The study has been carried out in scientific laboratories of the EKSU named after S. Amanzholov. It is found out that boride diffusion coatings obtained by this method are characterized by high hardness of 3.5 GPa and have an extensive diffusion zone. The wide diffusion zone is a surface layer of steel in which the compounds of boron and iron are distributed so that a transition region is formed between the hardened region and the ma

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Vu, Sang V., Cedric Gondro, Ngoc T. H. Nguyen, et al. "Prediction Accuracies of Genomic Selection for Nine Commercially Important Traits in the Portuguese Oyster (Crassostrea angulata) Using DArT-Seq Technology." Genes 12, no. 2 (2021): 210. http://dx.doi.org/10.3390/genes12020210.

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Genomic selection has been widely used in terrestrial animals but has had limited application in aquaculture due to relatively high genotyping costs. Genomic information has an important role in improving the prediction accuracy of breeding values, especially for traits that are difficult or expensive to measure. The purposes of this study were to (i) further evaluate the use of genomic information to improve prediction accuracies of breeding values from, (ii) compare different prediction methods (BayesA, BayesCπ and GBLUP) on prediction accuracies in our field data, and (iii) investigate the

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Michael, Gr. Voskoglou, and Athanassopoulos Evangelos. "The Importance of Bayesian Reasoning in Everyday Life and Science." International Journal of Education, Development, Society and Technology (IJEDST) ISSN: 2321 – 7537 8, no. 2 (2020): 24–33. https://doi.org/10.5281/zenodo.4026022.

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The Importance of Bayesian Reasoning in Everyday Life and Science Michael Gr. Voskoglou<sup> 1</sup> and Evangelos Athanassopoulos <sup>2</sup> 1 Department of Mathematical Sciences, School of Technological Applications, Graduate Technological Educational Sciences Institute of Western Greece, Patras, GREECE. 2 Independent Researcher, Gastouni, GREECE. voskoglou@teiwest.gr, mvoskoglou@gmail.com, evatha@gmail.com <strong>ABSTRACT: </strong> Bayesian reasoning has been proved to be an important component of the human cognition. The present work studies the importance of Bayesian reasoning in the

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Barkalov, S. A., T. V. Azarnova, and P. V. Polukhin. "Management of the Process of Web Applications Testing by the Fuzzing Method Based on Dynamic Bayesov Networks." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 17, no. 2 (2017): 51–64. http://dx.doi.org/10.14529/ctcr170205.

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Irwansyah, Mochamad Denny, Teguh Puja Negara, Erniyati Erniyati, and Puspa Citra. "Application of the Naive Bayes Classifier Method and Fuzzy Analytical Hierarchy Process in Determining Books Eligible for Publishing." Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika 21, no. 1 (2024): 55–67. http://dx.doi.org/10.33751/komputasi.v21i1.6677.

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The manuscript selection process is the process of assessing manuscripts worthy of publication. The Editor's job is to provide an evaluation of each manuscript based on the assessment criteria and sub-criteria. By using a decision support system, it can make it easier for policymakers to determine the suitability of a manuscript. In this research, a decision support system is applied to select papers that are worthy of publication, namely the Fuzzy Analytical Hierarchy Process (F-AHP) method for selecting the suitability of manuscripts using subjective criteria and the Naïve Bayes method for c

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Zavadskas, Edmundas Kazimieras, Leonas Ustinovičius, Zenonas Turskis, Gintautas Ambrasas, and Vladislavas Kutut. "ESTIMATION OF EXTERNAL WALLS DECISIONS OF MULTISTOREY RESIDENTIAL BUILDINGS APPLYING METHODS OF MULTICRITERIA ANALYSIS." Technological and Economic Development of Economy 11, no. 1 (2005): 59–68. http://dx.doi.org/10.3846/13928619.2005.9637683.

