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...

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...

The knapsack problem is a in combinatorial optimization, and many such problems, exhaustive search not tractable. In this paper, we describe analyze the randomized time‐varying (RTVKP) as integer linear programming (TV‐ILP) problem. way, present on‐line solution to RTVKP optimization highlight restrictions of static methods. addition, applied field finance converted into portfolio insurance Our methodology confirmed by simulation tests real‐world data sets, order explain being an excellent...

Many researchers have investigated the time-varying (TV) matrix pseudoinverse problem in recent years, for its importance addressing TV problems science and engineering. In this paper, of calculating inverse or an arbitrary real is considered addressed using singular value decomposition (SVD) zeroing neural network (ZNN) approaches. Since SVD frequently used to compute a matrix, research proposes new ZNN model based on method as well technique Tikhonov regularization, solving continuous...

Minimum-cost portfolio insurance (MCPI) is a well-known investment strategy that tries to limit the losses may incur as stocks decrease in price without requiring manager sell those stocks. In this research, we define and study time-varying MCPI problem linear programming problem. More precisely, using real-world datasets, three different error-correction neural networks are employed address financial continuous-time. These network solvers zeroing (ZNN), linear-variational-inequality...

The preface provides an overview of the III International Workshop “Hybrid Methods Modeling and Optimization in Complex Systems” (HMMOCS-III 2024), held from December 2-4, 2024, Krasnoyarsk, Russian Federation. workshop brought together international experts to discuss advanced topics mathematical modeling, optimization, complex systems. proceedings contain 50 selected papers reflecting latest advancements hybrid methods interdisciplinary approaches modeling optimizing

Because the banking business is growing, more people are seeking for bank loans, although banks can only lend to a certain number of applicants because they have limited amount assets to. Hence, in order save lot resources, industry particularly concerned developing ways lower risk element involved selecting safe applicant. These days, applicant requires less work thanks machine intelligence. In light this, new weights and structure determination (WASD) neuronet has been developed address...

The convergence and durability of zeroing neural networks (ZNN), a special family recurrent networks, have been the subject much recent research. Numerous time-varying problems in science engineering successfully solved by ZNN dynamics. An improvement design for calculating dynamic alternating current (AC) an electrical network, which is specific linear matrix equation problem, proposed this paper utilizing suitable defined neutrosophic-logic system (NS). In particular, gain parameter...

The influence of neutrosophy on many fields science and technology, as well its numerous applications, are evident. Our motivation is to apply for the first time in order improve methods solving unconstrained optimization. Particularly, this research, we propose investigate an improvement line search nonlinear optimization models. based application symmetry involved neutrosophic logic determining appropriate step size class descent direction methods. Theoretical analysis performed show...

The core components of both traditional and contemporary control systems are the proportional–integral–derivative (PID) systems, which have established themselves as standards for technical industrial applications. Therefore, tuning PID controllers is high importance. Utilizing optimization algorithms to reduce mean square error controller's output one approach controllers. In this paper, an appropriately modified metaheuristic algorithm dubbed beetle antennae search (BAS) employed robust...

<abstract><p>The importance of quaternions in a variety fields, such as physics, engineering and computer science, renders the effective solution time-varying quaternion matrix linear equation (TV-QLME) an equally important interesting task. Zeroing neural networks (ZNN) have seen great success solving TV problems real complex domains, while matrices may be readily represented either or matrix, magnified size. On that account, three new ZNN models are developed TV-QLME is solved...

The efficient solution of the time-varying quaternion matrix inverse (TVQ-INV) is a challenging but crucial topic due to significance quaternions in many disciplines, including physics, engineering, and computer science. main goal this research employ higher-order zeroing neural network (HZNN) strategy address TVQ-INV problem. HZNN family models that correlates hyperpower iterative methods with adjustable convergence order. Particularly, three novel are created order solve both directly...

The proportional–integral–derivative (PID) control systems, which have become a standard for technical and industrial applications, are the fundamental building blocks of classical modern systems. In this paper, three-layer feed-forward neural network (NN) model trained to replicate behavior PID controller is employed stabilize systems through NN feedback controller. A novel bio-inspired weights-and-structure-determination (BIWASD) algorithm, incorporates metaheuristic optimization algorithm...

This research introduces three novel zeroing neural network (ZNN) models for addressing the time-varying Yang–Baxter-like matrix equation (TV-YBLME) with arbitrary (regular or singular) real (TV) input matrices in continuous time. One ZNN dynamic utilizes error directly arising from involved TV-YBLME. Moreover, two are proposed using basic properties of YBLME, such as splitting YBLME and sufficient conditions a to solve YBLME. The Tikhonov regularization principle enables TV-YBLME an TV...

Numerous people are applying for bank loans as a result of the banking industry's expansion, but because banks only have certain amount assets to lend to, they can do so number applicants. Therefore, industry is very interested in finding ways reduce risk factor involved choosing safe applicant order save lots resources. These days, machine learning greatly reduces work needed choose applicant. Taking this into account, novel weights and structure determination (WASD) neural network has been...

The tangency portfolio, also known as the market is most efficient portfolio and arises from intercept point of Capital Market Line (CML) frontier. In this paper, a binary optimal under cardinality constraint (BOTPCC) problem defined studied nonlinear programming (NLP) problem. Because such NLP problems are widely approached by heuristic, beetle antennae search algorithm employed to provide solution BTPSCC Our method proved be magnificent substitute other evolutionary algorithms in...