检索结果-内蒙古大学图书馆

7th International Symposium on Computational Intelligence and Design (ISCID)

作者： Chen, Shaowei Wu, Minhua Zhao, Shuai Northwestern Polytech Univ Xian Peoples R China

ISBN: (纸本)9781479970056

Extreme Learning Machine has the quality of fast learning speed, good generalization performance, and high diagnostic accuracy. For analog circuit fault diagnosis and health management (PHM) applications, this paper presents the method of online sequential learning machine with differential evolution algorithm to optimize Extreme Learning Machine and improve the diagnostic accuracy and generalization performance effectively.

关键词： online sequential learning machine differential evolution algorithm analog circuits

来源：评论

学校读者我要写书评

暂无评论

Optimization of Advertising Budget Allocation Over Time Based on LS-SVMR and DE

引用

IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2014年第4期11卷 1076-1082页

作者： Niu, Dapeng Sun, Ying Wang, Fuli Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China China Minsheng Bank Suzhou Branch Suzhou 100738 Peoples R China

The advertising budget allocation problem for financial service is dealt with based on statistical learning and evolutionary computation in this paper. Taking the carry-over effects of the advertising into account, the least squares support vector machine regression (LS-SVMR) is used to construct the response model. A comparison between the proposed response model and traditional regression method based market response models is implemented. The results show the effectiveness and validity of the former model. Taking the budgets allocated to every month in the planning horizon as decision variables, the budget allocation optimization model is built and an improved differential evolution algorithm is used to find the optimal solutions. Finally, the proposed budget allocation method is illustrated by a practical problem.

关键词： Advertising budget allocation differential evolution algorithm least squares support vector machine regression (LS-SVMR) optimization

来源：评论

学校读者我要写书评

暂无评论

Application of differential evolution Optimization based Gaussian Mixture Models to Speaker Recognition

Application of Differential Evolution Optimization based Gau...

引用

26th Chinese Control and Decision Conference (CCDC)

作者： Zhou Hong Zhang JianHua E China Univ Sci & Technol Sch Informat Sci & Engn Shanghai 200237 Peoples R China

ISBN: (纸本)9781479937066

Voice-based speaker recognition technique can be used in the identification of speakers. In such manner, Gaussian Mixture Model (GMM) can provide voice feature vectors probability density model. In this paper, the Akaike's Information Criterion (AIC) is used to identify structures of the GM M models. The GM M parameter optimization is done by the differential evolution (DE) algorithm. During the optimization, a new parametric method is applied aiming at ensuring the positive definite symmetry property of an arbitrary covariance matrix. Here, both the expectation-maximization (FM) and DE are applied to identify the GM M parameters of a simulated dataset, and the utility of DE is proved by comparing the performances of the two. Farther, DE is used to identify parameters of the GMM of Speaker Dataset acquired by Information Processing Laboratory in Hokkaido University. Again, the good performances of DE demonstrate superiorities to the EM method.

关键词： Speaker Recognition Gaussian Mixture Models AIC differential evolution algorithm Covariance Matrix Parametric

来源：评论

学校读者我要写书评

暂无评论

RETRACTED: Optimization of fluidized bed spray granulation process based on a multiphase hybrid model (Retracted article. See vol. 143, pg. 152, 2015)

引用

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2014年 131卷 7-15页

作者： Niu, Dapeng Li, Ming Wang, Fuli Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China De Montfort Univ Sch Pharm Leicester LE1 9BH Leics England

An optimization strategy is presented to improve the granule quality of fluidized bed spray granulation in this paper. An accurate description of the relationship between the granule quality and the manipulated variables is first established as a prerequisite for optimization. Considering the characteristics of the fluidized bed spray granulation process and its multiphase features, a multiphase hybrid model is built with the population balance equations as the basic model, in combination with the use of black box models to obtain the unknown parameters. RBF neural network is adopted as the black modeling method in this work to describe the relationship between the parameters and the manipulated variables. Batch experiments of fluidized bed spray granulation are then used for hybrid model validation. The results show that the model has high accuracy and good generalization ability, and it can effectively reflect the characteristics of each phase of the granulation process. Based on the established multiphase hybrid model, an optimization problem and its corresponding online optimization strategy are proposed for fluidized bed spray granulation process. An improved differential evolution algorithm is used to solve the problem for online optimization and adjustment of the granulation process. Experimental results illustrate that both the hybrid model and the improved DE algorithm are effective when used in optimization of batch fluidized bed spray granulation process. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Fluidized bed spray granulation Optimization Population balance equation RBF neural network differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of a Derivative-Free Method with Projection Skill to Solve an Optimization Problem

