检索结果-内蒙古大学图书馆

Optimization of injection molding process parameters to improve the mechanical performance of polymer product against impact

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2015年第9-12期76卷 2199-2208页

作者： Xu, Yingjie Zhang, QingWen Zhang, Weihong Zhang, Pan Northwestern Polytech Univ ESAC Xian 710072 Shaanxi Peoples R China

Injection molding is the most widely used process in manufacturing polymer products. The warpage induced during injection molding process has an important influence on the mechanical performance of injection molded products. Therefore, how to optimize process parameters becomes the key issue in improving the mechanical performance of the product towards the expected service conditions. In this paper, a combined artificial neural network and particle swarm optimization (pso) algorithm method is proposed to optimize the injection molding process. An integrated finite element analysis of the injection molding process, the warpage-induced residual stresses during assembly, and mechanical performance of serviced product is firstly proposed. A back propagation neural network model is then developed to map the complex nonlinear relationship between process parameters and mechanical performance of the product. The pso algorithm is interfaced with this predictive model to optimize process parameters and thereby significantly improve the mechanical performance. A case study of vehicle window made of polycarbonate (PC) is presented. Optimum values of process parameters are determined to minimize the maximum von Mises stress within the PC vehicle window under impact loading.

关键词： Injection molding Warpage Impact BP neural network pso algorithm

来源：评论

学校读者我要写书评

暂无评论

Particle Swarm Optimization based Sequential and Parallel Tasks Scheduling Model for Heterogeneous Multiprocessor Systems

引用

FUNDAMENTA INFORMATICAE 2015年第1期139卷 43-65页

作者： Kumar, Paulraj Ranjith Babu, P. Palani, Sankaran PSR Engn Coll Sivakasi 626140 Tamil Nadu India KS Rangasamy Coll Technol Tiruchengode Tamil Nadu India Suharsan Engn Coll Pudukkottai Tamil Nadu India

Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given task should be executed. In multiprocessor systems, an efficient scheduling of sequential and parallel tasks onto the processors is known to be NP-Hard problem. In this paper, the problem of minimizing schedule length with energy consumption constraint and the problem of minimizing energy consumption with schedule length constraint on homogeneous and heterogeneous multiprocessor computers through independent sequential and parallel tasks are proposed. These problems emphasize the tradeoff between power and performance and are defined such that the power-performance product is optimized by fixing one factor and minimizing the other and vice versa. The performance of the proposed algorithm with optimal solution is validated using Particle Swarm Optimization (pso) The pso algorithm achieves 47.5% and 32% of power savings for scheduling sequential and parallel tasks to the processors respectively and also 45.5% of energy saving are achieved for scheduling both sequential or parallel tasks to the processors.

关键词： Multiprocessor Embedded Systems Energy and Power Optimization pso algorithm

来源：评论

学校读者我要写书评

暂无评论

Tuning of Fractional Order PID Controller Using Particle Swarm Optimization Technique for DC Motor Speed Control

Tuning of Fractional Order PID Controller Using Particle Swa...

引用

International Conference on Power Electronics, Intelligent Control and Energy Systems

作者： Ruchi V. Jain M.V. Aware A.S. Junghare Department of Electrical Engineering VNIT Nagpur India

ISBN: (纸本)9781467385886

Design of Fractional Order PID controller (FOPID) for speed regulation of DC motor is presented in this paper. In comparison with conventional PID, FOPID is more flexible and trustworthy to control higher order systems. The FOPID exhibits the Iso-damping property to enhance the robustness of closed loop response of the system against gain variations. According to parameters adjustment problems of FOPID controller, particle swarm optimization (pso) algorithm is adopted to optimize FOPID controller parameters. Peak overshoot, rise time and settling time are considered as important factors to minimize using pso technique. Simulation results give validation of the proposed work and provide effectiveness of FOPID controller in terms of robustness and control effect as compared to PID controller.

