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.
The main work of this paper is devoted to a new technique of constructing approximated solutions for linear delay differential equations using the basis functions power series functions with the aid of Weighted residual methods (collocations method, Galerkin’s method and least square method).
Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem
... Show MoreThe main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola
... Show MoreIn this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
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The research aims to study and analysis of concurrent engineering (CE) and cost optimization (CO), and the use of concurrent engineering inputs to outputs to improve the cost, and the statement of the role of concurrent engineering in improving the quality of the product, and achieve savings in the design and manufacturing time and assembly and reduce costs, as well as employing some models to determine how much the savings in time, including the model (Lexmark) model (Pert) to determine the savings in design time for manufacturing and assembly time.
To achieve the search objectives, the General Company for Electrical and Electronic Industries \ Refrigerated Engine
... Show MoreThis research aims to predict the value of the maximum daily loss that the fixed-return securities portfolio may suffer in Qatar National Bank - Syria, and for this purpose data were collected for risk factors that affect the value of the portfolio represented by the time structure of interest rates in the United States of America over the extended period Between 2017 and 2018, in addition to data related to the composition of the bonds portfolio of Qatar National Bank of Syria in 2017, And then employing Monte Carlo simulation models to predict the maximum loss that may be exposed to this portfolio in the future. The results of the Monte Carlo simulation showed the possibility of decreasing the value at risk in the future due to the dec
... Show MoreThis study focuses on studying an oscillation of a second-order delay differential equation. Start work, the equation is introduced here with adequate provisions. All the previous is braced by theorems and examplesthat interpret the applicability and the firmness of the acquired provisions
This paper deals with constructing mixed probability distribution from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are ( .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β) are estimated by three different methods, which are maximum likelihood, and Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.