检索结果-内蒙古大学图书馆

Optimization Alternatives for Robust Model-based Design of Synthetic Biological Circuits

IFAC-PapersOnLine 2016年第7期49卷 821-826页

作者： Boada, Y. Pitarch, J.L. Vignoni, A. Reynoso-Meza, G. Picó, J. Universitat Politècnica de Valencia Camino de Vera S/N Valencia46022 Spain Systems Engineering and Control Department Universidad de Valladolid C/ Real de Burgos S/N Valladolid47011 Spain Center for Systems Biology Dresden and the Max Planck Institute of Molecular Cell Biology and Genetics Pfotenhauer str. 108 Dresden01307 Germany Pontifícia Universidade Catolica do Parana Imaculada Conceião 1155 CuritibaPR80215-901 Brazil

Synthetic biology is reaching the situation where tuning devices by hand is no longer possible due to the complexity of the biological circuits being designed. Thus, mathematical models need to be used in order, not only to predict the behavior of the designed synthetic devices; but to help on the selection of the biological parts, i.e., guidelines for the experimental implementation. However, since uncertainties are inherent to biology, the desired dynamics for the circuit usually requires a trade-off among several goals. Hence, a multi-objective optimization design (MOOD) naturally arises to get a suitable parametrization (or range) of the required kinetic parameters to build a biological device with some desired properties. Biologists have classically addressed this problem by evaluating a set of random Monte Carlo simulations with parameters between an operation range. In this paper, we propose solving the MOOD by means of dynamic programming using both a global multi-objective evolutionary algorithm (MOEA) and a local gradient-based nonlinear programming (NLP) solver. The performance of both alternatives is then checked in the design of a well-known biological circuit: a genetic incoherent feed-forward loop showing adaptive behavior. © 2016

关键词： Dynamic programming Computer aided design Economic and social effects evolutionary algorithms Genetic programming Intelligent systems Kinetic parameters Monte Carlo methods multiobjective optimization Nonlinear programming Timing circuits Adaptive behavior Biological parts Feedforward loops Local gradients multi objective evolutionary algorithms Parametrizations Robust modeling Synthetic biology

来源：评论

学校读者我要写书评

暂无评论

Fast Solutions Enhancing using a Copula-based EDA and SVM for many-objective problems

引用

IFAC-PapersOnLine 2016年第12期49卷 781-786页

作者： Cheriet, Abdelhakim Cherif, Foudil Taleb-Ahmed, Abdelmalik LESIA Laboraroty University of Biskra Algeria LAMIH Electrical Engineering Department Valenciennes United States

In this paper we propose a new Copula-based Estimation of Distribution Algorithm, to solve Many-objective optimization problem and to get new optimal solutions in very court time. Our algorithm uses the proprieties of Copula and exploits their statistical properties to make new solutions using the founded optimal solutions through the estimation of their distribution. The first step of the proposed Copula-based Estimation of Distribution Algorithm (CEDA-SVM) is taking initial solutions offered by any MOEA (multi objective evolutionary Algorithm), and then creates Copulas to estimate their distribution, and we use Support Vector Machine (SVM) to learn the Pareto solutions model; those Copulas will be used to generate new solutions and SVM to avoid the expensive function evaluations. The idea of using the estimated distribution of the optimal solutions helps CEDA-SVM to avoid running the optimizer ( MOEA ) every time we need new alternatives solutions when the founded ones are not satisfactory. We tested CEDA-SVM on a set of many-objective benchmark problems traditionally used by the community, namely DTLZ (1, 2, 3, and 4) with different dimensions (3, 5, 8, 10, and 15). We used CEDA along with MOEA/D-Schy and MOEA/D-BI as two examples of MOEA thus resulting in two variants CEDA-MOAE/D-Scy and CEDA-MOEA/D-BI and compare them with MOEA/D-Schy and MOEA/D-BI. The results of our experiments show that, with both variants of CEDA-SVM, new solutions can be obtained in a very small time compared to the other algorithms. © 2016

关键词： evolutionary algorithms Distribution functions multiobjective optimization Optimal systems Support vector machines Bench mark problems Copula Estimation of distribution algorithms Initial solution Many objective optimizations multi objective evolutionary algorithms Optimal solutions Statistical properties

来源：评论

学校读者我要写书评

暂无评论

Rare-PEARs: A new multi objective evolutionary algorithm to mine rare and non-redundant quantitative association rules

引用

KNOWLEDGE-BASED SYSTEMS 2015年 89卷 366-384页

作者： Almasi, Mehrdad Abadeh, Mohammad Saniee Tarbiat Modares Univ Fac Elect & Comp Engn Tehran Iran