关键词： DC Motor PID FOPID pso algorithm Iso-damping

来源：评论

学校读者我要写书评

暂无评论

Combine particle swarm optimization algorithm and canonical sign digit to design finite impulse response filter

引用

SOFT COMPUTING 2015年第2期19卷 407-419页

作者： Soleimani, Ali Shahrood Univ Technol Dept Elect & Robot Engn Shahrood Iran

The main contribution of this paper is to design a digital finite impulse response filter using the particle swarm optimization (pso) algorithm combined canonical signed digit (CSD) representation. The design has been done based on matching certain frequency response and the filter coefficients in CSD representation with limited bits and some of coefficients to be zero, simultaneously. Using CSD representation, multipliers can substitute adders, shifters and subtractors. In filter design, the results show that combining pso and CSD representations simultaneously is better than combining pso and CSD sequentially. In addition the results, if the common adders and subtractors were computed for all filter coefficients that specified in CSD representation, significantly reduce the complexity of the hardware implementation of digital FIR filter.

关键词： pso algorithm FIR filter Canonical sign digit Reduce computation Genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

7 Particle Swarm Optimization Based Power Allocation Schemes of Device-to-Device Multicast Communication

引用

WIRELESS PERSONAL COMMUNICATIONS 2015年第3期85卷 1261-1277页

作者： Gong, Wenrong Wang, Xiaoxiang Beijing Univ Posts & Telecommun Minist Educ Key Lab Universal Wireless Commun Beijing 100876 Peoples R China

Device-to-device (D2D) multicast communication is a useful way to improve the communication efficiency of local services. In this paper, we study the power control of D2D multicast communication underlying cellular network. To improve the overall throughput of D2D and cellular communication, particle swarm optimization (pso) algorithm based power allocation schemes are proposed under two scenarios. Firstly, we introduce a distributed controlled D2D multicast group formation procedure. And then, the system model of both D2D communication reuse the same frequency with one cellular user equipment (CUE) and with multi-CUEs is introduced. Under these two scenarios, the power allocation problems are transformed to constrained optimization problems. pso algorithm is applied to get the solutions for optimization problems. Additionally, to get a compromise between fairness and the overall throughput of system, a new objective function with fairness factor is designed in the second scenario. Simulation results show that the proposed schemes significantly improve the throughput performance of system and guarantee the quality of both D2D and cellular communication.

关键词： D2D communication Multicast pso algorithm Power allocation

来源：评论

学校读者我要写书评

暂无评论

SVM Model for Influencing Factors of Financing

SVM Model for Influencing Factors of Financing

引用

2016 International Congress on Computation algorithms in Engineering

作者： Rui Zheng Ningjing Zhang School of Economics and Management Xi'an Shiyou University

In the trend of diversified economic development, how to entirely and systematically build a quantitative model for influencing factors of financing is a hot topic and difficult problem in the research of financial field. Based on SVM algorithm, this paper analyzes the influencing factors of China's small-and-medium-sized corporate financing, and establishes a financing weight regression model, in order to avoid decoupling, fuzzy evaluation and other issues. The accuracy of SVM model depends on the model parameters. The bionic algorithm and pso algorithm are introduced, and the norm of two adjacent prediction matrix differences is served as a fitness function, in order to solve the problems of affecting the prediction results due to numerical instabilities in the model prediction process. And this paper establishes a model with an ideal effect of the robustness and accuracy through introducing pso-SVM algorithm and based on MATLAB platform.

关键词： financing factors SVM pso algorithm regression

来源：评论

学校读者我要写书评

暂无评论

Comparative Study on Several pso algorithms

Comparative Study on Several PSO Algorithms

引用

26th Chinese Control and Decision Conference (CCDC)

作者： Jiang, Weichang Zhang, Yating Wang, Ruihua Beijing Univ Technol Elect Informat & Control Engn Coll Beijing 100124 Peoples R China

ISBN: (纸本)9781479937066

With the development of intelligent algorithm, GA and pso have become the hot spot for the study on multi-objective optimization in recently years. Information sharing is the core of pso algorithm, Comparing with GA, pso algorithm has less variables to adjust and is easy to achieve, so it is widely used in engineering. This paper focus on the comparation on several pso algorithm and introduce a kind of pso algorithm that is better in performance than others

关键词： pso algorithm Intelligent algorithm Selpso

来源：评论

学校读者我要写书评

暂无评论

Design and Analysis of a Novel Fully Decoupled Tri-axis Linear Vibratory Gyroscope with Matched Modes

引用

SENSORS 2015年第7期15卷 16929-16955页

作者： Xia, Dunzhu Kong, Lun Gao, Haiyu Southeast Univ Sch Instrument Sci & Engn Key Lab Micro Inertial Instruments & Adv Nav Tech Minist Educ Nanjing 210096 Jiangsu Peoples R China

