2024 December-1 - 241 articles
Classic options can no longer meet the diversified needs of investors; thus, it is of great significance to construct and price new options for enriching the financial market. This paper proposes a new option pricing model that integrates the logarit...
Simulating electromagnetic (EM) fields can obtain the EM responses of geoelectric models at different times and spaces, which helps to explain the dynamic process of EM wave propagation underground. EM forward modeling is regarded as the engine of in...
As a key task in machine learning, data classification is essential to find a suitable coordinate system to represent the data features of different classes of samples. This paper proposes the mutual-energy inner product optimization method for const...
Root-indices of graphs are mathematical tools that help us to understand complex systems, like molecules and networks, by capturing key structural information. In this study, we introduce two new root-indices, the first and the second Zagreb root-ind...
Efficient estimation methods for simultaneous autoregressive (SAR) models with missing data in the response variable have been well explored in the literature. A common practice is introducing measurement error into SAR models to separate the noise c...
Research about multiple positive solutions for fractional differential equations is very important. Based on some outstanding results reported in this field, this paper continue the focus on this topic. By using the properties of the Green function a...
Divisible residuated lattices are algebraic structures corresponding to a more comprehensive logic than Hajek’s basic logic with an important significance in the study of fuzzy logic. The purpose of this paper is to investigate commutative ring...
Using upper record value data, we provide a credible interval estimate for the scale parameter of a two-parameter exponential distribution based on Bayesian methods. Additionally, we propose two Bayesian credible confidence regions for both parameter...
Relative positioning accuracy between two devices is dependent on the precise range measurements. Ultra-wideband (UWB) technology is one of the popular and widely used technologies to achieve centimeter-level accuracy in range measurement. Neverthele...
Crime report clustering plays a critical role in modern law enforcement, enabling the identification of patterns and trends essential for proactive policing. However, traditional clustering approaches face significant challenges with the complex, uns...
An innovative method for bubble detection and characterization in multiphase flows using advanced computer vision and neural network algorithms is introduced. Building on the research group’s previous findings, this study combines high-speed vi...
In this study, five different time-dependent incompressible non-Newtonian boundary layer models in two dimensions are investigated with the self-similar Ansatz, including external magnetic field effects. The power-law, the Casson fluid, the Oldroyd-B...
This article introduces the 2-variable q-truncated exponential–Appell (q-trunc. exp. Appell) polynomials and investigates their fundamental properties. Specific results are derived for the q-trunc. exp. Appell family along with their graphical...
This work presents an original and very interesting approach to a calculus problem involving beams with intermediate supports through the transfer-matrix method, a very easy method to program to quickly obtain good results. To exemplify the applicabi...
This article addresses the issues of scalability and security in blockchain networks, with a focus on sharding algorithms and decentralized data storage. Key challenges include the low throughput and high transaction latency in public networks such a...
The rapid development of autonomous driving technology is widely regarded as a potential solution to current traffic congestion challenges and the future evolution of intelligent vehicles. Effective driving strategies for autonomous vehicles should b...
The Troesch problem is a well-known and important problem; the ability to solve it is important due to the practical applications of this problem. In this paper, we propose a method to solve this problem using a combination of two useful algorithms:...
In multi-attribute decision making (MADM), complex situations often arise where decision attributes are interval-valued hesitant fuzzy numbers (IVHFNs) and the attributes are interrelated. Traditional decision-making methods may be ineffective in han...
FTN signalling is an effective communication method that achieves a high spectral efficiency. However, employing a symbol rate faster than the Nyquist rate disrupts the orthogonality between symbols, leading to unavoidable inter-symbol interference (...
Consumer reviews play a pivotal role in shaping purchasing decisions and influencing the reputation of businesses in today’s digital economy. This paper presents a novel hybrid deep learning model, WDE-CNN-LSTM, designed to enhance the sentimen...
This paper solves a nonhomogeneous version of the pantograph equation. The nonhomogeneous term is taken as a polynomial of degree n with arbitrary coefficients. The nonhomogeneous pantograph equation is successfully converted to the standard homogene...
Performance analysis, utilizing video technology and recent technological advancements in soccer stadiums, provides a wealth of data, including player trajectories and real-time game statistics, which are crucial for tactical evaluation and decision-...
Quantum Generative Adversarial Networks (QGANs) represent a useful development in quantum machine learning, using the particular properties of quantum mechanics to solve the challenges of data analysis and modeling. This paper brings up a general ana...
Reverse factoring is a retailer-led supply chain financing system that can enhance liquidity of suppliers and reduce factoring fraud. This paper proposes a bargaining game theory model to analyze the profit distribution in reverse factoring for a two...
