This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

In order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

Abstract:In this research we prepared nanofibers by electrospinning from poly (Vinyl Alcohol) / TiO2. The spectrum of the solution (Emission) was studied at 772 nm. Several process parameter were Investigated as concentration of PVA, the effect of distance from nozzle tip to the grounded collector (gap distance), and final the effect of high voltage. We find the optimum condition to prepare a narrow nanofibers is at concentration of PVA 16gm, the fiber has 20nm diameter.

In this research we prepared nanofibers by electrospinning
from poly (Vinyl Alcohol) / TiO2. The spectrum of the solution
(Emission) was studied at 772 nm. Several process parameter were
Investigated as concentration of PVA, the effect of distance from
nozzle tip to the grounded collector (gap distance), and final the
effect of high voltage. We find the optimum condition to prepare a
narrow nanofibers is at concentration of PVA 16gm, the fiber has
20nm diameter

A reliable and environmental analytical method was developed for the direct determination of tetracycline using flow injection analysis (FIA) and batch procedures with spectrophotometric detection. The developed method is based on the reaction between a chromogenic reagent (vanadium (III) solution) and tetracycline at room temperature and in a neutral medium, resulting in the formation of an intense brown product that shows maximum absorption at 395 nm. The analytical conditions were improved by the application of experimental design. The proposed method was successfully used to analyze samples of commercial medications and verified throughout the concentration ranges of 25–250 and 3–25 µg/mL for both FIA and batch procedures, respecti

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

Physics and applied mathematics form the basis for understanding natural phenomena using differential equations depicting the flow in porous media, the motion of viscous liquids, and the propagation of waves. These equations provide a thorough study of physical processes, enhancing the understanding of complex applications in engineering, technology, and medicine. This paper presents novel approximate solutions for the Darcy-Brinkmann-Forchheimer moment equation, the Blasius equation and the FalknerSkan equation with initial / boundary conditions by using two iterative methods: the variational iteration method and the optimal variational iteration method. The variational iteration method is effectively developed by adding a control paramete

   Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr

The paper is concerned with the state and proof of the existence theorem of a unique solution (state vector) of couple nonlinear hyperbolic equations (CNLHEQS) via the Galerkin method (GM) with the Aubin theorem. When the continuous classical boundary control vector (CCBCV) is known, the theorem of existence a CCBOCV with equality and inequality state vector constraints (EIESVC) is stated and proved, the existence theorem of a unique solution of the adjoint couple equations (ADCEQS) associated with the state equations is studied. The Frcéhet derivative derivation of the "Hamiltonian" is obtained. Finally the necessary theorem (necessary conditions "NCs") and the sufficient theorem (sufficient conditions" SCs") for optimality of the stat