引用

Atmospheric and Oceanic Science Letters 2014年第6期7卷 499-504页

作者： PENG Fei SUN Guo-Dong State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) Institute of Atmospheric PhysicsChinese Academy of Sciences University of Chinese Academy of Sciences

Improving numerical forecasting skill in the atmospheric and oceanic sciences by solving optimization problems is an important issue. One such method is to compute the conditional nonlinear optimal perturbation(CNOP), which has been applied widely in predictability studies. In this study, the differential evolution(DE) algorithm, which is a derivative-free algorithm and has been applied to obtain CNOPs for exploring the uncertainty of terrestrial ecosystem processes, was employed to obtain the CNOPs for finite-dimensional optimization problems with ball constraint conditions using Burgers' equation. The aim was first to test if the CNOP calculated by the DE algorithm is similar to that computed by traditional optimization algorithms, such as the Spectral Projected Gradient(SPG2) algorithm. The second motive was to supply a possible route through which the CNOP approach can be applied in predictability studies in the atmospheric and oceanic sciences without obtaining a model adjoint system, or for optimization problems with non-differentiable cost functions. A projection skill was first explanted to the DE algorithm to calculate the CNOPs. To validate the algorithm, the SPG2 algorithm was also applied to obtain the CNOPs for the same optimization problems. The results showed that the CNOPs obtained by the DE algorithm were nearly the same as those obtained by the SPG2 algorithm in terms of their spatial distributions and nonlinear evolutions. The implication is that the DE algorithm could be employed to calculate the optimal values of optimization problems, especially for non-differentiable and nonlinear optimization problems associated with the atmospheric and oceanic sciences.

关键词： differential evolution algorithm spectral projected gradient algorithm CNOP Burgers＇ equation optimization problem

来源：评论

学校读者我要写书评

暂无评论

Targeted Pressure Management during CO₂ Sequestration: Optimization of Well Placement and Brine Extraction 12

Targeted Pressure Management during CO<sub>2</sub> Sequestra...

引用

12th International Conference on Greenhouse Gas Control Technologies (GHGT)

作者： Cihan, Abdullah Birkholzer, Jens Bianchi, Marco Univ Calif Berkeley Lawrence Berkeley Natl Lab Div Earth Sci Berkeley CA 94720 USA

Large-scale pressure increases resulting from carbon dioxide (CO2) injection in the subsurface can potentially impact caprock integrity, induce reactivation of critically stressed faults, and drive CO2 or brine through conductive features into shallow groundwater. Pressure management involving the extraction of native fluids from storage formations can be used to minimize pressure increases while maximizing CO2 storage. However, brine extraction requires pumping, transportation, possibly treatment, and disposal of substantial volumes of extracted brackish or saline water, all of which can be technically challenging and expensive. This paper describes a constrained differential evolution (CDE) algorithm for optimal well placement and injection/extraction control with the goal of minimizing brine extraction while achieving predefined pressure contraints. The CDE methodology was tested for a simple optimization problem whose solution can be partially obtained with a gradient-based optimization methodology. The CDE successfully estimated the true global optimum for both extraction well location and extraction rate, needed for the test problem. A more complex example application of the developed strategy was also presented for a hypothetical CO2 storage scenario in a heterogeneous reservoir consisting of a critically stressed fault nearby an injection zone. Through the CDE optimization algorithm coupled to a numerical vertically-averaged reservoir model, we successfully estimated optimal rates and locations for CO2 injection and brine extraction wells while simultaneously satisfying multiple pressure buildup constraints to avoid fault activation and caprock fracturing. The study shows that the CDE methodology is a very promising tool to solve also other optimization problems related to GCS, such as reducing 'Area of Review', monitoring design, reducing risk of leakage and increasing storage capacity and trapping. Published by Elsevier Ltd.

关键词： carbon sequestration pressure management brine extraction optimization differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

FPGA Implementation of differential Evaluation algorithm for MLP Training

FPGA Implementation of Differential Evaluation Algorithm for...

