求解不等式约束优化问题的一个改进算法

本文改进了一个求解不等式约束优化问题的对偶算法,建立了一个相应的算法,进一步证明了该算法的收敛性．最后,给出数值结果以验证该算法的有效性．

一种改进的IGBT模块结温提取算法及实验研究

IGBT模块目前被广泛应用于电力系统、牵引传动和电动汽车等各个领域,其安全可靠运行对电力电子系统具有重要意义。研究表明,器件的结温与其健康状况有密切的关系,如何实时提取IGBT的结温是在线监测亟需解决的重要问题。在研究IGBT关断期间电流变化率di/dt与结温关系的基础上,提出一种改进的结温提取模型和算法,该方法具有模型简单和准确的特点,并给出了详细的理论推导分析和简化计算模型。最后,通过设计的改进双脉冲实验,验证了模型和算法的正确性与实用性。

数据挖掘中的聚类算法

数据挖掘已经被广泛的应用于商业银行，电信行业，心理学，生物医学等各行各业中。由于数据挖掘涉及的学科领域和方法很多，所以就有多种分类方法。这里介绍了聚类方法的要求以及常见的聚类算法。现在还有很多改进的聚类算法，对H—K算法做了主要介绍。

一类具有非线性收获率的捕食者-食饵生态经济系统的分支分析

研究了一类捕食者-食饵生态经济模型的动力学行为.该模型具有非线性收获率,这使得模型更具一般性.选取经济利润v作为分支参数,通过局部参数化方法,Hopf分支理论和形式级数方法研究了系统的Hopf分支.同时,改进的参数化计算过程更简单,能够处理更复杂的模型.最后,通过MATLAB仿真证明了我们的结果.

Improved parallel weighted bit-flipping algorithm

An improved parallel weighted bit-flipping（PWBF） algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes, the bit-flipping step and the check node updating step of the original algorithm are parallelized. The simulation experiments demonstrate that the improved PWBF algorithm provides about 0. 1 to 0. 3 dB coding gain over the original PWBF algorithm. And the improved algorithm achieves a higher convergence rate. The choice of the threshold is also discussed, which is used to determine whether a bit should be flipped during each iteration. The appropriate threshold can ensure that most error bits be flipped, and keep the right ones untouched at the same time. The improvement is particularly effective for decoding quasi-cyclic low-density paritycheck（QC-LDPC） codes.

An Improved Hybrid Genetic Algorithm for Chemical Plant Layout Optimization with Novel Non-overlapping and Toxic Gas Dispersion Constraints

New approaches for facility distribution in chemical plants are proposed including an improved non-overlapping constraint based on projection relationships of facilities and a novel toxic gas dispersion constraint. In consideration of the large number of variables in the plant layout model, our new method can significantly reduce the number of variables with their own projection relationships. Also, as toxic gas dispersion is a usual incident in a chemical plant, a simple approach to describe the gas leakage is proposed, which can clearly represent the constraints of potential emission source and sitting facilities. For solving the plant layout model, an improved genetic algorithm (GA) based on infeasible solution fix technique is proposed, which improves the globe search ability of GA. The case study and experiment show that a better layout plan can be obtained with our method, and the safety factors such as gas dispersion and minimum distances can be well handled in the solution.

PLC-Oriented Access Point Location Planning Algorithm in Smart-Grid Communication Networks

In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of power-distribution communication networks, connecting users to control centers. Hence, they are vital for the reliable, safe, and economical operation of a power system. This paper proposes a planning method for AP allocation that takes into consideration economics, reliability, network delay, and （n-l） resilience. First, an optimization model for the AP location is established, which minimizes the cost of installing APs, while satisfying the reliability, network delay, and （n-1） resilience constraints. Then, an improved genetic algorithm is proposed to solve the optimization problem. The simulation results indicate that the proposed planning method can deal with diverse network conditions satisfactorily. Furthermore, it can be applied effectively with high flexibility and scalability.

Design and control of integrated pneumatic dexterous robot finger

Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless magnetic rotary encoders.Mechanical parts and FPAs are integrated,which reduces the overall size of the finger.Driven by FPA directly,the joint output torque is more accurate and the friction and vibration can be effectively reduced.An improved adaptive genetic algorithm(IAGA) was adopted to solve the inverse kinematics problem of the redundant finger.The statics of the finger was analyzed and the relation between fingertip force and joint torque was built.Finally,the finger force/position control principle was introduced.Tracking experiments of fingertip force/position were carried out.The experimental results show that the fingertip position tracking error is within ±1 mm and the fingertip force tracking error is within ±0.4 N.It is also concluded from the theoretical and experimental results that the finger can be controlled and it has a good application prospect.

Improved hyper-spherical search algorithm for voltage total harmonic distortion minimization in 27-level inverter

Multi-level inverters(MLIs)have become popular in different applications such as industrial power control systems and distributed generations.There are different forms of MLIs.The cascaded MLIs(CMLIs)have some special advantages among them such as more different output voltage levels using the same number of components and higher power quality.In this paper,a 27-level inverter switching algorithm considering total harmonic distortion(THD)minimization is investigated.Switching angles of the inverter switches are achieved by minimizing a THD-based objective function.In order to minimize the THD-based objective function,the hyper-spherical search(HSS)algorithm,as a novel optimization algorithm,is improved and the results of improved HSS(IHSS)are compared with HSS algorithm and other five evolutionary algorithms to show the advantages of IHSS algorithm.

