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In this paper, we introduce a new numerical simulation iterative algorithm to solve the split feasibility problem and the fixed point problem with demicontractive mappings. Our algorithm mainly involves primal-dual iterative, relaxed projection, inertial technique and self-adaptive step size. Under reasonable conditions, the strong convergence of our algorithm is established. Moreover, we provide some numerical simulation examples to demonstrate the efficiency of our iterative algorithm compared to existing algorithms in the other literature. [ABSTRACT FROM AUTHOR]

In this paper, we construct two kinds of exponential SAV approach with relaxation (R-ESAV) for dissipative system. The constructed schemes are linear and unconditionally energy stable. They can guarantee the positive property of SAV without any assumption compared with R-SAV and R-GSAV approaches, preserve all the advantages of the ESAV approach and satisfy dissipation law with respect to a modified energy which is directly related to the original free energy. We also give the rigorous consistency estimates of the constructed schemes for the L 2 gradient flows. Moreover, the second version of R-ESAV approach is easy to construct high-order BDF k schemes. Especially for Navier–Stokes equations, we construct two kinds of novel schemes based on the R-ESAV method. Finally, ample numerical examples are presented to exhibit that the proposed approaches are accurate and effective. • R-ESAV schemes can improve the accuracy of the solution significantly compared with the original ESAV approach. • We construct two kinds of novel schemes based on the R-ESAV method for Navier–Stokes equations. • Only one linear system with constant coefficients at each time step needs to be solved. • The positive property of SAV without any assumption can be guaranteed. • Numerical simulations are tested to show that the modified energy equals to the original free energy at almost all times. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, an adaptive algorithm is proposed for synchronization of chaotic systems with different orders. A modular adaptive control strategy is applied to make states of the slave system track those of the master, despite the unknown parameters. One of the most advantages of the modularity approach, which is applied for the first time in chaos synchronization, is its flexibility in choosing identification and control modules and designing them completely independently. In this paper, a modified recursive least square algorithm is used to identify the unknown parameters of the slave system, and the control module is designed by means of two different algorithms. First it is designed based on active control method, and then, in order to synchronize with a lower energy, we design an optimal controller. The two methods are applied on a practical case study, and the results are compared. Two different dimensional neuron models, the HR neuron model and the cable model of cylindrical cell, are considered as the master and slave systems, respectively. Simulation results confirm the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: In this paper we provide numerical evidence, via graphics generated with the help of computer simulations, that switching the control parameter of a dynamical system belonging to a class of fractional-order systems in a deterministic way, one obtains an attractor which belongs to the class of all admissible attractors of the considered system. For this purpose, while a multistep numerical method for fractional-order differential equations approximates the solution to the mathematical model, the control parameter is switched periodically every few integration steps. The switch is made inside of a considered set of admissible parameter values. Moreover, the synthesized attractor matches the attractor obtained with the control parameter replaced with the averaged switched parameter values. The results are verified in this paper on a representative system, the fractional-order Lü system. In this way we were able to extend the applicability of the algorithm presented in earlier papers using a numerical method for fractional differential equations. [Copyright &y& Elsevier]

• Fluid flows must depend on the geometries of given domains or irregularities of given data. In particular, when the datum has a jump discontinuity at a point, a curve started at the point can be generated into the domain and the jump discontinuity is propagated along the curve. The curve is directed by the fluid velocity vector. So the pressure gradient given in the momentum equations is not well-defined across the curve. • Recently we have shown that, when the inflow boundary data has a jump, there is a curve contained in the domain such that the fluid flows have jump there. By constructing a lifting vector field for the pressure jump value on the curve we decompose the solution into the jump part, the contact singularity part and the smoother one. In fact the solutions of the nonlinear compressible Stokes system are (0.1) u = K + Φ + w , p = p b + k + τ + σ , where p b has a jump discontinuity on inflow boundary, the pair (K , k) denotes the jump part, (Φ , τ) the contact singularity and (w , σ) the smoother part. The contact singular part is due to the intersection of the interface curve to the boundary of the domain. It is assumed that we have two contact points, denoted by a j , j = 1 , 2. • We call the curve the interface or jump curve and denote by C. Since the curve is directed by the velocity vector it is important to have a precise structure of the velocity vector. • In this paper we design a finite element numerical scheme based on the decomposition and try to address and confirm the important roles of each component in the decomposition numerically. It has been shown in [8] that the solutions of compressible Stokes flows with inflow jump condition can be decomposed into the jump discontinuity part (due to the pressure jump) plus the contact singularity (to the boundary) plus the smoother one, which is twice differentiable. In this paper we design a numerical scheme of each part in the decomposition and numerically demonstrate its essential role for capturing the jump discontinuity behaviors of the solutions. Several numerical simulations are presented, describing the critical role of each part. It is thought that such algorithm is new in constructing the jump discontinuity solutions. [ABSTRACT FROM AUTHOR]

