Selecting the best model from a set of candidates for a given set of data is obviously not an easy task. In this paper, we propose a new criterion that takes into account a larger penalty when adding too many coefficients (or estimated parameters) in...
Structural reanalysis methods have been proposed to improve the efficiency of structural analysis. However, the methods are typically only applicable to their specific type of structural modification. Since the optimization process often involves mul...
In nature-inspired thin-walled energy absorbers, the biological prototype is increasingly selected with multi-criteria decision-making (MCDM) tools, yet the effect of algebraic dependence among criteria on this selection is rarely examined. Nine biom...
Feature selection represents a critical step in developing accurate and interpretable models for early breast cancer detection. Despite extensive research in the field of mammographic image analysis, no consensus has yet been reached on the optimal f...
In the last years, the distribution network operators (DNOs) assumed transition strategies of the electric distribution networks (EDNs) towards the active areas of the microgrids where, regardless of the operating regimes, flexibility, economic effic...
A stable growth mode of a single dendritic crystal solidifying in an undercooled ternary (multicomponent) melt is studied with allowance for a forced convective flow. The steady-state temperature, solute concentrations and fluid velocity components a...
Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitra...
Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables. We consider the setting of incomplete data analysis, where some primary variables are not...
The choice of materials is crucial in responding to the increasing embodied carbon (EC) impacts of buildings. Building professionals involved in material selection for construction projects have a vital role to play in this regard. This paper aimed t...
This work presents a spatially regularized modelling framework for selecting IoT-enabled environmental monitoring nodes within smart-lighting infrastructures. The study does not claim novelty in CRITIC, TOPSIS, mixed-integer programming, or Voronoi t...
The selection of an appropriate wavelet is an essential issue that should be addressed in the wavelet-based filtering of electrocardiogram (ECG) signals. Since entropy can measure the features of uncertainty associated with the ECG signal, a novel co...
The Dutch Konik is valued from a genetic conservation perspective and also for its role in preservation of natural landscapes. The primary management objective for the captive breeding of this primitive horse is to maintain its genetic purity, whilst...
The positioning based on Wireless Local Area Networks (WLAN) is one of the most promising technologies for indoor location-based services, generally using the information carried by Received Signal Strengths (RSS). One challenge, however, is the huge...
This paper aims to demonstrate the applicability of a modal selection criterion based on strain energy potential for describing static deformations in a commonly used engineering geometry, specifically a circular plate. The analytical model relies on...
In this paper, to track maneuvering unmanned surface vehicles (USVs) in scenarios with clutter, we propose a novel method based on the probabilistic data association (PDA) algorithm and Rao-Blackwellized particle filter (RBPF) algorithm, and we furth...
This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. Four established selection criteria—modal kinetic energy (MKE), modal strain energy (MSE), modal...
Global Navigation Satellite Systems (GNSS) have undergone more than half a century of development and construction, with more than a hundred navigation satellites currently providing precise and reliable positioning, navigation, and timing (PNT) serv...
The main research purpose of the present paper is the establishment of certain compliance criteria, applied for the selection of the most appropriate, per case, bridge construction method, as well as the definition of the weights of these criteria. T...
Direct injection in hydrogen engines enables flexible combustion control, improves engine efficiency, and reduces the risk of abnormal combustion. However, implementing this injection strategy is challenging due to the need to provide a relatively hi...
It is still a major challenge to select appropriate variables from remote sensing sensors, which implicates finding reliable selection methods that can maximize the performance of chosen variables in regression models. In this study, we compare the p...
Disaster recovery sites are an important mechanism in continuous IT system operations. Such mechanisms can sustain IT availability and reduce business losses during natural or human-made disasters. Concerning the cost and risk aspects, the IT disaste...
Low-cost metal-oxide-semiconductor (MOS) electronic noses promise rapid, non-destructive meat freshness screening, and published classifiers frequently approach perfect accuracy. Such figures are rarely tested against the two conditions that most inf...
The extensive integration of intelligent and bionic technologies in the automotive industry has significantly heightened interest in the advancement of smart vehicle cockpits. The growing demand for automobile cockpit functions makes the personalizat...
Model selection criteria are widely used to identify the model that best represents the data among a set of potential candidates. Amidst the different model selection criteria, the Bayesian information criterion (BIC) and the Akaike information crite...
Change points indicate significant shifts in the statistical properties in data streams at some time points. Detecting change points efficiently and effectively are essential for us to understand the underlying data-generating mechanism in modern dat...
