基于电子优化算法的项目工期-成本优化

针对不同工序多方案条件下的项目工期-成本优化问题,引入了一种新的算法——电子优化算法(Electimize).在建立工期-成本优化的数学模型并简要介绍算法原理的基础上,应用MATLAB软件对算法进行编程,引入精英档案存储提高寻优效率,实现了最低成本对应的最优工期搜索.针对一个经典算例,采用电子优化算法进行优化,并将其结果与遗传算法和枚举法的结果进行对比,进而验证了该算法的可行性与适用性.

Ka波段空间行波管双阳极电子枪设计与优化

利用EGUN软件设计了一把导流系数为0.07μP的Ka波段空间行波管双阳极电子枪。该枪为皮尔斯型电子枪,双阳极分别为控制阳极(2.58 kV)和离子拒止阳极(9 kV)。该设计应用综合迭代法的计算结果进行初步设计,通过调整设计第一阳极,建立考虑导流系数、注腰半径和层流性的电子注性能优化目标函数,应用量子粒子群算法结合MATLAB与EGUN软件对电子枪阳极头位置进行了优化,优化结果满足了空间行波管对电子注的注腰半径和层流性的设计要求。

Micro-vibration response analysis and its application of electronic workshop raw land based on whale optimization algorithm

Environmental micro-vibration is one of the key factors impacting the running of electronic workshop.Low frequency micro-vibration has a significant influence on the normal operation of high precision machining and testing equipment,and even causes irreversible damage to the equipment.Micro-vibration testing and response analysis are important to guide the vibration isolation design and ensure the stable operation of various precision equipment in the workshop.Parameters of Davidenkov model are fitted based on whale swarm optimization algorithm,and its applicability is verified.At the same time,taking the testing project of an electronic workshop raw land as an example,the micro-vibration response is analyzed.The results show that the nonlinear constitutive model constructed by whale optimization algorithm can simulate the dynamic nonlinear behavior of soil under the action of micro-vibration better.Compared with the traditional equivalent linearization method,the nonlinear constitutive model based on the whale optimization algorithm has a smaller acceleration response value.It can effectively suppress the“virtual resonance effect”produced by the equivalent linearization method.

Temperature prediction model for a high-speed motorized spindle based on back-propagation neural network optimized by adaptive particle swarm optimization

To predict the temperature of a motorized spindle more accurately,a novel temperature prediction model based on the back-propagation neural network optimized by adaptive particle swarm optimization(APSO-BPNN)is proposed.First,on the basis of the PSO-BPNN algorithm,the adaptive inertia weight is introduced to make the weight change with the fitness of the particle,the adaptive learning factor is used to obtain different search abilities in the early and later stages of the algorithm,the mutation operator is incorporated to increase the diversity of the population and avoid premature convergence,and the APSO-BPNN model is constructed.Then,the temperature of different measurement points of the motorized spindle is forecasted by the BPNN,PSO-BPNN,and APSO-BPNN models.The experimental results demonstrate that the APSO-BPNN model has a significant advantage over the other two methods regarding prediction precision and robustness.The presented algorithm can provide a theoretical basis for intelligently controlling temperature and developing an early warning system for high-speed motorized spindles and machine tools.

Feature extraction of induction motor stator fault based on particle swarm optimization and wavelet packet

To effectively extract the interturn short circuit fault features of induction motor from stator current signal, a novel feature extraction method based on the bare-bones particle swarm optimization （BBPSO） algorithm and wavelet packet was proposed. First, according to the maximum inner product between the current signal and the cosine basis functions, this method could precisely estimate the waveform parameters of the fundamental component using the powerful global search capability of the BBPSO, which can eliminate the fundamental component and not affect other harmonic components. Then, the harmonic components of residual current signal were decomposed to a series of frequency bands by wavelet packet to extract the interturn circuit fault features of the induction motor. Finally, the results of simulation and laboratory tests demonstrated the effectiveness of the proposed method.

