An Elastic Collision Seeker Optimization Algorithm for Optimization Constrained Engineering Problems

To improve the seeker optimization algorithm (SOA), an elastic collision seeker optimization algorithm (ECSOA) was proposed. The ECSOA evolves some individuals in three situations: completely elastic collision, completely inelastic collision, and non-completely elastic collision. These strategies enhance the individuals’ diversity and avert falling into the local optimum. The ECSOA is compared with the particle swarm optimization (PSO), the simulated annealing and genetic algorithm (SA_GA), the gravitational search algorithm (GSA), the sine cosine algorithm (SCA), the multiverse optimizer (MVO), and the seeker optimization algorithm (SOA); then, fifteen benchmark functions, four PID control parameter models, and six constrained engineering optimization problems were selected for the experiment. According to the experimental results, the ECSOA can be used in the benchmark functions, the PID control parameter optimization, and the optimization constrained engineering problems. The optimization ability and robustness of ECSOA are better.

Stabiizing The Steady State Solution of Lasser Fever: Problems and Prospect

The study of mathematical modeling of the stability analysis of Lassa fever was examined. A mathematical model for the spread and control of Lassa fever was formulated and analyzed. The model incorporates a control parameter, the use of condom to control human to human transmission through sexual contact with opposite sex. The disease free and endemic equilibrium states were analyzed.

A Complex-Valued Encoding Multichain Seeker Optimization Algorithm for Engineering Problems

This article comes up with a complex-valued encoding multichain seeker optimization algorithm (CMSOA) for the engineering optimization problems. The complex-valued encoding strategy and the multichain strategy are leaded in the seeker optimization algorithm (SOA). These strategies enhance the individuals’ diversity, enhance the local search, avert falling into the local optimum, and are the influential global optimization strategies. This article chooses fifteen benchmark functions, four proportional integral derivative (PID) control parameter models, and six constrained engineering problems to test. According to the experimental results, the CMSOA can be used in the benchmark functions, in the PID control parameter optimization, and in the optimization of constrained engineering problems. Compared to the particle swarm optimization (PSO), simulated annealing based on genetic algorithm (SA_GA), gravitational search algorithm (GSA), sine cosine algorithm (SCA), multiverse optimizer (MVO), and seeker optimization algorithm (SOA), the optimization ability and robustness of the CMSOA are better than those of others algorithms.

Modified method of image histogram hyperbolization

One of the methods to improve image quality, which consists in increasing the resolution of image details by contrast enhancement, is to hyperbolize the image histogram. Herewith this increase in local contrast is carried out indirectly. It is due to the nature of the change in the histogram of the transformed image. Usually the histogram of the input image is transformed so that it has a uniform distribution, which illustrates the same contribution of pixels gray level to the image structure. However, there is a method that is based on modeling the human visual system, which is characterized by the logarithmic dependence of the human reaction to light stimulation. It consists in the hyperbolic transformation of the histogram of the image. Then, due to its perception by the visual system, at its output, during the psychophysical perception of the image, an approximately uniform distribution of the histogram of the levels of gray pixels is formed. But the drawback is the lack of effectiveness of this approach for excessively light or dark images. The modified method of image histogram hyperbolization has been developed. It is based on the power transformation of the probability distribution function, which in the discrete version of the images is approximated by a normalized cumulative histogram. The power index is a control parameter of the transformation. to improve the darkened images we use the value of the control parameter less than one, and for light images more than one. The effectiveness of the proposed method is shown by examples.

A Modification of Gustavsen and Semlyen’s vector fitting algorithm for overestimated model order

Gustavsen and Semlyen’s vector fitting algorithm (VFA) is popular for the determination of the poles and residues of a sampled response function, modeled as a finite order rational function. However, it does not always perform well when the original function is of infinite order and/or the model order is overestimated. This article is concerned with a novel “null-space” modification of the VFA that provides an accurate representation of the original function when the model order is large and when the original VFA performs poorly. The null-space method is parameterized by a single control parameter, L, which can be adjusted to improve accuracy. Comparisons are made with the original VFA and another of Gustavsen’s modifications

A Modification of Gustavsen and Semlyen’s vector fitting algorithm for overestimated model order

Gustavsen and Semlyen’s vector fitting algorithm (VFA) is popular for the determination of the poles and residues of a sampled response function, modeled as a finite order rational function. However, it does not always perform well when the original function is of infinite order and/or the model order is overestimated. This article is concerned with a novel “null-space” modification of the VFA that provides an accurate representation of the original function when the model order is large and when the original VFA performs poorly. The null-space method is parameterized by a single control parameter, L, which can be adjusted to improve accuracy. Comparisons are made with the original VFA and another of Gustavsen’s modifications

Interval of restitution coefficient for chattering in impact damper

Based on the impact damper, a dynamic model of a non-fixed constrained collision system was established. The coefficient of restitution is used as the main control parameter to analyze the system’s periodic movement and its bifurcation region. The chattering movement characteristics of the system were revealed. The interval of restitution coefficient for the chattering of collision system under various mass ratio and frequency ratio was obtained. The results show that the chattering phenomenon occurs in the collision system when the coefficient of restitution is greater than 0.5; as the mass ratio decreases, the interval of restitution coefficient for chattering continues to expand; as the frequency increases, the interval of restitution coefficient for chattering narrows.

Fixed-Time Synchronization Control of Delayed Dynamical Complex Networks

Fixed-time synchronization problem for delayed dynamical complex networks is explored in this paper. Compared with some correspondingly existed results, a few new results are obtained to guarantee fixed-time synchronization of delayed dynamical networks model. Moreover, by designing adaptive controller and discontinuous feedback controller, fixed-time synchronization can be realized through regulating the main control parameter. Additionally, a new theorem for fixed-time synchronization is used to reduce the conservatism of the existing work in terms of conditions and the estimate of synchronization time. In particular, we obtain some fixed-time synchronization criteria for a type of coupled delayed neural networks. Finally, the analysis and comparison of the proposed controllers are given to demonstrate the validness of the derived results from one numerical example.