检索结果-内蒙古大学图书馆

Parallel-differential evolution approach for optimal event-driven load shedding against voltage collapse in power systems

引用

IET GENERATION TRANSMISSION & DISTRIBUTION 2014年第4期8卷 651-660页

作者： Xu, Yan Dong, Zhao Yang Luo, Fengji Zhang, Rui Wong, Kit Po Univ Newcastle Ctr Intelligent Elect Networks Newcastle NSW 2300 Australia Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia Univ Western Australia Sch Elect Elect & Comp Engn Perth WA 6009 Australia

Event-driven load shedding is an effective countermeasure against voltage collapse in power systems. Conventionally, its optimisation relies on sensitivity-based linear methods, which, however, could suffer from unrealistic assumptions and sub-optimality. In this study, an alternative approach based on parallel-differential evolution (P-DE) is proposed for efficiently and globally optimising the event-driven load shedding against voltage collapse. Working in a parallel structure, the approach consists of candidate buses selection, voltage stability assessment (VSA) and DE optimisation. Compared with conventional methods, it fully considers the non-linearity of the problem and is able to effectively escape from local optima and not limited to system modelling and unrealistic assumptions. Besides, any type of objective functions and VSA techniques can be used. The proposed approach has been tested on the IEEE 118-bus test system considering two cases for preventive control and corrective control, respectively, and compared with the two existing methods. Simulation results have verified its effectiveness and superiority over the compared methods.

关键词： evolutionary computation load shedding optimisation power system dynamic stability voltage control parallel-differential evolution approach optimal event-driven load shedding voltage collapse power systems sensitivity-based linear methods P-DE event-driven load shedding parallel structure candidate buses selection voltage stability assessment VSA DE optimisation objective functions VSA techniques IEEE 118-bus test system preventive control corrective control

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of multi-objective and multi-algorithm approaches for the optimal design of distribution transformers

引用

JOURNAL OF ENGINEERING RESEARCH 2014年第4期2卷 33-45页

作者： Ubeku, E. U. Odiase, F. Univ Benin Dept Elect & Elect Engn Benin Nigeria

This paper presents the sizing of three phase transformer using four intelligent algorithms namely geometric programming, genetic algorithm, simulated annealing, and particle swam optimization. Four independent objective functions and eight constraints were used. The comparative analysis carried out on the results obtained from these intelligent algorithms shows that all the outputs from the intelligent algorithms are the same. The fastness of results shows that geometric programming is the fastest, while genetic algorithm, simulated annealing, and particle swam optimization followed in that order. The output results from the cost objective function were compared with the results obtained by Masood (2012) and it showed that money was saved in the following order, 6.4%, 16.32%, 10.63% and 16.79% respectively for geometric programming, genetic algorithm, simulated annealing, and particle swam optimization.

关键词： Constraints minimisation objective functions particle swam optimization simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Effective Multi-Modal Retrieval based on Stacked Auto-Encoders

引用

PROCEEDINGS OF THE VLDB ENDOWMENT 2014年第8期7卷 649-660页

作者： Wang, Wei Ooi, Beng Chin Yang, Xiaoyan Zhang, Dongxiang Zhuang, Yueting Natl Univ Singapore Sch Comp Singapore Singapore Illinois Singapore Pte Adv Digital Sci Ctr Singapore Singapore Zhejiang Univ Coll Comp Sci Hangzhou Zhejiang Peoples R China

Multi-modal retrieval is emerging as a new search paradigm that enables seamless information retrieval from various types of media. For example, users can simply snap a movie poster to search relevant reviews and trailers. To solve the problem, a set of mapping functions are learned to project high-dimensional features extracted from data of different media types into a common lowdimensional space so that metric distance measures can be applied. In this paper, we propose an effective mapping mechanism based on deep learning (i.e., stacked auto-encoders) for multi-modal retrieval. Mapping functions are learned by optimizing a new objective function, which captures both intra-modal and inter-modal semantic relationships of data from heterogeneous sources effectively. Compared with previous works which require a substantial amount of prior knowledge such as similarity matrices of intra-modal data and ranking examples, our method requires little prior knowledge. Given a large training dataset, we split it into mini-batches and continually adjust the mapping functions for each batch of input. Hence, our method is memory efficient with respect to the data volume. Experiments on three real datasets illustrate that our proposed method achieves significant improvement in search accuracy over the state-of-the-art methods.

