Most previous studies on lossless image compression have focused on improving preprocessing functions to reduce the redundancy of pixel values in real images. However, we assumed stochastic generative models directly on pixel values and focused on ac...
This paper deals with a prediction problem of a new targeting variable corresponding to a new explanatory variable given a training dataset. To predict the targeting variable, we consider a model tree, which is used to represent a conditional probabi...
Saliency map generation in synthetic aperture radar (SAR) imagery has become a promising research area, since it has a close relationship with quick potential target identification, rescue services, etc. Due to the multiplicative speckle noise and co...
In information theory, lossless compression of general data is based on an explicit assumption of a stochastic generative model on target data. However, in lossless image compression, researchers have mainly focused on the coding procedure that outpu...
The error threshold is the cornerstone to balance the mathematical complexity and simulation speed of wind farm (WF) equivalent models, and can promote the standardization process of equivalent methodology. Due to differences in power system conditio...
Aiming at the existing problems in practical teaching in higher education, we construct an intelligent teaching recommendation model for a higher education practical discussion course based on naive Bayes machine learning and an improved k-NN data mi...
Risk of flash floods is currently an important problem in many parts of Vietnam. In this study, we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial Basis Function Classifier (RBFC), Multinomial Naïve Bayes (NBM...
This study evaluates Empirical Bayes (EB) c-charts for monitoring count-type data under precautionary (PLF) and logarithmic (LLF) loss functions. By assuming an exponential prior for the Poisson mean, the EB framework enables the construction of pred...
The power of projection using divergence functions is a major theme in information geometry. One version of this is the variational Bayes (VB) method. This paper looks at VB in the context of other projection-based methods in information geometry. It...
Stochastic epidemic models may offer a vitally essential public health tool for comprehending and regulating disease progression. The best illustration of their importance and usefulness is perhaps the substantial influence that these models have had...
In periods of dramatic stock price volatility, the identification of change points in stock price time series is important for analyzing the structural changes in financial market data, as well as for risk prevention and control in the financial mark...
This paper presents the intrinsic limit determination algorithm (ILD Algorithm), a novel technique to determine the best possible performance, measured in terms of the AUC (area under the ROC curve) and accuracy, that can be obtained from a specific...
The empirical Bayes (EB) method is widely acclaimed for crash hotspot identification (HSID), which integrates crash prediction model estimates and observed crash frequency to compute the expected crash frequency of a site. The traditional negative bi...
9 December 2024
In the current competition process of e-commerce platforms, the technical and algorithmic wars that can quickly grasp user needs and accurately recommend target commodities are the core tools of platform competition. At the same time, the existing on...
Solar power’s variability makes managing power system planning and operation difficult. Facilitating a high level of integration of solar power resources into a grid requires maintaining the fundamental power system so that it is stable when in...
The Internet of Things (IoT) has been influential in predicting major diseases in current practice. The deep learning (DL) technique is vital in monitoring and controlling the functioning of the healthcare system and ensuring an effective decision-ma...
In machine learning, classifiers have the feature of constant symmetry when performing the attribute transformation. In the research field of tourism recommendation, tourists’ interests should be mined and extracted by the symmetrical transform...
The commonly used POI route recommendation methods usually ignore the effects of tourists’ interests and transportation geographical conditions, and so may not output the optimal results. To solve the problems, we propose a POI route recommenda...
Commonly, it is accepted that oncology treatment would yield outcomes with a certain determinism without any quantitative support or mathematical model that establishes such determinations. Nowadays, with the advent of nanomedicine, the targeting dru...
Constructing an accurate model for insurance losses is a challenging task. Researchers have developed various methods to model insurance losses, such as composite models. Composite models combine two distributions: one for part of the data with small...
High-dimensional data recognition problem based on the Gaussian Mixture model has useful applications in many area, such as audio signal recognition, image analysis, and biological evolution. The expectation-maximization algorithm is a popular approa...
Meta-analytic deconvolution seeks to recover the distribution of true effects from noisy site-specific estimates. While Efron’s log-spline prior provides an elegant empirical Bayes solution with excellent point estimation properties, its plug-i...
During the pandemic of the coronavirus disease (COVID-19), statistics showed that the number of affected cases differed from one country to another and also from one city to another. Therefore, in this paper, we provide an enhanced model for predicti...
Generalized progressively Type-II hybrid strategy has been suggested to save both the duration and cost of a life test when the experimenter aims to score a fixed number of failed units. In this paper, using this mechanism, the maximum likelihood and...