In this paper, the authors approach the problem of boundary condition synthesis (also defined as field continuation) in a doubly connected domain by the use of a Neural Network-based approach. In this innovative method, given a field problem (magneto...
The numerical solution to boundary differential problems is a crucial task in modern applied mathematics. Usually, implicit integration methods are applied to solve this class of problems due to their high numerical stability and convergence. The kno...
At present, energy demands are mainly covered by the use of fossil fuels. The process of fossil fuel production increases pollution from oil extraction, transport to processing centers, treatment to obtain lighter fractions, and delivery and use by t...
Simulating composite material structures requires complex constitutive models, which normally require fine meshes to obtain an accurate prediction of their behavior. Pam-Crash software has been used for several years in the automotive industry and ha...
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As the logistics industry modernizes, living standards improve, and consumption patterns shift, the demand for fresh food continues to grow, making cold chain logistics for perishable goods a critical component in ensuring food quality and safety. Ho...
Modern developments in data analysis techniques and evolutionary optimization algorithms have made it possible to analyze large amounts of unstructured digital data sets. Based on the differential evolution algorithm and semiclassical quantum simulat...
Transport mode is one of the important travel characteristics for citizens, which is crucial to the planning and management of urban transportation. With the natural advantages of large sample sizes and a wide coverage of people, more and more resear...
In the context of discrete event systems (DESs), critical states usually refer to a system configuration of interest, describing certain important system properties, e.g., fault diagnosability, state/language opacity, and state/event concealment. Tec...
Platooning technology, which reduces fuel consumption by decreasing aerodynamic drag, is emerging as a key solution for enhancing road efficiency and environmental sustainability in logistics. Conventional vehicle-to-vehicle communication has limitat...
The purpose of this study was to ensure the compliance and safety of a robot’s movements during interactions with the external environment. This paper proposes a control strategy for learning variable impedance characteristics from multiple set...
The present study dealt with a comprehensive mathematical model to explore the nonlinear forced vibration of a magnetostrictive laminated beam. This system was subjected to mechanical impact, a nonlinear Winkler–Pasternak foundation, and an ele...
In this paper, we deal with the properties and applications of a nonlinear scalarization function for sets by using the Minkowski difference. Under some suitable assumptions, the continuity and convexity concerned with the nonlinear scalarization fun...
Improving product quality is an effective way for a company to gain goodwill as well as to increase sales. In this paper, the focus is on a two-echelon supply chain consisting of a manufacturer and a retailer. Considering the delayed effect of qualit...
High-dimensional parameter testing is commonly used in bioinformatics to analyze complex relationships in gene expression and brain connectivity studies, involving parameters like means, covariances, and correlations. In this paper, we present a nove...
Thanks to advancements in automated driving technology, autonomous trucks (ATs) can form platoons with minimal inter-vehicle distances on highways, significantly reducing air drag and fuel consumption for fleets. Given the dispersed distribution and...
Consumers’ low-carbon preferences will affect the decision-making behavior of supply chain members; an understanding of the influence mechanism of reciprocal altruistic preferences and reference low-carbon-level effect on carbon emission transf...
Efficient and economical hydrocarbon extraction relies on a clear understanding of fluid flow dynamics in subsurface reservoirs, where multiphase flow in porous media poses complex modeling challenges. Traditional numerical methods for solving the go...
Surrounding rock squeezing is a common geological disaster in underground excavation projects (e.g., TBM tunneling and deep mining), which has adverse effects on construction safety, schedule, and property. To predict the squeezing of the surrounding...
To address the challenges of environmental impact and distribution efficiency in fresh food logistics, a segmented transshipment model involving the coordinated operation of gasoline and electric vehicles is proposed. The model minimizes total distri...
The lognormal moment sequence is considered. Using the fractional moments technique, it is first proved that the lognormal has the largest differential entropy among the infinite positively supported probability densities with the same lognormal-mome...
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The primary objective of our research is to enhance the efficiency and effectiveness of Neural Architecture Search (NAS) with regard to Graph Neural Networks (GNNs). GNNs have emerged as powerful tools for learning from unstructured network data, com...
Indoor point clouds often present significant challenges due to the complexity and variety of structures and high object similarity. The local geometric structure helps the model learn the shape features of objects at the detail level, while the glob...
The conventional approach to intensity-modulated radiation therapy treatment planning involves two distinct strategies: optimizing an evaluation function while accounting for dose constraints, and solving feasibility problems using feasibility-seekin...
A model of Edgeworthian economies is studied, in which participants are randomly chosen at each period to exchange two goods to increase their utilities, as described by the Cobb–Douglas utility function. Participants can trade deviating from t...
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