关键词： Signal encoding Deep learning Mapping Semantics Heterogeneous sources High dimensional feature Low dimensional spaces Mapping functions Mapping mechanism Metric distances objective functions State of the art methods

来源：评论

学校读者我要写书评

暂无评论

Making models match measurements: Model optimization for morphogen patterning networks

引用

SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY 2014年第0期35卷 109-123页

作者： Hengenius, J. B. Gribskov, M. Rundell, A. E. Umulis, D. M. Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47907 USA Purdue Univ Dept Agr & Biol Engn W Lafayette IN 47907 USA Purdue Univ Dept Biol Sci W Lafayette IN 47907 USA

Mathematical modeling of developmental signaling networks has played an increasingly important role in the identification of regulatory mechanisms by providing a sandbox for hypothesis testing and experiment design. Whether these models consist of an equation with a few parameters or dozens of equations with hundreds of parameters, a prerequisite to model-based discovery is to bring simulated behavior into agreement with observed data via parameter estimation. These parameters provide insight into the system (e.g., enzymatic rate constants describe enzyme properties). Depending on the nature of the model fit desired - from qualitative (relative spatial positions of phosphorylation) to quantitative (exact agreement of spatial position and concentration of gene products) - different measures of data-model mismatch are used to estimate different parameter values, which contain different levels of usable information and/or uncertainty. To facilitate the adoption of modeling as a tool for discovery alongside other tools such as genetics, immunostaining, and biochemistry, careful consideration needs to be given to how well a model fits the available data, what the optimized parameter values mean in a biological context, and how the uncertainty in model parameters and predictions plays into experiment design. The core discussion herein pertains to the quantification of model-to-data agreement, which constitutes the first measure of a model's performance and future utility to the problem at hand. Integration of this experimental data and the appropriate choice of objective measures of data-model agreement will continue to drive modeling forward as a tool that contributes to experimental discovery. The Drosophila melanogaster gap gene system, in which model parameters are optimized against in situ immunofluorescence intensities, demonstrates the importance of error quantification, which is applicable to a wide array of developmental modeling studies. (C) 2014 Elsevier Ltd. A

关键词： Developmental biology Mathematical modeling Dynamic modeling objective functions Parameter estimation Morphogens

来源：评论

学校读者我要写书评

暂无评论

Sensorless speed control of a five-phase induction machine under open-phase condition

引用

JOURNAL OF ENGINEERING-JOE 2014年第5期2014卷 201-209页

作者： Morsy, Ahmed S. Abdelkhalik, Ayman S. Ahmed, Shehab Massoud, Ahmed Mohamed Alexandria Univ Elect Power & Machines Dept Fac Engn Alexandria Egypt Texas A&M Univ Qatar Elect & Comp Engn Doha 23874 Qatar Qatar Univ Elect Engn Dept Doha Qatar

Recently, multiphase machines have been promoted as competitors to their three-phase counterparts in high-power safety-critical drive applications. Among numerous advantages of multiphase induction machine (IM) drives, self-starting and operation under open phase(s) stand as the most salient features. With open phase(s), optimal current control provides disturbance-free operation given a set of objective functions. Although hysteresis current control was merely employed in the literature as it offers a simple controller structure to control the remaining healthy phases, it is not suitable for high-power applications. In the literature, multiple synchronous reference frame (dq) control can be an alternative;however, it requires back and forth transformations with several calculations and additional sophistication. In this paper, a simple technique employing adaptive proportional resonant (PR) current controllers is presented to control a five-phase IM under open-phase conditions. Results for both volt/hertz (V/f) and field oriented control (FOC) systems are presented. Moreover, sensorless operation under fault condition is also demonstrated by estimating the machine speed using a rotor flux-based model reference adaptive system (MRAS) speed estimator. The proposed controllers are experimentally verified and compared. Although FOC provides better dynamic performance, V/f control offers a simpler control structure and a lower number of PR controllers.

