This paper investigates modified function projective synchronization (MFPS) for complex dynamical networks with mixed time-varying and hybrid asymmetric coupling delays, which is composed of state coupling, time-varying delay coupling and distributed time-varying delay coupling. In contrast to previous results, the coupling configuration matrix needs not be symmetric or irreducible. The MFPS of delayed complex dynamical networks is considered via either hybrid control or hybrid pinning control with nonlinear and adaptive linear feedback control, which contains error linear term, time-varying delay error linear term and distributed time-varying delay error linear term. Based on Lyapunov stability theory, adaptive control technique, the parameter update law and the technique of dealing with some integral terms, we will show that control may be used to manipulate the scaling functions matrix such that the drive system and response networks could be synchronized up to the desired scaling function matrix. Numerical examples are given to demonstrate the effectiveness of the proposed method. The results in this article generalize and improve the corresponding results of the recent works.

The theme of this study is to present the impacts and importance of the fractional order derivatives of the susceptible, infected and quarantine (SIQ) model based on the coronavirus with the lockdown effects. The purpose of these investigations is to achieve more accuracy with the use of fractional derivatives in the SIQ model. The integer, nonlinear mathematical SIQ system with the lockdown effects is also provided in this study. The lockdown effects are categorized into the dynamics of the susceptible, infective and quarantine, generally known as SIQ mathematical system. The fractional order SIQ mathematical system has never been presented before, nor solved by using the strength of the stochastic solvers. The stochastic solvers based on the Levenberg-Marquardt backpropagation scheme (LMBS) along with the neural networks (NNs), i.e., LMBS-NNs have been implemented to solve the fractional order SIQ mathematical system. Three cases using different values of the fractional order have been provided to solve the fractional order SIQ mathematical model. The data to present the numerical solutions of the fractional order SIQ mathematical model is selected as 80% for training and 10% for both testing and validation. For the correctness of the LMBS-NNs, the obtained numerical results have been compared with the reference solutions through the Adams–Bashforth–Moulton based numerical solver. In order to authenticate the competence, consistency, validity, capability and exactness of the LMB-NNs, the numerical performances using the state transitions (STs), regression, correlation, mean square error (MSE) and error histograms (EHs) are also provided.

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In solar heating, ventilation, and air conditioning (HVAC), communications are designed to create new 3D mathematical models that address the flow of rotating Sutterby hybrid nanofluids exposed to slippery and expandable seats. The heat transmission investigation included effects such as copper and graphene oxide nanoparticles, as well as thermal radiative fluxing. The activation energy effect was used to investigate mass transfer with fluid concentration. The boundary constraints utilized were Maxwell speed and Smoluchowksi temperature slippage. With the utilization of fitting changes, partial differential equations (PDEs) for impetus, energy, and concentricity can be decreased to ordinary differential equations (ODEs). To address dimensionless ODEs, MATLAB’s Keller box numerical technique was employed. Graphene oxide Copper/engine oil (GO-Cu/EO) is taken into consideration to address the performance analysis of the current study. Physical attributes, for example, surface drag coefficient, heat move, and mass exchange are mathematically processed and shown as tables and figures when numerous diverse factors are varied. The temperature field is enhanced by an increase in the volume fraction of copper and graphene oxide nanoparticles, while the mass fraction field is enhanced by an increase in activation energy.

In this article, we consider the finite-time mixed H ∞ /passivity, finite-time stability, and finite-time boundedness for generalized neural networks with interval distributed and discrete time-varying delays. It is noted that this is the first time for studying in the combination of H ∞ , passivity, and finitetime boundedness. To obtain several sufficient criteria achieved in the form of linear matrix inequalities (LMIs), we introduce an appropriate Lyapunov-Krasovskii function (LKF) including single, double, triple, and quadruple integral terms, and estimating the bound of time derivative in LKF with the use of Jensen's integral inequality, an extended single and double Wirtinger's integral inequality, and a new triple integral inequality. These LMIs can be solved by using MATLAB's LMI toolbox. Finally, five numerical simulations are shown to illustrate the effectiveness of the obtained results. The received criteria and published literature are compared.INDEX TERMS neural networks, Lyapunov-Krasovskii function, H ∞ and passivity, time-varying delays, finite-time bounded

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This paper presents the function projective synchronization problem of neural networks with mixed time-varying delays and uncertainties asymmetric coupling. The function projective synchronization of this model via hybrid adaptive pinning controls and hybrid adaptive controls, composed of nonlinear and adaptive linear feedback control, is further investigated in this study. Based on Lyapunov stability theory combined with the method of the adaptive control and pinning control, some novel and simple sufficient conditions are derived for the function projective synchronization problem of neural networks with mixed time-varying delays and uncertainties asymmetric coupling, and the derived results are less conservative. Particularly, the control method focuses on how to determine a set of pinned nodes with fixed coupling matrices and strength values and randomly select pinning nodes. Based on adaptive control technique, the parameter update law, and the technique of dealing with some integral terms, the control may be used to manipulate the scaling functions such that the drive system and response systems could be synchronized up to the desired scaling function. Finally, numerical examples are given to illustrate the effectiveness of the proposed theoretical results.

Two-dimensional mixed convection radiative nanofluid flow along with the non-Darcy permeable medium across a wavy inclined surface are observed in the present analysis. The transformation of the plane surface from the wavy irregular surface is executed via coordinate alteration. The fluid flow has been evaluated under the outcomes of heat source, thermal radiation, and chemical reaction rate. The nonlinear system of partial differential equations is simplified into a class of dimensionless set of ordinary differential equations (ODEs) through a similarity framework, where the obtained set of ODEs are further determined by employing the computational technique parametric continuation method (PCM) via MATLAB software. The comparative assessment of the current outcomes with the earlier existing literature studies confirmed that the present findings are quite reliable, and the PCM technique is satisfactory. The effect of appropriate dimensionless flow constraints is studied versus energy, mass, and velocity profiles and listed in the form of tables and figures. It is perceived that the inclination angle and wavy surface assist to improve the flow velocity by lowering the concentration and temperature. The velocity profile enhances with the variation of the inclination angle of the wavy surface, non-Darcian term, and wavy surface term. Furthermore, the rising value of Brownian motion and thermophoresis effect diminishes the heat-transfer rate.