This paper explores the application of various machine learning techniques for predicting customer churn in the telecommunications sector. We utilized a publicly accessible dataset and implemented several models, including Artificial Neural Networks,...
Background: The analysis of vitamins in baby food is a challenging task given the complexity of the food matrix, vitamin stability, and strict regulations of the European Union regarding permissible deviations from declared values. Vitamins in food e...
Global optimization is used in many practical and scientific problems. For this reason, various computational techniques have been developed. Particularly important are the evolutionary techniques, which simulate natural phenomena with the aim of det...
In this paper, we target the problems of finding a global minimum of nonlinear and stochastic programming problems. To solve this type of problem, we propose new approaches based on combining direct search methods with Evolution Strategies (ESs) and...
In this paper, we investigate and propose the application of an unsupervised machine learning clustering method to characterize the spatial and temporal distribution of ionospheric plasma irregularities over the Western African equatorial region. The...
This paper pioneers a novel approach in electromagnetic (EM) system analysis by synergistically combining Bayesian Neural Networks (BNNs) informed by Latin Hypercube Sampling (LHS) with advanced thermal–mechanical surrogate modeling within COMS...
This article deals with the identification of a superior forecasting method for market liquidity using a calibrated Heston model for the bid/ask price path simulation instead of a standard Brownian motion, as well as a compound Poisson process and in...
Class imbalance is a common issue in machine learning, often causing bias in learning models toward the majority class and leading to poor predictive performance for the minority class data. To address the class imbalance problem, this paper presents...
The annual bluegrass weevil (ABW), Listronotus maculicollis (Kirby), a significant pest of short-mown turfgrass in eastern North America, has developed widespread insecticide resistance because of excessive synthetic insecticide use. The proper monit...
Classification problems due to data imbalance occur in many fields and have long been studied in the machine learning field. Many real-world datasets suffer from the issue of class imbalance, which occurs when the sizes of classes are not uniform; th...
Generating practical methods for simulation-based optimization has attracted a great deal of attention recently. In this paper, the estimation of distribution algorithms are used to solve nonlinear continuous optimization problems that contain noise....
In this paper, a new sampling technique is proposed that can be used in the Multistart global optimization technique as well as techniques based on it. The new method takes a limited number of samples from the objective function and then uses them to...
The need for accurate physical measurements is omnipresent in both scientific and engineering applications. Such measurements can be used to explore and characterize the behavior of a system over the parameters of interest. These procedures are often...
With the rapid growth of simulation software packages, generating practical tools for simulation-based optimization has attracted a lot of interest over the last decades. In this paper, a modified method of Estimation of Distribution Algorithms (EDAs...
This paper presents the design, optimization, and calibration of multivariable resonators for microwave dielectric sensors. An optimization technique for the circular complementary split ring resonator (CC-SRR) and square complementary split ring res...
Glioblastoma is a malignant brain tumor with a dismal prognosis. The standard treatment has not changed in the past 15 years as clinical trials of new treatment protocols have failed. A high prevalence of the human cytomegalovirus (HCMV) in glioblast...
The high printing efficiency and easy availability of desktop digital light processing (DLP) printers have made DLP 3D printing a promising technique with increasingly broad application prospects, particularly in personalized medicine. The objective...
Surrogate-based algorithms are indispensable in the aerospace engineering field for reducing the computational cost of optimization and uncertainty quantification analyses, particularly those involving computationally intensive solvers. This paper pr...
This paper presents a method for selecting the sampling time for induction machine parameter estimation from the machine line start measurements. the metaheuristic optimization method is used to find the optimal Prony exponential series approxiamtion...
We compare reconstructed quantum state images of a birefringent sample using direct quantum state tomography and inverse numerical optimization technique. Qubits are used to characterize birefringence in a flat transparent plastic sample by means of...
The goal of this article is to provide an intuitive explanation of an electromagnetic field sampling technique, known as optimal field sampling. This explanation provides insight into the physical mechanisms underlying the sampling strategy along obs...
Landslide susceptibility mapping (LSM) is significant for disaster prevention and mitigation, land use management, and as a reference for decision-making. Convolutional neural networks (CNNs) in deep learning have been successfully applied to LSM stu...
High-resolution three-dimensional (3D) Inverse Synthetic Aperture Radar (ISAR) imaging is essential for the characterization of target scattering in various environments. The practical application of this technique is frequently impeded by the length...
Traditional approaches used for analyzing the mechanical properties of auxetic structures are commonly based on deterministic techniques, where the effects of uncertainties are neglected. However, uncertainty is widely presented in auxetic structures...
Multiple Importance Sampling (MIS) combines the probability density functions (pdf) of several sampling techniques. The combination weights depend on the proportion of samples used for the particular techniques. Weights can be found by optimization o...