引用

IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Yilmaz, Ali Riza Erkmen, Burcu Yavuz, Oguzhan Yildiz Tech Univ Dept Elect & Com Engn Istanbul Turkey Telekomunikasyon AS R&D Dept Netas Istanbul Turkey

ISBN: (纸本)9781479930203

In this work, differential evolution algorithm (DEA) is implemented on an embedded systems based on FPGA for the training of multi-layer perceptron (MLP). The classification performance of the MLP trained by DEA on FPGA has been analyzed by using a non-linear database. The MLP performance on FPGA has been compared with that on MATLAB in terms of computational performance and test accuracy. It is proved that DEA is suitable for realizing on FPGA considering simplicity of the algorithm. Simulation results of each component for DEA on FPGA are demonstrated in this paper.

关键词： differential evolution algorithm MLP Training FPGA

来源：评论

学校读者我要写书评

暂无评论

Proper selection of different parameters of DE algorithm to study the dynamic performance of AGC in a two area hydrothermal system

Proper selection of different parameters of DE algorithm to ...

引用

International Conference on Advances in Electrical Engineering (ICAEE)

作者： Mishra, Nandan Jena, Swapnil Kumar Behera, Plaban Kumar Sahu, Binod Kumar Siksha O Anusandhan Univ Dept Elect Engn Bhubaneswar Odisha India

ISBN: (纸本)9781479935420

In this paper a novel attempt is made to select the proper strategy and the control parameters of differential evolution (DE) algorithm to design the gains of proportional-integral-derivative (PID) controllers for automatic generation control (AGC) of an interconnected two equal area hydrothermal system. The hydro area is equipped with a mechanical governor and the thermal area with a reheat turbine. The best strategy and proper values of control parameters of DE algorithm are determined by applying 1% SLP to thermal area. The PID controller gains are tuned using DE algorithm with the best strategy and control parameters. Finally the dynamic response of the proposed two area system is studied with optimum controller gains.

关键词： Automatic Generation Control differential evolution algorithm Generation Rate Constraints Proportional-Integral-Derivative Controller

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Control Allocation Using Hybrid Optimization algorithm

Nonlinear Control Allocation Using Hybrid Optimization Algor...

引用

International Conference on Mechatronics and Control (ICMC)

作者： Guo, Mengxu Chen, Mou Zhang, Hangyue Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781479925384

A nonlinear control allocation scheme is developed using hybrid optimization algorithm. To achieve nonlinear control allocation results, a hybrid optimization algorithm is presented in which the ant colony algorithm and differential evolution algorithm are employed. The nonlinear control allocation problem is divided into two optimal problems which are selecting optimal truncation point combination problem and optimizing the corresponding section coefficients problem. Under this case, the actuators constraints are segmented into some intervals according to the rate limits and position boundary of actuators. The optimal combination of cutoff interval is given through ant colony algorithm searching, and the optimal combination of truncation points is obtained. On the basis of the optimal truncation points, the corresponding truncation point coefficients are optimized by using the differential evolution algorithm. Then, the actuator commands are obtained by the calculation results of truncation points and corresponding truncation point coefficients. Simulation results show that the developed control allocation method is effective and the control requirement can be achieved.

关键词： nonlinear control allocation ant colony algorithm differential evolution algorithm hybrid optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

Driving Cycle-Based Design Optimization of Interior Permanent Magnet Synchronous Motor Drives for Electric Vehicle Application

Driving Cycle-Based Design Optimization of Interior Permanen...

引用

IEEE International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM)

作者： Guenther, Stephan Ulbrich, Stefan Hofmann, Wilfried Tech Univ Dresden Elektrotechn Inst D-01062 Dresden Germany

ISBN: (纸本)9781479947492

The paper discusses the influence of driving cycles on the design optimization of permanent magnet synchronous machines. A bi-objective design optimization is presented for synchronous machines with V-shaped buried magnets. The machine length and the loss energy over a given driving cycle are defined as objectives. A total of 14 parameters defining geometry and winding layout are chosen as design parameters. Additionally some constraints like speed-torque-requirements and minimal stray field bridge widths are set. The optimization problem is solved using 2D finite element analysis and a high-performance differential evolution algorithm. The analyses are performed for the ARTEMIS driving cycle due to the more realistic driving behavior in comparison to the most commonly used New European Driving Cycle. Furthermore, a reference design optimization against the rated point loss energy is presented. The results show a much better performance of the driving cycle optimized machines in comparison to the rated point optimized machines in terms of the cycle-based loss energy. Loss savings depend strongly on the machine length and are approximately in between 15 % and 45 %.

关键词： Interior Permanent Magnet Synchronous Machine Driving Cycle Efficiency Loss Minimization ARTEMIS Electric Vehicle Bi-Objective Optimization differential evolution algorithm Finite Element Analysis

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：