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This paper analyses the most widespread designs of external walls of the multi‐storey residential buildings now in use. Such 49 alternative designs of external walls of multi‐storey residential buildings are analyzed using multicriteria analysis program under uncertainty. Few ways of the decision are applied for the decision of the problem: the method of distance to an ideal point, Baye's rule and Wald's rule. To project and understand effective construction of a building, it is necessary to execute exhaustive analysis of all decisions (planimetric, prolongation of term and quality of building

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Gede Widnyana Putra, Ida Bagus, Made Sudarma, and I. Nyoman Satya Kumara. "Klasifikasi Teks Bahasa Bali dengan Metode Information Gain dan Naive Bayes Classifier." Majalah Ilmiah Teknologi Elektro 15, no. 2 (2016): 81–86. http://dx.doi.org/10.24843/mite.1502.12.

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Naderi, Yousef, and Saadat Sadeghi. "The importance of disease incidence rate on performance of GBLUP, threshold BayesA and machine learning methods in original and imputed data set." Spanish Journal of Agricultural Research 18, no. 3 (2020): e0405. http://dx.doi.org/10.5424/sjar/2020183-15228.

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Aim of study: To predict genomic accuracy of binary traits considering different rates of disease incidence.Area of study: SimulationMaterial and methods: Two machine learning algorithms including Boosting and Random Forest (RF) as well as threshold BayesA (TBA) and genomic BLUP (GBLUP) were employed. The predictive ability methods were evaluated for different genomic architectures using imputed (i.e. 2.5K, 12.5K and 25K panels) and their original 50K genotypes. We evaluated the three strategies with different rates of disease incidence (including 16%, 50% and 84% threshold points) and their e

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Schuhen, Katrin, Maik Rudloff, Carolin Hiller, and Matthias Duchscherer. "Per- und polyfluorierte Chemikalien." gwf Wasser | Abwasser 158, no. 01 (2017): 55–67. http://dx.doi.org/10.17560/gwfwa.v158i01.1798.

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Haupteintragungspfade von per- und polyfluorierten organischen Verbindungen (PFCs) in die Umwelt sind PFC-haltige Industrieabwässer und -abfälle sowie Feuerlöscheinsätze. Über den Wasserkreislauf werden die Verbindungen durch Pflanzen und Tiere aufgenommen und schließlich auch durch den Menschen. Zur Entfernung dieser Stoffe aus der Umwelt wurden bisher verschiedene Methoden untersucht. Adsorptionsmethoden stellen eine effektive und effiziente Methode für die Sanierung von PFC-kontaminierten Flächen dar. Die Behandlung der bisherigen PFC-Schadensfälle in Deutschland erfolgt durch die Umweltlan

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Bhalla, Rajni, and Amandeep Bagga. "Opinion mining framework using proposed RB-bayes model for text classication." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 477–84. https://doi.org/10.11591/ijece.v9i1.pp477-484.

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Information mining is a capable idea with incredible potential to anticipate future patterns and conduct. It alludes to the extraction of concealed information from vast data sets by utilizing procedures like factual examination, machine learning, grouping, neural systems and genetic algorithms. In naive baye’s, there exists a problem of zero likelihood. This paper proposed RB-Bayes method based on baye’s theorem for prediction to remove problem of zero likelihood. We also compare our method with few existing methods i.e. naive baye’s and SVM. We demonstrate that this techniq

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Lewis, Nicholas. "Objective Inference for Climate Parameters: Bayesian, Transformation-of-Variables, and Profile Likelihood Approaches." Journal of Climate 27, no. 19 (2014): 7270–84. http://dx.doi.org/10.1175/jcli-d-13-00584.1.

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Abstract Insight is provided into the use of objective-Bayesian methods for estimating climate sensitivity by considering their relationship to transformations of variables in the context of a simple case considered in a previous study, and some misunderstandings about Bayesian inference are discussed. A simple model in which climate sensitivity (S) and effective ocean heat diffusivity (Kυ) are the only parameters varied is used, with twentieth-century warming attributable to greenhouse gases (AW) and effective ocean heat capacity (HC) being the only data-based observables. Probability density

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