Particle swarm optimization algorithm for simultaneous optimal placement and sizing of shunt active power conditioner(APC)and shunt capacitor in harmonic distorted distribution system

Due to development of distribution systems and increase in electricity demand,the use of capacitor banks increases.From the other point of view,nonlinear loads generate and inject considerable harmonic currents into power system.Under this condition if capacitor banks are not properly selected and placed in the power system,they could amplify and propagate these harmonics and deteriorate power quality to unacceptable levels.With attention of disadvantages of passive filters,such as occurring resonance,nowadays the usage of this type of harmonic compensator is restricted.On the other side,one of parallel multi-function compensating devices which are recently used in distribution system to mitigate voltage sag and harmonic distortion,performs power factor correction,and improves the overall power quality as active power conditioner(APC).Therefore,the utilization of APC in harmonic distorted system can affect and change the optimal location and size of shunt capacitor bank under harmonic distortion condition.This paper presents an optimization algorithm for improvement of power quality using simultaneous optimal placement and sizing of APC and shunt capacitor banks in radial distribution networks in the presence of voltage and current harmonics.The algorithm is based on particle swarm optimization(PSO).The objective function includes the cost of power losses,energy losses and those of the capacitor banks and APCs.

Gridless Net Routing of Integrate Circuit with Particle Swarm Optimization Algorithm

Particle swarm optimization algorithm is presented for the layout of ＂Integrate Circuit （IC）＂ design. Particle swarm optimization based on swarm intelligence is a new evolutionary computational tool and is successfully applied in function optimization, neural network design, classification, pattern recognition, signal processing and robot technology and so on. A modified algorithm is presented and applied to the layout of IC design. For a given layout plane, first of all, this algorithm generates the corresponding grid group by barriers and nets＇ ports with the thought ofgridless net routing, establishes initialization fuzzy matrix, then utilizes the global optimization character to find out the best layout route only if it exits. The results of model simulation indicate that PSO algorithm is feasible and efficient in IC layout design.

Two-dimensional silicon-carbon hybrids with a honeycomb lattice: New family for two-dimensional photovoltaic materials

We predict a series of new two-dimensional(2D) inorganic materials made of silicon and carbon elements(2D SixC1?x) based on density functional theory. Our calculations on optimized structure, phonon dispersion, and finite temperature molecular dynamics confirm the stability of 2D SixC1?x sheets in a two-dimensional, graphene-like, honeycomb lattice. The electronic band gaps vary from zero to 2.5 e V as the ratio x changes in 2D SixC1?x changes, suggesting a versatile electronic structure in these sheets. Interestingly, among these structures Si0.25C0.75 and Si0.75C0.25 with graphene-like superlattices are semimetals with zero band gap as their ? and ?* bands cross linearly at the Fermi level. Atomic structural searches based on particle-swarm optimization show that the ordered 2D SixC1?x structures are energetically favorable. Optical absorption calculations demonstrate that the 2D silicon-carbon hybrid materials have strong photoabsorption in visible light region, which hold promising potential in photovoltaic applications. Such unique electronic and optical properties in 2D SixC1?x have profound implications in nanoelectronic and photovoltaic device applications.

Phase Transition and Physical Properties of InS

Using the crystal structure prediction method based on particle swarm optimization algorithm, three phases （Pnnm, C2/m and Pm-3m） for InS are predicted. The new phase Pm-3m of InS under high pressure is firstly reported in the work. The structural features and electronic structure under high pressure of InS are fully investigated. We predicted the stable ground-state structure of InS was the Pnnm phase and phase transformation of InS from Pnnm phase to Pm-3m phase is firstly found at the pressure of about 29.5 GPa. According to the calculated enthalpies of InS with four structures in the pressure range from 20 GPa to 45 GPa, we find the C2/m phase is a metastable phase. The calculated band gap value of about 2.08 eV for fnS with Pnnm structure at 0 GPa agrees well with the experimental value. Moreover, the electronic structure suggests that the C2/m and Pm-3m phase are metallic phases.