关键词： angular velocity control induction motor drives sensorless machine control machine vector control electric current control model reference adaptive control systems sensorless speed control five-phase induction machine open-phase condition high-power safety-critical drive applications multiphase induction machine IM drives optimal current control objective functions hysteresis current control high switching frequency multiple synchronous reference frame adaptive proportional resonant current controllers PR field oriented control system FOC machine speed estimation rotor flux-based MRAS speed estimator prototype five-phase IM PR controllers power 1 hp

来源：评论

学校读者我要写书评

暂无评论

A linear programming based interactive method for multiobjective programming problems involving fuzzy coefficients and random variable coefficients 7

A linear programming based interactive method for multiobjec...

引用

Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS)

作者： Yano, Hitoshi Nagoya City Univ Sch Humanities & Social Sci Nagoya Aichi 4678501 Japan

ISBN: (纸本)9781479959556

In this paper, we propose a linear programming based interactive method for multiobjective linear programming problems, in which fuzzy coefficients and random variable coefficients are involved in the objective functions simultaneously. In the proposed method, it is assumed that the decision maker has a fuzzy goal for each objective function, and such a fuzzy goal can be quantified by eliciting the membership function. Through the possibility measure and a fractile optimization model, the original problem is transformed to the well-defined multiobjective programming problem. Then, a generalized Pareto optimal concept is defined, and a linear programming based interactive algorithm is proposed to obtain a satisfactory solution from among a generalized Pareto optimal solution set.

关键词： Pareto optimisation fuzzy set theory linear programming decision maker fractile optimization model fuzzy coefficients fuzzy goal generalized Pareto optimal solution set linear programming based interactive method membership function multiobjective programming problems objective functions possibility measure random variable coefficients Agriculture Decision making Linear programming Pareto optimization Programming Random variables

来源：评论

学校读者我要写书评

暂无评论

R2-BEAN: R2 Indicator Based Evolutionary Algorithm for Noisy Multiobjective Optimization 7

R2-BEAN: R2 Indicator Based Evolutionary Algorithm for Noisy...

引用

7th IEEE Symposium on Computational Intelligence for Security and Defense Applications (IEEE-CISDA)

作者： Phan, Dung H. Suzuki, Junichi Univ Massachusetts Dept Comp Sci Boston MA 02125 USA

ISBN: (纸本)9781479954315

This paper proposes and evaluates an indicator based and noise-aware dominance operator for evolutionary algorithms to solve the multiobjective optimization problems (MOPs) that contain noise in their objective functions. The proposed operator, U(R)2(-)dominance operator is designed with (1) a quality indicator, called R2 indicator, which quantifies the goodness of a given solution candidate (individual) and (2) a non-parametric (i.e., distribution-free) statistical significance test called the Mann Whitney U-test. The U-R2-dominance operator takes samples of given two individuals in the objective space, calculates the R2 indicator value for each sample, estimates the impacts of noise on the R2 values with a U-test, and determines which individual is statistically superior/inferior. Experimental results show that it operates reliably in noisy MOPs and outperforms existing noise aware dominance operators particularly when many outliers exist under asymmetric noise distributions.

关键词： evolutionary computation nonparametric statistics statistical testing Mann-Whitney U-test R2 indicator R2-BEAN UR2-dominance operator asymmetric noise distributions evolutionary algorithms indicator-based dominance operator multiobjective optimization problems noise-aware dominance operators noisy MOP noisy multiobjective optimization nonparametric statistical significance test objective functions objective space quality indicator Linear programming Noise Noise measurement Optimization Sociology Statistics Vectors evolutionary algorithm Noise quality indicator Nonparametric Statistics Noise measurement Statistical tests objective function Sociology linear programming Mann-Whitney test MOP Mops

来源：评论

学校读者我要写书评

暂无评论

The Optimal Design of Thermal Insulation on the Pipeline by using Particle Swarm Optimization

The Optimal Design of Thermal Insulation on the Pipeline by ...