Abstract: The power generated by wind turbines changes rapidly because of the continuous fluctuation of wind speed and air density. As a consequence, it can be important to predict the energy production, starting from some basic input parameters. The aim of this paper is to show that a two-hidden layer neural network can represent a useful tool to carefully predict the wind energy output. By using proper experimental data (collected from three wind farm in Southern Italy) in combination with a back propagation learning algorithm, a suitable neural architecture is found, characterized by the hyperbolic tangent transfer function in the first hidden layer and the logarithmic sigmoid transfer function in the second hidden layer. Simulation results are reported, showing that the estimated wind energy values (predicted by the proposed network) are in good agreement with the experimental measured values. [Copyright &y& Elsevier]

Abstract: Recently, a variety of chaos-based hash functions have been proposed. Nevertheless, none of them can realize modification localization. In this paper, a hash function with both modification detection and localization capabilities is proposed, which can also support the parallel processing mode. By using the mechanism of changeable-parameter and self-synchronization, the keystream can establish a close relation with the algorithm key, the content, and the order of each message unit. Theoretical analysis and computer simulation indicate that the proposed algorithm can satisfy the performance requirements of hash functions. [Copyright &y& Elsevier]

Abstract: In this paper we propose an alternative way to study robustness and vulnerability of complex networks, applying a modal analysis. The modal weights of the network nodes are considered as a measure for their busyness, which is further used for preferential removal of nodes and attack simulation. Analyses of the attack vulnerability are carried out for several generic graphs, generated according to ER and BA algorithms, as well as for some examples of manmade networks. It was found that a modal weight based attack causes significant disintegration of manmade networks by removing a small fraction of the busiest nodes, comparable to the one based on the node degree and betweenness centrality. [Copyright &y& Elsevier]

Abstract: In this paper, it is studied the dynamics of the robotic bird in terms of time response and robustness. It is analyzed the wing angle of attack and the velocity of the bird, the tail influence, the gliding flight and the flapping flight. The results are positive for the construction of flying robots. The development of computational simulation based on the dynamic of the robotic bird should allow testing strategies and different algorithms of control such as integer and fractional controllers. [Copyright &y& Elsevier]

Abstract: Since the issue of track initiation belongs to the NP-hard problem in the bearings-only multi-sensor-multi-target tracking system, a novel proposed track initiation technique is proposed in this paper. The proposed track initiation technique is based upon an ant colony optimization (ACO) algorithm, a kind of heuristic optimization method. Observing that each target is of the characteristic of uniform rectilinear motion, we develop a new cost function derived from the thought of Hough transform. Numerical simulation results show that the proposed ACO-based track initiation method not only meets the requirement of real time, but also performs better than other traditional techniques, especially in the scenario that all targets move in parallel. [Copyright &y& Elsevier]

Abstract: Chaos is undesirable in many engineering applications since it causes a serious degradation of the system performance and restricts the system’s operating range. Therefore, the problem of controlling chaos has attracted intense interest in recent years. This paper proposes an approach for optimizing the control of chaotic systems with input saturation using an input-state linearization scheme. In the proposed approach, the optimal system gains are identified using the Nelder–Mead simplex algorithm. This algorithm does not require the derivatives of the cost function (or the performance index) to be optimized, and is therefore particularly applicable to problems with undifferentiable elements or discontinuities. Two numerical simulations are performed to demonstrate the feasibility and effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: A block encryption algorithm using dynamic sequences generated by multiple chaotic systems is proposed in this paper. In this algorithm, several one-dimension chaotic maps generate pseudo-random sequences, which are independent and approximately uniform. After a series of transformations, the sequences constitute a new pseudo-random sequence uniformly distributing in the value space, which covers the plaintext by executing Exclusive-OR and shifting operations some rounds to form the cipher. This algorithm makes the pseudo-random sequence possess more concealment and noise like characteristic, and overcomes the periodic malpractice caused by the computer precision and single chaotic system. Simulation results show that the algorithm is efficient and useable for the security of communication system. [Copyright &y& Elsevier]