This work aims to propose a new analyzing tool, called the fractional iteration algorithm I for finding numerical solutions of nonlinear time fractional-order Cauchy reaction-diffusion model equations. The key property suggested technique is its ability and flexibility investigate linear models conveniently accurately. proposed approach can be utilized without use any transformation, Adomian polynomials, small perturbation, discretization or linearization. main feature algorithm-I...

The role of integer and noninteger order partial differential equations (PDE) is essential in applied sciences engineering. Exact solutions these are sometimes difficult to find. Therefore, it takes time develop some numerical techniques find accurate types equations. This work aims present a novel approach termed as fractional iteration algorithm-I for finding the solution nonlinear proposed developed tested on fractional-order Fornberg–Whitham equation employed without using any...

Variational iteration method has been extensively employed to deal with linear and nonlinear differential equations of integer fractional order. The key property the technique is its ability flexibility investigate models conveniently accurately. current study presents an improved algorithm variational algorithm-II (VIA-II) for numerical treatment diffusion as well convection-diffusion equations. This newly introduced modification termed modified (MVIA-II). convergence MVIA-II studied in...

The problem of solving linear equations is considered as one the fundamental problems commonly encountered in science and engineering. In this article, complex-valued time-varying matrix equation (CVTV-LME) investigated. Then, by employing a complex-valued, QR (CVTVQR) decomposition, zeroing neural network (ZNN) method, equivalent transformations, Kronecker product, vectorization techniques, we propose study CVTVQR decomposition-based (CVTVQR-LME) model. addition to usage further advantage...

This paper presents a recurrent neural network (RNN) for computing the Drazin inverse of real matrix in time. is composed n independent parts (subnetworks), where order input matrix. These subnetworks can operate concurrently, so parallel and distributed processing be achieved. In this way, computational advantages over existing sequential algorithms attained real-time applications. The RNN defined convenient an implementation electronic circuit. number neurons same as elements output...

The Zhang neural network (ZNN) has recently realized remarkable success in solving time-varying problems. Harmonic noise widely exists industrial applications and can severely affect the solution computed by ZNN models. This article attempts to solve aforementioned limitations providing first design with an inherent capability prohibit harmonic noise. Moreover, it opens new opportunities shift research on ZNNs ideal situations that theoretical consideration nonideal working environments. We...

The problem of portfolio management relates to the selection optimal stocks, which results in a maximum return investor while minimizing loss. Traditional approaches usually model as convex optimization and require calculation gradient. Note that gradient-based methods can stuck at local optimum for complex problems simplification convex, further solved using methods, is high cost solution accuracy. In this paper, we formulate nonconvex problem, considers transaction cardinality constraint,...

A correlation between fuzzy logic systems (FLS) and zeroing neural networks (ZNN) design is investigated. It shown that the gain parameter included in ZNN can be dynamically adjusted over time by means of an appropriate value derived as output a properly defined FLS, which includes appropriately membership functions rules. Dynamical are applicable to time-varying rank-deficient matrices proposed. Convergence properties investigated illustrative simulation experiments performed. Presented...

Neutrosophic sets have been recognized as an effective approach in solving complex decision-making (DM) problems, mainly when such problems are related to uncertainties, published numerous articles thus far. The use of the three membership functions that can be used express accuracy, inaccuracy, and indeterminacy during evaluation alternatives multiple-criteria DM said a significant advantage these sets. By utilizing functions, neutrosophic provide efficient flexible alternatives, even if...

In this article, a simple and new algorithm is proposed, namely the modified variational iteration algorithm-I (mVIA-I), for obtaining numerical solutions to different types of fifth-order Korteweg de-Vries (KdV) equations. order verify precision, accuracy stability mVIA-I method, generated results are compared with Laplace decomposition Adomian Homotopy perturbation transform method method. Comparison mentioned methods reveals that computationally attractive, exceptionally productive...

A special recurrent neural network (RNN), that is the zeroing (ZNN), adopted to find solutions time-varying quadratic programming (TVQP) problems with equality and inequality constraints. However, there are some weaknesses in activation functions of traditional ZNN models, including convex restriction redundant formulation. With aid different functions, modified models obtained overcome drawbacks for solving TVQP problems. Theoretical experimental research indicate proposed better more...

Engineering design optimization problems are difficult to solve because the objective function is often complex, with a mix of continuous and discrete variables various constraints. Our research presents novel hybrid algorithm that integrates benefits sine cosine (SCA) artificial bee colony (ABC) address engineering problems. The SCA recently developed metaheuristic many advantages, such as good search ability reasonable execution time, but it may suffer from premature convergence. enhanced...

The Markowitz model, a Nobel Prize winning model for portfolio analysis, paves the theoretical foundation in finance modern investment. However, it remains challenging problem high frequency trading (HFT) era to find more time efficient solution especially when considering circumstances with dynamic fluctuation of stock prices and desire pursue contradictory objectives less risk but return. In this paper, we establish recurrent neural network address runtime. Rigorous analysis on convergence...

High-frequency trading proposes new challenges to classical portfolio selection problems. Especially, the timely and accurate solution of portfolios is highly demanded in financial market nowadays. This article makes progress along this direction by proposing novel neural networks with softmax equalization address problem. To best our knowledge, first time that technique used deal equation constraints selections. Theoretical analysis shows proposed method globally convergent optimum...