Study on Control Performance of Bearing Temperature based on Genetic Algorithm

In order to improve the control effect of the bearing, this article studies the temperature control technology to improve the genetic algorithm, at the same time, analyze temperature simulation of bearing based on fuzzy PID control technology and improved genetic algorithm, the simulation results show that, the control method has good robustness based on Improved Genetic Algorithm. It can monitor a plurality of beating temperature, provides a new method for the detection and prevention of bearing fault.

A New Searching Strategy for the Lost Plane Based on RBF Neural Network Model and Global Optimization Model

In this paper, we construct two models for the searching task for a lost plane. Model 1 determines the searching area. We predict the trajectory of floats generated after the disintegration of the plane by using RBF neural network model, and then determine the searching area according to the trajectory. With the pass of time, the searching area will also be constantly moving along the trajectory. Model 2 develops a maritime search plan to achieve the purpose of completing the search in the shortest time. We optimize the searching time and transform the problem into the 0-1 knapsack problem. Solving this problem by improved genetic algorithm, we can get the shortest searching time and the best choice for the search power.

Design of a Dedicated Reconfigurable Multiplier in an FPGA

We design a reconfigurable pipelined multiplier embedded in an FPGA. This design is based on the modified Booth algorithm and performs 18 × 18 signed or 17 × 17 unsigned multiplication. We propose a novel method for circuit optimization to reduce the number of partial products. A new layout floorplan design of the multiplier block is reported to comply with the constraints imposed by the tile-based FPGA chip design. The multiplier can be configured as synchronous or asynchronous. Its operation can also be configured as pipelined for high-frequency operation. This design can be easily extended for different input and output bit-widths. We employ a novel carry look-ahead adder circuit to generate the final product. The transmission-gate logic is used for the low-level circuits throughout the entire multiplier for fast logic operations. The design of the multiplier block is based on SMIC 0.13μm CMOS technology using full-custom design methodology. The operation of the 18 × 18 multiplier takes 4. lns. The two-stage pipelined operation cycle is 2.5ns. This is 29.1% faster than the commercial multiplier and is 17.5% faster than the multipliers reported in other academic designs. Compared with the distributed LUT-based multiplier,it demonstrates an area efficiency ratio of 33 ： 1.

Parameters inversion of high central core rockfill dams based on a novel genetic algorithm

Parameters identification of rockfill materials is a crucial issue for high rockfill dams. Because of the scale effect, random sampling and sample disturbance, it is difficult to obtain the actual mechanical properties of rockfill from laboratory tests. Parameters inversion based on in situ monitoring data has been proven to be an efficient method for identifying the exact parameters of the rockfill. In this paper, we propose a modified genetic algorithm to solve the high-dimension multimodal and nonlinear optimal parameters inversion problem. A novel crossover operator based on the sum of differences in gene fragments(So DX) is proposed, inspired by the cloning of superior genes in genetic engineering. The crossover points are selected according to the difference in the gene fragments, defining the adaptive length. The crossover operator increases the speed and accuracy of algorithm convergence by reducing the inbreeding and enhancing the global search capability of the genetic algorithm. This algorithm is compared with two existing crossover operators. The modified genetic algorithm is then used in combination with radial basis function neural networks(RBFNN) to perform the parameters back analysis of a high central earth core rockfill dam. The settlements simulated using the identified parameters show good agreement with the monitoring data, illustrating that the back analysis is reasonable and accurate. The proposed genetic algorithm has considerable superiority for nonlinear multimodal parameter identification problems.

Multi-objective hydraulic optimization and analysis in a minipump

Minipump is widely used in microfluidics system, active cooling system, etc. But building a high efficiency minipump is still a challenging problem. In this paper, a systematic method was developed to design, characterize and optimize a particular mechanical minipump. The optimization work was conducted to cope with the conflict between pressure head and hydraulic efficiency by an improved back-propagation neural network （BPNN） with the non-dominated sorting genetic algorithm-II （NSGA-II）. The improved BPNN was utilized to predicate hydraulic performance and, moreover, was modified to improve the prediction accuracy. The NSGA-II was processed for minipump multi-objective optimization which is dominated by four impeller dimensions. During hydraulic optimization, the processing feasibility was also taken into consideration. Experiments were conducted to validate the above optimization methods. It was proved that the optimized minipump was improved by about 24 % in pressure head and 4.75 % in hydraulic efficiency compared to the original designed prototype. Meanwhile, the sensitivity test was used to analyze the influence of the four impeller dimensions. It was found that the blade outlet angle β2 and the impeller inlet diameter Do significantly influence the pressure head H and the hydraulic efficiency η, respec- tively. Detailed internal flow fields showed that the optimum model can relieve the impeller wake and improve both the pressure distribution and flow orientation.