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In this paper, we investigate the multiple attribute decision-making problems with picture 2-tuple linguistic information. Then, we utilize arithmetic and geometric operations to develop several picture 2-tuple linguistic aggregation operators. The prominent characteristic of these proposed operators is studied. Then, we have utilized these operators to develop some approaches to solving the picture 2-tuple linguistic multiple attribute decision-making problems. Finally, a practical example for enterprise resource planning (ERP) system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness. [ABSTRACT FROM AUTHOR]

In this article, we extend multi-attributive border approximation area comparison (MABAC) approach to the multiple attribute group decision making with picture 2-tuple linguistic numbers. We review the concept of picture 2-tuple linguistic sets and introduce its corresponding score function, accuracy function, and operational laws. In addition, we propose two aggregation operators of picture 2-tuple linguistic numbers and then develop a method by combining traditional MABAC model with the overall picture 2-tuple linguistic evaluation information. Our proposed method is increasingly accurate and valid even when the conflicting attributes are considered. We also provide a numerical instance for assessing and selecting the renewable energy power generation project to demonstrate the efficacy of our novel model. Finally, we compare our proposed approach with other traditional operators to further show its benefits. [ABSTRACT FROM AUTHOR]

This paper aims to establish several synchronization criteria of competitive complex networks (CCNs) by using fixed-time (FDT) control. In CCNs, the variations of different nodes are diverse if they are influenced by external environment. Here, we design two types of controller to deal with the different variations of nodes. Meanwhile, these designed controllers guarantee the synchronization of the CCNs in a given time. The estimated settling time improves corresponding results in the literature. Furthermore, based on rigorous mathematical proof and the structured comparison system, several FDT synchronization criteria are obtained. Some comparisons are presented to show the advantages of these new theoretical results. The validity of our theoretical results is illustrated by numerical simulations. [ABSTRACT FROM AUTHOR]

Here, nonlinear mixed convective flow of nanomaterials over a porous stretching sheet is discussed. The Buongiorno model is used in the mathematical modeling. Important aspects of Buongiorno model, i.e., Brownian movement and thermophoresis are addressed. Further impact of activation energy, viscous dissipation, Joule heating and nonlinear thermal radiation retained in energy and concentration expressions. Optimization of entropy generation rate is discussed. The governing systems are modeled through dimensionless variables. The series solutions are constructed via OHAM algorithm. Features of various sundry variables are interpreted and deliberated. Our analysis reveals that entropy enhances via higher estimation of Reynolds number, radiation and magnetic variables. Our analysis reveals that Bejan number shows decaying feature via Brinkman number and magnetic parameter. [ABSTRACT FROM AUTHOR]

In this paper, a new hyperchaotic memristor oscillator is proposed. Different dynamical properties of the proposed system such as dissipativity, equilibrium points, and their stabilities, Lyapunov exponents and Kaplan-Yorke dimension are investigated. The system has a line of equilibria. Thus it belongs to the category of systems with hidden attractors. Investigation of the stability of the line of equilibria shows that the line is stable in some intervals and unstable in some others. Bifurcation analysis of the system reveals several coexisting attractors in some range of parameters which indicates multistability. Various coexisting attractors of the proposed system are studied. [ABSTRACT FROM AUTHOR]

This paper is devoted to the passivity analysis of an array model for coupled inertial delayed neural networks (NNs) with impulses under different network structures, namely directed and undirected topologies. Firstly, utilising the information of eigenvectors for the directed coupling matrix, a new Lyapunov functional is constructed, by which, together with the aid of some inequality techniques and network characteristics, the two sets of sufficient criteria are established to, respectively, guarantee the strictly input passivity and strictly output passivity of the impulsive network with directed coupling. Secondly, benefited from the properties of the undirected coupling matrix, some more concise conditions that are easier to be verified for the passivities of the undirected coupled network accompanied by impulsive effects are proposed. Finally, two numerical examples are designed to execute the verification of the derived theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the passivity analysis problem is investigated for a class of discrete-time stochastic neural networks (DSNNs) with randomly occurring mixed time delays (ROMDs). The mixed delays comprise time-varying discrete delays, infinite-distributed delays as well as finite-distributed delays. A set of Bernoulli-distributed white sequences is used to account for the random nature of the occurrence of the mixed time delays. In addition, stochastic disturbances are taken into consideration to describe the state-dependent noises caused possibly by electronic devices and hardware implementation of neural networks. By using a combination of Lyapunov-Krasovskii functional, free-weighting matrix approach and stochastic analysis technique, we establish sufficient conditions guaranteeing the passivity performance of the underlying DSNNs. Furthermore, a delay-dependent robust passivity criterion is presented to deal with the parameter uncertainties in the DSNNs with ROMDs. A simulation example is provided to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Neural network is important for a wide range of applications. Especially, a small neural network can display various complex behaviors. In this work, the investigations of a Hopfield neural network and its field programmable gate array (FPGA) implementation have been reported. The considered Hopfield neural network is simple because it includes only three neurons. It is interesting that we observed chaos and numerous coexisting attractors in such a network. In addition, the network has been implemented via an FPGA platform to verify its feasibility. [ABSTRACT FROM AUTHOR]

The present study investigates the dynamical properties of a fractional order coronary artery system and its control with uncertainties in the parameters. The fractional order model of the coronary artery system (FOCA) is derived using the Grünwald-Letnikov method and the properties of the FOCA system are discussed. Bifurcation plots of the system in the parameter space are derived and presented. The novelty of the paper is the identification of the multistable feature shown by the FOCA system, which has not been discussed in the research literature. Various coexisting attractors are also presented to show the multistability. An adaptive sliding mode controller is designed to stabilize the chaotic oscillations in the FOCA system. Numerical simulations are conducted to indicate the effectiveness of the controller. [ABSTRACT FROM AUTHOR]

This paper investigates the algebraic formulation and control for a class of networked evolutionary games with finite memories and time-varying networks by using the semi-tensor product method and presents a number of new results. Firstly, a kind of algebraic expressions is formulated for the given networked evolutionary games, and the dynamics of the given game is expressed as a finite homogenous Markov chain, based on which, the behaviors of the players in the corresponding evolutionary games are analyzed. Then, the control problem of the given games is studied. Under certain assumptions, the relationship between the strict Nash equilibriums and the fixed points of the given networked evolutionary games is revealed, and a free-type control sequence is designed to guarantee the Nash equilibrium reachable globally. Finally, an illustrative example is studied to support our new results. [ABSTRACT FROM AUTHOR]

We examine the stability problem for delayed neutral-type neural networks (NNs) with interval time-varying delay signals under the effects of leakage term by constructing a suitable Lyapunov–Krasovskii functionals (LKFs) with the triple- and four-integral terms and using the famous Jensen inequality, Wirtinger single integral inequality (WSII), and Wirtinger double integral inequality (WDII), combined with the reciprocally convex approach (RCC) for the stability of addressing NNs. Therefore, the major contribution of this study lies in a consideration of new integral inequalities and improved LKFs, fully taking the relationship between the terms in the Leibniz–Newton formula within the framework of linear matrix inequalities (LMIs). Moreover, we assume that the lower bound of interval time-varying delay is not restricted to zero. Using several examples, we show that the proposed stability criterion is less conservative than previous results. Also, the proposed technique is applied to benchmark problem that is associated with reasonable issues to showing feasibility on a real-world problem, including transporting time delay signals and leakage delay as a process variable in the quadruple-tank process system. [ABSTRACT FROM AUTHOR]