In this paper, an improved particleswarmoptimization (PSO) algorithm, which can perform a global search over the search space with a faster convergence speed, is proposed for frequency-selective surface (FSS) design...
详细信息
In this paper, an improved particleswarmoptimization (PSO) algorithm, which can perform a global search over the search space with a faster convergence speed, is proposed for frequency-selective surface (FSS) design. Four improvement strategies including better particle initialization, acceleration coefficient dynamic adjustment, search space reset, and particle density control are applied to PSO algorithm aiming to accelerate convergence and, at the same time, improve its search capability. For verification, the improved PSO algorithm has been successfully implemented to the square loop FSS design. Then, the optimized results are compared to those obtained by the standard PSO algorithm as well as those existing in the literature, respectively, proving that the improved PSO algorithm has the capacity for accelerating convergence on the premise of ensuring the optimization accuracy.
In order to improve the security of information storage in multi-domain optical network privacy protection, hybrid encoding and encryption of privacy protection information in multi-domain optical network is carried o...
详细信息
In order to improve the security of information storage in multi-domain optical network privacy protection, hybrid encoding and encryption of privacy protection information in multi-domain optical network is carried out. A hybrid coding and secure encryption technique based on particleswarmoptimization (PSO) for privacy protection information in multidomain optical network is proposed. The coding mapping equation of privacy protection information security encryption in multi-domain optical network is constructed, and the privacy protection information of multi-domain fiber network is loaded into the coding mapping equation of security encryption of privacy protection information in multi-domain fiber network. A set of characteristic solutions describing the entropy function of the characteristic distribution of random encryption keys are obtained, and the elliptic mapping random linear combination coding and chaotic encryption key allocation are carried out. The privacy protection method of multi-domain optical fiber network is used to encrypt and decode information with mixed coding and steganography. Under the bilinear mapping coding system, the privacy-protected information in multidomain optical network is encrypted and encrypted, stored and transmitted confidently. The simulation results show that this encryption technique has better steganography performance and better secure transmission and storage performance for the privacy protection information mixed encoding encryption in multi-domain optical network.
Power Scheduling Problem (PSP) is a problem of schedule the smart home appliances at appropriate time period according to an electricity pricing scheme. The smart home appliances can be scheduled by shifting their tim...
详细信息
ISBN:
(纸本)9781538679425
Power Scheduling Problem (PSP) is a problem of schedule the smart home appliances at appropriate time period according to an electricity pricing scheme. The smart home appliances can be scheduled by shifting their time operations from period to another. The significant objective of the scheduling process is to reduce the electricity bill and Peak-to-average ratio (PAR) and improve the user comfort level. In this paper, particleswarmoptimization (PSO) algorithm is adapted in order to handle the PSP and to obtain an optimal smart home appliances schedule. Smart battery (SB) is formulated and used in this work to enhance the schedule of the appliances by storing the power at low peak periods and use the stored power by the smart home appliances at peak periods. The simulation results proved the efficiency of using the proposed SB in terms of reducing electricity bill and improving the user comfort level. In addition, PSO is compared with genetic algorithm (GA) in order to evaluate its performance. PSO outperforms GA in terms of achieving the PSP objectives.
A Voltage lift performance is an excellent role to DC/DC conversion topology. The Voltage Lift Multilevel Inverter (VL-MLI) topology is suggested with minimal number of components compared to the conventional multilev...
详细信息
A Voltage lift performance is an excellent role to DC/DC conversion topology. The Voltage Lift Multilevel Inverter (VL-MLI) topology is suggested with minimal number of components compared to the conventional multilevel inverter (MLI). In this method, the Modified particleswarmoptimization (MPSO) conveys a primary task for the VL-MLI using Half Height (H-H) method, it determine the required optimum switching angles to eliminate desired value of harmonics. The simulation circuit for fifteen level output uses single switch voltage-lift inverter fed with resistive and inductive loads (R & L load). The power quality is developed by voltage-lift multilevel inverter with minimized harmonics under the various Modulation Index (MI) while varied from 0.1 up to 1. The circuit is designed in a Field Programmable Gate Array (FPGA), which includes the MPSO rules for fast convergence to reduce the lower order harmonics and finds the best optimum switching angle values. To report this problem the H-H has implemented with MPSO to reduce minimum Total Harmonic Distortion (THD) for simulation circuit using Proteus 7.7 simulink tool. Due to the absence of multiple switches, filter and inductor element exposes for novelty of the proposed system. The comparative analysis has been carried-out with existing optimization and modulation methods.
An application based on a microservice architecture with a set of independent, fine-grained modular services is desirable, due to its low management cost, simple deployment, and high portability. This type of containe...
详细信息
An application based on a microservice architecture with a set of independent, fine-grained modular services is desirable, due to its low management cost, simple deployment, and high portability. This type of container technology has been widely used in cloud computing. Several methods have been applied to container-based microservice scheduling, but they come with significant disadvantages, such as high network transmission overhead, ineffective load balancing, and low service reliability. In order to overcome these disadvantages, in this study, we present a multi-objective optimization problem for container-based microservice scheduling. Our approach is based on the particle swarm optimization algorithm, combined parallel computing, and Pareto-optimal theory. The particle swarm optimization algorithm has fast convergence speed, fewer parameters, and many other advantages. First, we detail the various resources of the physical nodes, cluster, local load balancing, failure rate, and other aspects. Then, we discuss our improvement with respect to the relevant parameters. Second, we create a multi-objective optimization model and use a multi-objective optimization parallel particle swarm optimization algorithm for container-based microservice scheduling (MOPPSO-CMS). This algorithm is based on user needs and can effectively balance the performance of the cluster. After comparative experiments, we found that the algorithm can achieve good results, in terms of load balancing, network transmission overhead, and optimization speed.
optimization methodologies are being utilized in various structural designing practices to solve size, shape and topology optimization problems. A heuristic particleswarmoptimization (HPSO) algorithm was anticipated...
