This study aims to construct a reduced thermodynamic cycle model with high accuracy and high model execution speed based on artificial neural network training for real-time numerical analysis. This paper proposes a method of constructing a fast avera...
The Beijing-Tianjin-Hebei (B-T-H) region, who captures the national strategic highland in China, has drawn a great deal of attention due to the fog and haze condition and other environmental problems. Further, the high carbon emissions generated by e...
Mean-value engine models (MVEMs) are frequently applied in system-level simulations of vehicle powertrains. In particular, MVEMs are a common choice in engine simulators, where real-time execution is mandatory. In the case of real-time applications w...
In this study, a linear model of the transformation of the stress amplitude due to the mean value was used. The coefficient of the material sensitivity to cycle asymmetry with consideration of the dependence of this coefficient on the number of fatig...
The generalized extreme value (GEV) distribution has been extensively applied in predicting extreme events across diverse fields, enabling accurate estimation of extreme quantiles of maxima. Although the mean and variance of the GEV can be expressed...
Computational algorithms are systematically written instructions or steps used to solve logical and mathematical problems with computers. These algorithms are crucial to rapidly and efficiently analyzing complex data, especially in global optimizatio...
When designing a stock portfolio, investors must select stocks with different characteristics and increasing price trends and weigh each capital. Both are fundamental to diversifying loss and profit. Therefore, the mechanisms that accommodate both ar...
Investors generally aim to obtain a high return from their stock portfolio. However, investors must realize that a high value-at-risk (VaR) is essential to calculate for this aim. One of the objects in the VaR calculation is the asymmetric return vol...
With the development of the Internet environment, the trend of the retail industry in the future. It cannot be separated from the community, data and experience. Consumers’ lifestyles and purchasing behaviors are constantly changing and retailers mus...
With growing urbanization, it has become necessary to manage this growth smartly. Specifically, increased electrical energy consumption has become a rapid urbanization trend in China. A building model based on a neural network was proposed to overcom...
We study a Mean-Risk model, where risk is measured by a Modified CoVaR (Conditional Value at Risk):
This paper deals with the quasi-instantaneous determination (in a single-step response time) of apparent, active, and reactive (i.e., blind and distortion) power mean values including the total power factor, total harmonic distortion, and phase shift...
This paper deals with the quasi-instantaneous determination of an apparent-, active-, and reactive (i.e., blind and distortion) power mean values, including total power factor, total harmonic distortion, and phase shift of fundamentals of power elect...
In this paper, we propose a weighted Lindley (NWLi) model for the analysis of extreme historical insurance claims. It extends the classical Lindley distribution by incorporating a weight parameter, enabling more flexibility in modeling insurance clai...
Recognizing the importance of incorporating different risk measures in the portfolio management model, this paper examines the dynamic mean-risk portfolio optimization problem using both variance and value at risk (VaR) as risk measures. By employing...
As a powerful generalization to fuzzy set, hesitant fuzzy set (HFS) was introduced, which provided multiple possible membership values to be associated with a specific instance. But HFS did not consider occurrence probability values, and to circumven...
In this article, to meet the requirements of marine engine room simulator on both the simulation speed and simulation accuracy, a mean value engine model (MVEM) for the 7S80ME-C9.2 marine two-stroke diesel engine was developed and validated in the MA...
Development of intelligent ships requires marine diesel engine simulation models of high accuracy and fast response. In addition, with advent of tighter shipping air emissions regulations, such models are required to have emission prediction capabili...
Middle East Respiratory Syndrome (MERS) is a human coronavirus subtype that poses a significant public health concern due to its ability to spread between individuals. This research aims to develop a fractional-order mathematical model to investigate...
This paper presents an efficient algorithm for Explicit Model-Following (EMF) control using an Output-derivative Feedback Control (OFC) scheme within the Reciprocal State Space (RSS) framework, aimed at overcoming the performance limitations associat...
The importance of neural network (NN) modelling is evident from its performance benefits in a myriad of applications, where, unlike conventional techniques, NN modeling provides superior performance without relying on complex filtering and/or time-co...
This paper proposes the extended state observer (ESO)-based active disturbance rejection control (ADRC) for the speed tracking of an autonomous vehicle. Uncertainties, both in the vehicle plant and in the sensors, such as nonlinear uncertainties due...
Predicting end-of-process variables in internal combustion engines, such as brake-specific fuel consumption or pollutant emissions, is crucial for engine design decisions. However, errors in common multi-layer-perceptron-based artificial neural netwo...
Effective stakeholder management is essential in construction projects, but numerous context-specific challenges often hinder its implementation. This study investigates the factors that limit stakeholder management in Türkiye’s constructi...
Construction professionals recognize rework’s negative impact on project performance, yet a comprehensive understanding of its critical factors still needs to be provided. Consequently, this study sought to inquire deeply into the causes of con...