It is a relatively well-known fact that in problems of Bayesian model selection, improper priors should, in general, be avoided. In this paper we will derive and discuss a collection of four proper uniform priors which lie on an ascending scale of in...
In the classical Stochastic Subspace Identification (SSI) method, mode selection is primarily based on frequency stability, damping stability, and mode shape similarity using the Modal Assurance Criterion (MAC). However, these criteria are often insu...
Only unstructured single-path model selection techniques, i.e., Information Criteria, are used by Bounds test of cointegration for model selection. The aim of this paper was twofold; one was to evaluate the performance of these five routinely used in...
Hybrid nanofluids raise the thermal output of evacuated-tube solar collectors, but the heat-transfer gain comes at the cost of friction and pumping power, so the working fluid must be chosen in line with a constrained thermo-hydraulic criterion. Its...
Artificial Neural Networks (ANN) have been widely applied in hydrologic and water quality (H/WQ) modeling in the past three decades. Many studies have demonstrated an ANN’s capability to successfully estimate daily streamflow from meteorological data...
The most widely used forms of model selection criteria, the Bayesian Information Criterion (BIC) and the Akaike Information Criterion (AIC), are expressed in terms of synthetic indicators of the residual distribution: the variance and the mean-square...
Denoising one-dimensional signals by wavelet shrinkage critically depends on the choice of wavelet basis, yet basis selection is often guided by heuristics rather than explicit statistical criteria. This paper investigates the relationship between wa...
Motor imagery is based on the volitional modulation of sensorimotor rhythms (SMRs); however, the sensorimotor processes in patients with amyotrophic lateral sclerosis (ALS) are impaired, leading to degenerated motor imagery ability. Thus, motor image...
Background: Choosing the number of clusters is still one of the least settled steps in a K-means analysis. The within-cluster sum of squares (WCSS) elbow plot is easy to understand, yet visual inspection is difficult to reproduce, and different valid...
This study proposes an intelligent decision-support framework for alternative selection in complex construction projects, where evaluation processes are affected by uncertainty, multiple decision-makers, and interdependent criteria. The framework int...
Variable selection is important for developing accurate and interpretable prediction models. While classical and penalized methods are widely used, few simulation studies provide meaningful comparisons. This study compares their predictive performanc...
Information criteria such as the Akaike information criterion (AIC) and Bayesian information criterion (BIC) are commonly used for model selection. However, the current theory does not support unconventional data, so naive use of these criteria is no...
Model-free variable selection has attracted increasing interest recently due to its flexibility in algorithmic design and outstanding performance in real-world applications. However, most of the existing statistical methods are formulated under the m...
The Bayesian information criterion (BIC), the Akaike information criterion (AIC), and some other indicators derived from them are widely used for model selection. In their original form, they contain the likelihood of the data given the models. Unfor...
The safe development of chemical industries requires adequate control of the environmental sustainability of the areas where enterprises are located. The purpose of the article is to develop and test a methodology for solving the multicriteria proble...
A variable selection method is put forward for multivariate linear regression models which obey normality. This method hinges on minimizing a generalized
This study systematically examines the robustness of the Akaike Information Criterion (AIC) in determining the optimal order (p) of an autoregressive (AR) model applied to the RR interval time series of the PhysioNet healthy subject database. The AR...
Parental selection is at the beginning and contributes significantly to the success of any breeding work. The value of a cross is reflected in the potential of its progeny population. Breeders invest substantial resources in evaluating progeny to sel...
Support vector regression (SVR) is a powerful kernel-based regression prediction algorithm that performs excellently in various application scenarios. However, for real-world data, the general SVR often fails to achieve good predictive performance du...
The accuracy of modal superposition methods for determining displacement or strain field of structures largely depends on the selection of modes relevant to its deformation. Analytical methods for modal selection have been developed to minimise error...
Most statistical modeling applications involve the consideration of a candidate collection of models based on various sets of explanatory variables. The candidate models may also differ in terms of the structural formulations for the systematic compo...
In this paper, first we show that the variance used in the Markowitz’s mean-variance model for the portfolio selection with its numerous modifications often does not properly present the risk of portfolio. Therefore, we propose another treating...
This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rat...
The aim of this work is to develop a die material selection criterion for aluminum hot stamping applications. The criterion has been based on the back-to-back comparison of a set of reciprocating friction and wear tests. Three representatives belongi...
This study develops three capital allocation approaches and a directional weight increment algorithm to identify the efficient frontier of all possible multi-asset portfolios precisely and rapidly. Subsequently, this study proposes an asset selection...
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