详细信息
optimization methodologies are being utilized in various structural designing practices to solve size, shape and topology optimization problems. A heuristic particleswarmoptimization (HPSO) algorithm was anticipated in this article in order to address the size optimization problem of truss with stress and displacement constraints. This article contributes in improvisation in the truss structure design rationality while reducing the engineering cost by proposing the HPSO approach. Primarily, the basic principle of the original PSO algorithm is presented, then the compression factor is established to improve the PSO algorithm, and a reasonable parameter setting value is presented. To validate the performance of the proposed optimization approach, various experimental illustrations were performed. The results show that the convergence history of experimental illustration 2 and experimental illustration 3 is optimal. The experimental illustration 2 converges after about 150 iterations, however, the experimental illustration 3 is close to the optimal solution after about 500 iterations. Therefore, the PSO algorithm can successfully optimize the size design of truss structures, and the algorithm is also time efficient. The improved PSO algorithm has good convergence and stability, and can effectively optimize the size design of truss structures.
The unequal area facility layout problem(UA-FLP) is to place some objects in a specified space according to certain requirements,which is a NP-hard problem in mathematics because of the complexity of its solution,the ...
详细信息
The unequal area facility layout problem(UA-FLP) is to place some objects in a specified space according to certain requirements,which is a NP-hard problem in mathematics because of the complexity of its solution,the combination explosion and the complexity of engineering *** swarmoptimization(PSO) algorithm is a kind of swarm intelligence algorithm by simulating the predatory behavior of *** at the minimization of material handling cost and the maximization of workshop area utilization,the optimization mathematical model of UA-FLPP is established,and it is solved by the particleswarmoptimization(PSO) algorithm which simulates the design of birds' predation *** improved PSO algorithm is constructed by using nonlinear inertia weight,dynamic inertia weight and other methods to solve static unequal area facility layout *** effectiveness of the proposed method is verified by simulation experiments.
The bonding performance of the interface between two concrete layers is of great importance for China Rail Track System III (CRTS III) slab ballastless track structure. While the bonding performance is close to the di...
详细信息
The bonding performance of the interface between two concrete layers is of great importance for China Rail Track System III (CRTS III) slab ballastless track structure. While the bonding performance is close to the distribution and amounts of defects such as the bubble or the void on the bonding interface. In this paper, combining the Support Vector Machine (SVM) with the particleswarmoptimization (PSO) algorithm, named SVM-PSO algorithm is used to predict the splitting tensile strength of the bonding interface based on the distribution of defects. And the influence of different parameters in the SVM-PSO algorithm on the prediction ability is discussed. Results indicate that the relative error between the average strength value of every 100 predictions and the experimental strength value is less than 5%. The achievements will provide an effective method for predicting the splitting tensile strength of the bonding interface between two concrete layers like CRTS III slab ballastless track structure in practice.
In photovoltaic power generation systems, pv arrays are often affected by local shadow phenomena, resulting in the unstable operation of the system and the reduction of output power. In addition, pv array's p-u ch...
详细信息
In photovoltaic power generation systems, pv arrays are often affected by local shadow phenomena, resulting in the unstable operation of the system and the reduction of output power. In addition, pv array's p-u characteristic curve will show multiple peaks, and the traditional maximum power point tracking(MPPT) algorithm cannot complete the tracking of the maximum power point because it can only find the single peak. particleswarmoptimization(PSO) algorithm has good global optimization ability of multi-peak, which is widely used in tracking the maximum power point of local shadow. However, PSO algorithm has the shortcoming of insufficient convergence speed and low search accuracy. Therefore, a particleswarmoptimization(YSPSO) algorithm with compression factor is proposed to effectively improve the global search ability and local improvement ability of the whole algorithm.
With the increasing use of inverters in the industry, the need to reduce the output harmonics is felt more than ever. Interstellar multi-level structures have grown exponentially due to benefits such as harmonic reduc...
详细信息
ISBN:
(纸本)9781728131498
With the increasing use of inverters in the industry, the need to reduce the output harmonics is felt more than ever. Interstellar multi-level structures have grown exponentially due to benefits such as harmonic reduction and loss reduction. In multi-level inverters, nonlinear and complex equations become more complex when the number of surfaces increases. One of the ways to find optimal keying angles is to reduce the harmonics of the whole Newton-Raphson method. One of the main disadvantages of the Newton-Raphson method is the strong dependence of the answers to the initial guesses. By choosing different initial guesses, different answers may be obtained or results will not converge. And their solution is not possible by conventional methods of numerical solution of nonlinear equations such as the Newton-Ruffson method. In this thesis, one of a variety of Intelligent algorithms is used to solve the Newton-Raphson method problem. The particleswarmalgorithm has been selected based on the proper background in solving problems of high complexity to solve the problem of optimal keying angles in this dissertation. In this thesis, the particleswarmalgorithm has been improved. Simulation results for various multilevel converters have been presented and represent the high efficiency of the improved type of particleswarmalgorithm in determining the appropriate angle of fire for reducing the high harmonics and generating a waveform with very low harmonic distortion and near sinusoidal.
暂无评论