引用

3rd International Conference on Materials and Products Manufacturing Technology (ICMPMT 2013)

作者： Lv, Hongyan Si, Xiaodong Wu, Wenzhen Northeast Petr Univ Sch Comp & Informat Technol Daqing Peoples R China Daqing Drilling Grp Int Div Daqing Peoples R China

ISBN: (纸本)9783037859162

Particle swarm optimization is simple, easily achieved and do not need to adjust many parameters. And it doesn't need the gradient information. Now, this algorithm has been widely used in function optimization, nerve network training, fuzzy systems control and so on. In this paper, we use this algorithm to solve the optimal design of thermal insulation on the pipeline. Numerical results show that this algrithm can get more precise results than methods before used.

关键词： Particle swarm optimization the optimal design of thermal insulation on the pipeline objective functions

来源：评论

学校读者我要写书评

暂无评论

Conjunctive Query Programming: A Paradigm for Knowledge Engineering of Optimization Problems in the Semantic Web

Conjunctive Query Programming: A Paradigm for Knowledge Engi...

引用

IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (WI-IAT)

作者： Fischer, Thomas Univ Jena Dept Business Informat Syst D-07743 Jena Germany

ISBN: (纸本)9781479941438

This paper explores the idea of integrating powerful optimization and planning techniques with knowledge representation formalisms of the Semantic Web. The paper outlines a language paradigm that combines algebraic and logical modelling of constraints and objective functions. It provides a method for instantiation of optimization and planning problems with Semantic Web background knowledge, by modelling objective functions and restrictions as algebraic and logic expressions of results of conjunctive queries. Furthermore, the paper investigates reasoning techniques for the language based on problem compilation to satisfiability modulo theories and integer programming.

关键词： algebra computability inference mechanisms integer programming knowledge representation planning (artificial intelligence) query processing semantic Web algebraic expressions conjunctive query programming knowledge engineering language paradigm logic expressions objective functions optimization techniques planning techniques problem compilation reasoning techniques satisfiability modulo theories semantic Web background knowledge Linear programming OWL Ontologies Optimization Planning Conjunctive Query Programming Semantic Web semantic networks Knowledge Representation Integer Programming Knowledge based engineering Planning Techniques objective function Algebra computability Inference mechanisms knowledge representation languages query analysis Ontology linear programming

来源：评论

学校读者我要写书评

暂无评论

SIMULATION-BASED MULTIobjective OPTIMIZATION OF BRIDGE CONSTRUCTION PROCESSES USING PARALLEL COMPUTING

SIMULATION-BASED MULTIOBJECTIVE OPTIMIZATION OF BRIDGE CONST...

引用

Winter Simulation Conference

作者： Salimi, Shide Mawlana, Mohammed Hammad, Amin Concordia Univ 1455 Maisonneuve Blvd West Montreal PQ H3G 1M8 Canada

ISBN: (纸本)9781479974863

Conventionally, efforts are made to optimize the performance of simulation models by examining several possible resource combinations. However, the number of possible resource assignments increases exponentially with the increase of the range of available resources. Many researchers combined Genetic Algorithms (GAs) and other optimization techniques with simulation models to reach the Pareto solutions. However, due to the large number of resources required in complex and large-scale construction projects, which results in a very large search space, and the limittion of the GA capability in fast convergence to the optimum results, parallel computing is required to reduce the computational time. This paper proposes the usage of Non-dominated Sorting Genetic Algorithm (NSGA-II) as the optimization engine integrated with Discrete Event Simulation (DES) to model the bridge construction processes. The parallel computing platform is applied to reduce the computation time necessary to deal with multiple objective functions and the large search space.

关键词： bridges (structures) discrete event simulation genetic algorithms parallel processing structural engineering computing DES NSGA-II Pareto solution bridge construction process construction projects nondominated sorting genetic algorithm objective functions optimization techniques parallel computing resource assignment simulation models simulation-based multiobjective optimization Bridges Computational modeling Genetic algorithms Optimization Parallel processing Sociology Statistics PARALLEL PROCESSING (COMPUTERS) discrete event simulation Genetic Algorithm (GA) Sociology Simulation models DES gene Diethylstilbestrol Computational modeling objective function bridges Bridge construction

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：