A new Bernoulli matrix method for solving high-order linear and nonlinear Fredholm integro-differential equations with piecewise intervals

Numerical solution of linear integro-differential equation by using sine–cosine wavelets

In this study, a practical matrix method is presented to find an approximate solution of high-order linear Fredholm integro-differential equations with constant coefficients under the initial-boundary conditions in terms of Taylor polynomials. The method converts the integro-differential equation to a matrix equation, which corresponds to a system of linear algebraic equations. Error analysis and illustrative examples are included to demonstrate the validity and applicability of the technique.

Polynomial solution of high-order linear Fredholm integro-differential equations with constant coefficients

Hybrid functions approach for nonlinear constrained optimal control problems

In this paper, a new numerical method for solving the optimal control of linear time-varying delay systems with quadratic performance index is presented. The method is based upon hybrid functions approximation. The properties of hybrid functions, consisting of block-pulse functions and Bernoulli polynomials, are presented. The operational matrices of integration, product, delay and the integration of the cross product of two hybrid functions of block-pulse and Bernoulli polynomials vectors are given. These matrices are then utilized to reduce the solution of the optimal control of delay systems to the solution of algebraic equations. Illustrative examples are included to demonstrate the validity and applicability of the technique.

Optimal Control of Delay Systems by Using a Hybrid Functions Approximation

Solving second kind integral equations with Hybrid Chebyshev and Block-Pulse functions

We use a combination of Fourier and block-pulse functions on the interval [0, 1], to solve the linear integro differential equation. We convert the integral equation to a system of linear equations. Illustrative examples are included to demonstrate the validity and applicability of the technique.

Direct method for solving integro differential equations using hybrid Fourier and block-pulse functions

Experimental analysis of hybrid dryer combined with spiral solar air heater and auxiliary heating system: Energy, exergy and economic analysis

• Fe N C and Co N C electrocatalysts derived from bimetallic MOF (Zn/Fe-BZIF and Zn/Co-BZIF). • MOF-molecule composites approach strategy with pyrrole monomers was used. • The acceptable ORR performance was observed for Fe N C in both acidic and alkaline media. • Good ORR stability and low ethanol crossover were observed for Fe-based electrocatalyst. • Fe N C as the cathode in a passive alkaline DEFC could reach promising power density. Herein, a ZIF-molecule-composites approach is applied to make nonprecious metal catalysts (NPMCs) throughout the high-temperature thermal treatment of composite bimetallic zeolite imidazole frameworks (Zn/Fe-BZIF and Zn/Co-BZIF) with pyrrole and FeCl 3 (BZIFs@PPy/FeCl 3 ). The prepared electrocatalysts are characterized by XRD, FESEM, TEM, EDX-mapping, BET, Raman, and XPS. The Fe N C electrocatalyst shows superior to its counterpart (Co N C) for ORR (oxygen reduction reaction). Iron-based MOF electrocatalyst exhibits the optimal ORR catalytic performance with high selectivity (direct four-electron reduction of O 2 to H 2 O), high activity, and durability in both alkaline and acidic environment. In acidic conditions, Fe N C represents the comparable onset potential (E onset = 0.90 V RHE ) to the commercial Pt/C (E onset = 0.95 V RHE ), which also far outperforms the Co-based counterpart (Co N C, E onset = 0.77 V RHE ). In addition, under alkaline conditions, Fe N C represents the highest onset potential (E onset = 1.02 V RHE ) versus Pt/C and Co N C (E onset = 1.0 V and 0.74 V RHE , respectively). Moreover, this optimum electrocatalyst (Fe N C) illustrates excellent stability in alkaline media (95% maintenance of initial current density through 10,000 s chronoamperometric measurements). Finally, passive alkaline direct ethanol fuel cell performance is evaluated to obtain the activity of prepared electrocatalysts in alkaline media. The results showed promising fuel cell performance, especially for the Fe-based electrocatalyst (Fe N C 3 h). The current work provides a new horizon towards representing pioneer nonprecious metal and nitrogen-doped carbonaceous structures with an excellent ORR activity and direct ethanol fuel cell performance. 

Metal-Nitrogen co-doped hierarchical porous carbon derived from the bimetallic metal-organic framework as ORR electrocatalyst for passive alkaline direct ethanol fuel cell

Abstract This study came as an attempt to predict the foreign direct investment of the State of Qatar, depending on the model of artificial neural networks and the comparison between its models, because this type of model takes into account the non-linear and stochastic characteristics that characterize the financial and economic chains in general. A multi-layer artificial neural network was built consisting of three layers (the input layer, the hidden layer, the output layer), and the number of training passes was installed 999 times, and the network learning rate was 0.6 and the activation function used is the SIGMOID function using the back propagation algorithm. The MLP (4-10-1) model gave accurate results that are close to the actual values, and it also gave the lowest values for the error measurement criteria represented in the MAE, RMSE and MAPE standards. This reflects the strength of the predicted model, which is consistent with the results of most studies that have been conducted on the subject, both Arab and foreign. It turned out that the feed-forward artificial neural network model is superior to other network models, as the outputs of the hidden layer are inputs for the time following the next time, which can be relied upon as an appropriate method for future prediction of the GDP of the State of Qatar. Also, the forecast values are positive for the period (2020-2040), which encourages increased investor attraction and market recovery in subsequent periods.

Modeling and prediction using an artificial neural network to study the impact of foreign direct investment on the growth rate / a case study of the State of Qatar

A. Heydari

Papers

Solving second kind integral equations with Hybrid Chebyshev and Block-Pulse functions

Direct method for solving integro differential equations using hybrid Fourier and block-pulse functions

Experimental analysis of hybrid dryer combined with spiral solar air heater and auxiliary heating system: Energy, exergy and economic analysis

Metal-Nitrogen co-doped hierarchical porous carbon derived from the bimetallic metal-organic framework as ORR electrocatalyst for passive alkaline direct ethanol fuel cell

Modeling and prediction using an artificial neural network to study the impact of foreign direct investment on the growth rate / a case study of the State of Qatar