Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawbacks as well as fuzzy differential equations, especialy for electrical circuits and machines. In contrast to the previous works that mainly adopted the symmetric triangular fuzzy coefficients without any theoretical considerations, the proposed framework provides a mathematical foundation for fuzzy membership selection and examines the robustness of the estimators under symmetric triangular, asymmetric triangular, and trapezoidal fuzzy topologies. To evaluate the performance of the system, a Monte Carlo simulation framework is implemented under six sample sizes (T = 10, 15, 20, 30, 50, 100) and under different levels of structural complexity. The simulation results show that the QP method is always superior to the LP paradigm in terms of the estimation error of the center trajectory and the spread of uncertainty of the parameters in terms of Fuzzy Degree (FD). This is especially true in small sample situations, where the operational advantage is more pronounced, making it particularly useful for systemic modeling in data-sparse situations. Moreover, the proposed framework-based fuzzy differential equation offers a mathematically efficient tool to model mysterious engineering systems like network-based smart grids, control models, communication systems, and cyber-based frameworks. The combination of fuzzy dynamic approaches allows a reliable scheme and uncertainty quantification-based system for complex engineering environmental conditions, whereas deterministic schemes are becoming inadequate.
This paper presents the first data for bremsstrahlung buildup factor (BBUF) produced by the complete absorption of Y-91 beta particles in different materials via the Monte Carlo simulation method. The bremsstrahlung buildup factors were computed for different thicknesses of water, concrete, aluminum, tin and lead. A single relation between the bremsstrahlung buildup factor BBUF with both the atomic number Z and thickness X of the shielding material has been suggested.
This study emphasizes the infinite-boundary integro-differential equation. To examine the approximate solution of the problem, two modified optimization algorithms are proposed based on generalized Laguerre functions. In the first technique, the proposed method is applied to the original problem by approximating the solution using the truncated generalized Laguerre polynomial of the unknown function, optimizing coefficients through error minimization, and transforming the integro-differential equation into an algebraic equation. In contrast, the second approach incorporates a penalty term into the objective function to effectively enforce boundary and integral constraints. This technique reduces the original problem to a mathematical optimi
... Show MoreThis research aims to identify the means and forms of interactive communication concerning Iraqi topics on the websites of global radio stations, namely Sawa and Monte Carlo. It also seeks to uncover the editorial and artistic interactions related to Iraqi topics on the selected websites chosen as the research sample, comparing them with the editorial interaction within the Iraqi context between the Radio Monte Carlo and Sawa websites.
The research yields several conclusions, including the following:
Iraqis focus their interaction with topics related to Iraq on Facebook for both Radio Monte Carlo and Sawa; Arabs show higher levels of interaction on Twitter with Radio Monte Carlo; Participants on the webs
Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem
... Show MoreThis article introduces a novel procedure to detect an approximate solution to Fredholm fractional integro-differential equations with linear type (LFFIDE) defined using Caputo fractional derivative. The new procedure approximates the solution using three types of polynomials: Laguerre polynomials, Hermite polynomials, and Legendre polynomials, thereafter transforming the problem into a linear programming problem. The approximate solutions are compared using testing examples to examine the efficiency of the suggested approach. Also, a comparison with the other methods using the same polynomials illustrates The effectiveness and consistency of the proposed technique. Finally, the error analysis of the proposed technique and convergent are di
... Show MoreA new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever
... Show MoreThe advancement of digital technology has increased the deployment of wireless sensor networks (WSNs) in our daily life. However, locating sensor nodes is a challenging task in WSNs. Sensing data without an accurate location is worthless, especially in critical applications. The pioneering technique in range-free localization schemes is a sequential Monte Carlo (SMC) method, which utilizes network connectivity to estimate sensor location without additional hardware. This study presents a comprehensive survey of state-of-the-art SMC localization schemes. We present the schemes as a thematic taxonomy of localization operation in SMC. Moreover, the critical characteristics of each existing scheme are analyzed to identify its advantages
... Show MoreIn this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this
... Show MoreIn this paper, a new analytical method is introduced to find the general solution of linear partial differential equations. In this method, each Laplace transform (LT) and Sumudu transform (ST) is used independently along with canonical coordinates. The strength of this method is that it is easy to implement and does not require initial conditions.
The temperature distributions are to be evaluated for the furnace of Al-Mussaib power plant. Monte Carlo simulation procedure is used to evaluate the radiation heat transfer inside the furnace, where the radiative transfer is the most important process occurring there. Weighted sum of gray-gases model is used to evaluate the radiative properties of the non gray gas in the enclosure. The energy balance equations are applied for each gas, and surface zones, and by solving these equations, both the temperature, and the heat flux are found.
Good degree of accuracy has been obtained, when comparing the results obtained by the simulation with the data of the designing company, and the data obtained by the zonal method. In
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