In the near future, Poland is going to have more and more favorable conditions for viticulture. Organic acids and polyphenols are among the most commonly analyzed compounds due to their beneficial properties for human health and their importance in t...
Volumetric absorptive microsampling (VAMS) is the newest and most promising sample-collection technique for quantitatively analyzing drugs, especially for routine therapeutic drug monitoring (TDM) and pharmacokinetic studies. This technique uses an a...
The dual response surface methodology is a widely used technique in industrial engineering for simultaneously optimizing both the process mean and process standard deviation functions of the response variables. Many optimization techniques have been...
The problem of finding the global minimum of a function is applicable to a multitude of real-world problems and, hence, a variety of computational techniques have been developed to efficiently locate it. Among these techniques, evolutionary technique...
Precision agriculture techniques contribute to optimizing the use of agricultural inputs, as they consider the spatial and temporal variability in the production factors. Prescription maps of limestone and fertilizers at variable rates (VRA) can be g...
In spite of the rather large use of the fused deposition modeling (FDM) technique for the fabrication of scaffolds, no studies are reported in the literature that optimize the geometry of such scaffold types based on mechanobiological criteria. We im...
In the cultural heritage field, non-invasive analyses are becoming more important as they avoid any sampling, allowing in situ measurements to be performed. XRF is one of the most common among those techniques, as it allows elemental speciation of th...
This paper presents a new combined method for the short-term load forecasting of electric power systems based on the Fuzzy c-means (FCM) clustering, particle swarm optimization (PSO) and support vector regression (SVR) techniques. The training sample...
Ionic liquid based, microwave-assisted extraction (ILMAE) was successfully applied to the extraction of proanthocyanidins from Larix gmelini bark. In this work, in order to evaluate the performance of ionic liquids in the microwave-assisted extractio...
Satellite and UAV-based remote sensing have been widely used for agricultural systems monitoring jointly. How to quantitatively optimize the efficiency of integrating these two techniques remains largely understudied. To address this gap, we, for the...
Root-knot nematode disease seriously threatens the production of Rui yams, making it important to explore effective management strategies, including the optimal time for disease control and efficient application techniques. In this study, we monitore...
Research on electroencephalography (EEG) signals and their data analysis have drawn much attention in recent years. Data mining techniques have been extensively applied as efficient solutions for non-invasive brain–computer interface (BCI) rese...
In this study, AlSi12 alloy samples were produced via the selective laser melting (SLM) technique to produce high-density components with complex and customized parts for railway applications. Nonetheless, the production of dense samples necessitates...
This research proposes an efficient technique for reliability-based topology optimization (RBTO), which deals with uncertainty and employs proportional topology optimization (PTO) to achieve the optimal reliability structure. The recent technique, ca...
A conventional approach to solving stochastic optimal control problems with time-dependent uncertainties involves the use of the stochastic maximum principle (SMP) technique. For large-scale problems, however, such an algorithm frequently leads to co...
Powerful computer-aided design tools are presently vital for engineering product development. Efficient global optimization (EGO) is one of the most popular methods for design of a high computational cost problem. The original EGO is proposed for onl...
Soils comprise the largest pool of terrestrial carbon yet have lost significant stocks due to human activity. Changes to land management in cropland and grazing systems present opportunities to sequester carbon in soils at large scales. Uncertainty i...
The study was focused on optimizing the procedure of synthesizing iron gallate (FeGa2O4) nanoparticles by mechanochemical techniques. Due to a lack of information in the literature about the sequence of synthesis procedures of FeGa2O4 structures, the...
Machine learning approaches are commonly used to model physical phenomena due to their adaptability to complex systems. In general, a substantial number of samples must be collected to create a model with reliable results. However, collecting numerou...
To reduce the computational cost of the multi-objective optimization process and improve the accuracy of fatigue life prediction for the lower control arm (LCA) of a vehicle under multiaxial random vibration, this paper focuses on the LCA of a MacPhe...
Hyperparameters allow metaheuristics to be tuned to a wide range of problems. However, even though formalized tuning of metaheuristic parameters can affect the quality of the solution, it is rarely performed. The empirical selection method and the tr...
Background/Objectives: International guidelines advocate for personalized vaccination protocols using point-of-care (POC) antibody titration to identify dogs requiring boosters for CPV-2, CDV, and CAdV-1. As traditional venipuncture can be challengin...
Infrared spectroscopy SBS asphalt-modifier content detection technology has been applied in practical projects, which can effectively ensure the quality of pavement engineering. If the composition ratio of modified asphalt is not clear, the accuracy...
In this paper, some methodologies aimed at the identification of the Pareto front of a multi-objective optimization problem are presented and applied. Three different approaches are presented: local sampling, Pareto front resampling and Normal Bounda...
A realistic industrial conceptual design optimization problem for commercial transport airplanes was formulated with reasonable fidelity and comprehensiveness by selecting appropriate design parameters, constraints, and objectives, in order to provid...
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