Minimum Bayes factors are commonly used to transform two-sided p-values to lower bounds on the posterior probability of the null hypothesis, in particular the bound
The current literature includes limited information on the classification precision of Bayes estimation for latent class analysis (BLCA). (1) Objectives: The present study compared BLCA with the robust maximum likelihood (MLR) procedure, which is the...
Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP)...
16 April 2020
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices, and can cause social upheaval and loss of life. As a result, many scientists study the phenomenon, and some of them have focused on producing landslide susce...
Vertical integration, also known as make-or-buy, defines whether activities are conducted by company or provided by external parties. There are different models to support decision making for vertical integration in the literature. However, they igno...
In this paper, we develop statistical inference of competing risks samples which are collected under a joint Type-II censoring scheme of products with Weibull lifetime distributions. These inferences are drawn from two independent fatal risks and com...
A new two-parameter weighted-exponential (WE) distribution, as a beneficial competitor model to other lifetime distributions, namely: generalized exponential, gamma, and Weibull distributions, is studied in the presence of adaptive progressive Type-I...
The goal of the Label Ranking (LR) problem is to learn preference models that predict the preferred ranking of class labels for a given unlabeled instance. Different well-known machine learning algorithms have been adapted to deal with the LR problem...
Paratuberculosis is a widespread infectious disease in ruminants that leads to significant economic losses in livestock production. In this study, we developed a practical method for predicting the likelihood of the herd-level presence of the infecti...
Today, the reliability or quality practitioner always aims to shorten testing duration and reduce testing costs without neglecting efficient statistical inference. So, a generalized progressively Type-II hybrid censored mechanism has been developed i...
A new two-parameter statistical model, obtained by compounding the generalized-exponential and exponential distributions, called the PRC lifetime model, is explored in this paper. This model can be easily linked to other well-known six-lifetime model...
This paper deals with the statistical inference of the unknown parameter and some life parameters of inverse Lindley distribution under the assumption that the data are adaptive Type-II progressively censored. The maximum likelihood method is conside...
Impervious surface as an evaluation indicator of urbanization is crucial for urban planning and management. It is necessary to obtain impervious surface information with high accuracy and resolution to meet dynamic monitoring under rapid urban develo...
Latent Variable Models (LVMs) are well established tools to accomplish a range of different data processing tasks. Applications exploit the ability of LVMs to identify latent data structure in order to improve data (e.g., through denoising) or to est...
Given the emergence of China as a political and economic power in the 21st century, there is increased interest in analyzing Chinese news articles to better understand developing trends in China. Because of the volume of the material, automating the...
This paper considers a class of generative graphical models for parsimonious modeling of Gaussian mixtures and robust unsupervised learning, each assuming that the data are generated independently and identically from a finite mixture model with an e...
We consider the two-sample problem involving a new class of angle-based models for ranking data. These models are functions of the cosine of the angle between a ranking and a consensus vector. A Bayesian approach is employed to determine the correspo...
Rapid urbanization has altered the natural surface properties and spatial patterns, increasing the risk of urban waterlogging. Assessing the probability of urban waterlogging risk is crucial for preventing and mitigating the environmental risks assoc...
Physicians depend on their insight and experience and on a fundamentally indicative or symptomatic approach to decide on the possible ailment of a patient. However, numerous phases of problem identification and longer strategies can prompt a longer t...
A new two-parameter extended exponential lifetime distribution with an increasing failure rate called the Poisson–exponential (PE) model was explored. In the reliability experiments, an adaptive progressively Type-II hybrid censoring strategy i...
The present paper describes a novel recognition method of pulmonary nodules (i.e., cancer candidates) in thoracic computed tomography scans by use of three-dimensional spherical and cylindrical models that represent nodules and blood vessels, respect...
The rapid expansion of small and medium enterprise (SME) lending has intensified the need for accurate and interpretable credit risk forecasting. Financial institutions must anticipate potential business loan delinquency to maintain portfolio stabili...
By a “covering” we mean a Gaussian mixture model fit to observed data. Approximations of the Bayes factor can be availed of to judge model fit to the data within a given Gaussian mixture model. Between families of Gaussian mixture models, we propose...
This study presents the design and evaluation of a multi-model artificial intelligence (AI) framework for proactive quality risk management in projects. A dataset comprising 2000 risk records was developed, containing four columns: Risk Description (...
Submarine mine water inrush has become a problem that must be urgently solved in coastal gold mining operations in Shandong, China. Research on water in subway systems introduced classifications for the types of mine groundwater and then established...
This study proposes Bayesian estimation of multivariate regular vine (R-vine) copula models with generalized autoregressive conditional heteroskedasticity (GARCH) margins modeled by Gaussian-mixture distributions. The Bayesian estimation approach inc...
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