The dynamic load caused by vehicle vibration due to an uneven pavement surface is a primary factor affecting the structural performance and service life of asphalt pavement. As the principles of vibration mechanics, in conjunction with the coherence...
This paper considers observation driven models with conditional mean and variance dynamics for non-negative valued time series. The motivation is to relax the restriction imposed on the higher order moment dynamics in standard multiplicative error mo...
Intensively grown strawberries in a greenhouse require frequent and precise soil physicochemical constituents for optimal production. Strawberry leaf color analyses are the most effective way to evaluate soil status and protect against excess environ...
This paper aims to design a quadratic optimization model of an investment portfolio based on value-at-risk (VaR) by entering risk-free assets and company liabilities. The designed model develops Markowitz’s investment portfolio optimization mod...
This paper presents a simulator model of a diesel engine with a turbocharger for hardware-in-the-loop (HIL) applications, which is used to obtain engine performance data to study the engine performance under faulty conditions, to assist engineers in...
The number of software failures, software reliability, and failure rates can be measured and predicted by the software reliability growth model (SRGM). SRGM is developed and tested in a controlled environment where the operating environment is differ...
Grassmann variables are used to formally transform a system with constraints into an unconstrained system. As a result, the Schrödinger equation arises instead of the Wheeler–DeWitt one. The Schrödinger equation describes a system&rsq...
In this study, modelling of microhardness values by means of artificial neural networks of Al/SiCp metal matrix composite material couples with diffusion method and manufactured by powder metallurgy process, were obtained using a backpropagation neur...
In this article, we expand the Muirhead mean (MM) operator and dual Muirhead mean (DMM) operator with single-valued neutrosophic 2-tuple linguistic numbers (SVN2TLNs) to propose the single-valued neutrosophic 2-tuple linguistic Muirhead mean (SVN2TLM...
Today, semi-structured and unstructured data are mainly collected and analyzed for data analysis applicable to various systems. Such data have a dense distribution of space and usually contain outliers and noise data. There have been ongoing research...
In this article, we expand the dual generalized weighted BM (DGWBM) and dual generalized weighted geometric Bonferroni mean (DGWGBM) operator with single valued neutrosophic numbers (SVNNs) to propose the dual generalized single-valued neutrosophic n...
Conceptual rainfall-runoff models besides precipitation and discharge data generally require estimates of the mean daily air temperature as input data. For the estimation of the mean daily air temperature, there are different methods available. The p...
In this paper, we expand the Hamy mean (HM) operator and Dombi operations with interval-valued intuitionistic fuzzy numbers (IVIFNs) to propose the interval-valued intuitionistic fuzzy Dombi Hamy mean (IVIFDHM) operator, interval-valued intuitionisti...
As house mortgage appraisal values have played a leading role in the 2007–2012 financial crisis, it is important to develop robust mass appraisal models that correctly estimate these values. The present paper intends to propose a methodology to exami...
Preoperative imaging differentiation between ChRCC and RO is difficult with conventional subjective evaluation, and the development of quantitative analysis is a clinical challenge. Forty-nine patients underwent partial or radical nephrectomy precede...
The paper presents an algorithm for calculating the fatigue life of S355J0 steel specimens subjected to cyclic bending, cyclic torsion, and a combination of bending and torsion using mean stress values. The method of transforming cycle amplitudes wit...
Early prediction of the growth and development of plants is important for the intelligent breeding process, yet accurate prediction and simulation of plant phenotypes is difficult. In this work, a prediction model of plant growth and development base...
(1) Background: To avoid affecting the accuracy and practicability of the security federation model due to the geographical and environmental factors involved in each local model and set the corresponding weights for each local model, the local model...
The main aim of this paper is to present the results of research on the application of a modified mathematical model to determine the quality parameters of SBAS (Satellite Based Augmentation System) satellite positioning in aviation. The authors deve...
To study the uncertainties of a collapse susceptibility prediction (CSP) under the coupled conditions of different data-based models and different connection methods between collapses and environmental factors, An’yuan County in China with 108...
Weighted average temperature (Tm) plays a crucial role in global navigation satellite system (GNSS) precipitable water vapor (PWV) retrieval. Aiming at the poor applicability of the existing Tm models in Europe, in the article, we used observations f...
This study examined how different nonhomogeneous soil characteristics affected hydrologic responses in rainfall-runoff models. The cell-based FLO-2D and lumped Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) were setup. Then, water...
Improving forecasts, particularly the accuracy, efficiency, and precision of time-series forecasts, is becoming critical for authorities to predict, monitor, and prevent the spread of the Coronavirus disease. However, the results obtained from the pr...
In this study, the artificial neural networks have been used for the estimation of hourly ambient temperature in Denizli, Turkey. The model was trained and tested with four years (2002-2005) of hourly mean temperature values. The hourly temperature v...
In a real-world implementation, machine learning models frequently experience concept drift when forecasting the electricity load. This is due to seasonal changes influencing the scale, mean, and median values found in the input data, changing their...
of 278