We present in this paper a novel fully decoupled silicon micromachined tri-axis linear vibratory gyroscope. The proposed gyroscope structure is highly symmetrical and can be limited to an area of about 8.5 mm x 8.5 mm. It can differentially detect three axes' angular velocities at the same time. By elaborately arranging different beams, anchors and sensing frames, the drive and sense modes are fully decoupled from each other. Moreover, the quadrature error correction and frequency tuning functions are taken into consideration in the structure design for all the sense modes. Since there exists an unwanted in-plane rotational mode, theoretical analysis is implemented to eliminate it. To accelerate the mode matching process, the particle swam optimization (pso) algorithm is adopted and a frequency split of 149 Hz is first achieved by this method. Then, after two steps of manual adjustment of the springs' dimensions, the frequency gap is further decreased to 3 Hz. With the help of the finite element method (FEM) software ANSYS, the natural frequencies of drive, yaw, and pitch/roll modes are found to be 14,017 Hz, 14,018 Hz and 14,020 Hz, respectively. The cross-axis effect and scale factor of each mode are also simulated. All the simulation results are in good accordance with the theoretical analysis, which means the design is effective and worthy of further investigation on the integration of tri-axis accelerometers on the same single chip to form an inertial measurement unit.

关键词： tri-axis gyroscope gyroscope structure pso algorithm mode matching

来源：评论

学校读者我要写书评

暂无评论

An efficient meta-heuristic algorithm for grid computing

引用

JOURNAL OF COMBINATORIAL OPTIMIZATION 2015年第3期30卷 413-434页

作者： Pooranian, Zahra Shojafar, Mohammad Abawajy, Jemal H. Abraham, Ajith Dezful Islamic Azad Univ Grad Sch Dezful Iran Univ Roma La Sapienza Dept Informat Engn Elect & Telecommun DIET I-00184 Rome Italy Deakin Univ Sch Informat Technol Waurn Ponds Vic Australia Sci Network Innovat & Res Excellence Machine Intelligence Res Labs MIR Labs Auburn WA 98071 USA

A grid computing system consists of a group of programs and resources that are spread across machines in the grid. A grid system has a dynamic environment and decentralized distributed resources, so it is important to provide efficient scheduling for applications. Task scheduling is an NP-hard problem and deterministic algorithms are inadequate and heuristic algorithms such as particle swarm optimization (pso) are needed to solve the problem. pso is a simple parallel algorithm that can be applied in different ways to resolve optimization problems. pso searches the problem space globally and needs to be combined with other methods to search locally as well. In this paper, we propose a hybrid-scheduling algorithm to solve the independent task-scheduling problem in grid computing. We have combined pso with the gravitational emulation local search (GELS) algorithm to form a new method, pso-GELS. Our experimental results demonstrate the effectiveness of pso-GELS compared to other algorithms.

关键词： Grid computing pso algorithm GELS Scheduling Independent tasks

来源：评论

学校读者我要写书评

暂无评论

Theoretical and empirical coupled modeling on the surface roughness in diamond turning

引用

MATERIALS & DESIGN 2015年 82卷 216-222页

作者： He, C. L. Zong, W. J. Cao, Z. M. Sun, T. Harbin Inst Technol Ctr Precis Engn Harbin 150001 Peoples R China

In this work, a theoretical and empirical coupled method is proposed to predict the surface roughness achieved by single point diamond turning, in which the surface roughness is considered to be composed of the certain and uncertain parts. The certain components are directly formulated in theory, such as the effects of the kinematics and minimum undeformed chip thickness. The uncertain components in relation to the material spring back, plastic side flow, micro defects on the cutting edge of diamond tool, and others, are empirically predicted by a RBF (radial basis function) neural network, which is established by referring to the experimental data. Finally, the particle swarm optimization algorithm is employed to find the optimal cutting parameters for the best surface roughness. The validation experiments show that the optimization is satisfied, and the prediction accuracy is high enough, i.e. that the prediction error is only 0.59-10.11%, which indicates that the novel surface roughness prediction method proposed in this work is effective. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Diamond turning Surface roughness Minimum undeformed chip thickness RBF neural network pso algorithm

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：