Since finding quantitative association rules (QARs) is an NP-hard problem, evolutionary methods are suitable solutions for discovery QARs. Nevertheless, most of the previous evolutionary methods to discover association rules only consider frequent dependency among items in datasets. They do not pay specific attention to interestingness and non-redundancy as two critical objectives. In this paper, the proposed algorithm (Rare-PEARs) gives a chance to each rule with different length and appearance (antecedent and consequent parts of rules) to be created. Therefore, various interesting, rare or interesting and rare rules can be found. Some of these rules might be uninteresting (those that contain frequent item sets). However, we try to avoid them by Rare-PEARs. To accomplish this goal, our method decomposes the process of association rule mining into N - 1 sub-problems (N is the number of attributes, and each sub-problem is handled by an independent sub-process during Rare-PEARs execution). Each sub-process starts individually with a different initial population. It then explores the search space of its corresponding sub-problem to find rules with semi-optimal intervals for each of the attributes. This process is done by a new definition of Non-Dominated concept. Rare-PEARs uses this definition to find semi-optimal intervals for attributes during the execution of each sub-process. Finally, Rare-PEARs collects QARs from sub-processes and determines the ultimate Non-Dominated rules based on the interestingness and reliability measures. Rare-PEARs tries to maximize three objectives: interestingness, accuracy and reliability while providing vast coverage on the input dataset. We compared Rare-PEARs with ten algorithms (multi-objective, mono-objective and classical algorithms of association rule mining) over several real-world datasets. The results demonstrate high efficiency of Rare-PEARs. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Random permutation multi objective evolutionary algorithms Quantitative association rules

来源：评论

学校读者我要写书评

暂无评论

Constraint Handling and multi-objective Methods for the Evolution of Interplanetary Trajectories

引用

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2015年第4期38卷 792-799页

作者： Izzo, Dario Hennes, Daniel Riccardi, Annalisa ESA European Space Res & Technol Ctr NL-2201 AZ Noordwijk Netherlands

A study is conducted to demonstrate constraint handling and multi-objective methods for the evolution of interplanetary trajectories. The study is based on the methods developed during GTOC6 and few advanced evolutionary techniques able to evolve complex Jupiter capture options are proposed. The evolutionary process is set up to be able to deal with constraints, along with multiple objectives and show the use of advanced evolutionary techniques to effectively search the solution space in both cases. The investigations show how these techniques allow the evolution of solutions of use to trajectory designers for the complex trajectory case considered in this study where other approaches fail to find acceptable solutions in a reasonable time.

关键词： Spacecraft Trajectory Optimization Callisto multi objective evolutionary algorithms Cumulative Distribution Function Deep Space Maneuver Sequential Quadratic Programming Genetic Algorithm Trajectory Optimization Annealing Derivative Free Method

来源：评论

学校读者我要写书评

暂无评论

multi-objective Optimization of Electric Vehicle Fast Charging Stations with SPEA-II

引用

IFAC-PapersOnLine 2015年第30期48卷 535-540页

作者： Shi, Ruifeng Lee, Kwang Y. School of Control and Computer Engineering North China Electric Power University Beijing China Department of Electrical and Computer Engineering Baylor University TX76798 United States

During the past two decades, electrification of the transportation sector is gradually becoming a global trend due to the environmental benefits from electric vehicle (EV). Although EV charging post plays as a primary energy supply, public EV Fast Charging Station (FCS) is definitely an important backup energy supply system to the EV customers in case of urgent need. Based on current existing FCS system and the prediction of the EV charging need in the future, this paper proposes a multi-objective EV FCS layout re-planning optimization problem, which simultaneously takes the economic issue and the customers' satisfaction into consideration. To solve the problem a popular multi-objective evolutionary algorithm, Strengthen Pareto evolutionary Algorithm-II (SPEA-II), is employed in this study. Numerical case studies shows that the SPEA-II can successfully address the balance between different objectives during the re-planning FCS procedure by contrast to that of a single-objective optimization method (Improved Genetic Algorithm). © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： multiobjective optimization Customer satisfaction Electric vehicles Energy resources Fast charging (Batteries) Genetic algorithms Numerical methods Charging station planning Customers' satisfaction Environmental benefits Fast charging stations multi objective evolutionary algorithms Optimization problems Single objective optimization SPEA II

来源：评论

学校读者我要写书评

暂无评论

Thermal Performance Analysis and Optimization of Microjet Cooling of High-Power Light-Emitting Diodes

引用

JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER 2013年第2期27卷 235-245页

作者： Husain, Afzal Kim, Sun-Min Kim, Jun-Hee Kim, Kwang-Yong Inha Univ Dept Mech Engn Inchon 402751 South Korea

The present study investigates the thermal and hydraulic performance of the microjet array cooling system for thermal management of a high-power light-emitting diode array. Three-dimensional numerical analyses were performed for steady incompressible turbulent flow and conjugate heat transfer through a finite volume solver. The performances of several microjet array configurations, viz., 1-jet, 4-jet, 9-jet, 13-jet, and 16-jet arrays, were analyzed at two flow rates and top-cavity heights. The design optimization of a 4-jet array cooling system was performed using a multi-objective evolutionary algorithm. For the optimization, two design variables, viz., ratio of the nozzle diameter and height of the top cavity and ratio of the height and length of the top cavity, were selected. The thermal resistance and pressure drop were selected as the objective functions of the design. The Pareto-optimal solutions were obtained and discussed in view of the thermal resistance and pressure drop and sensitivity of design variables to objective functions.

关键词： Thermal Performance Diodes Heat Transfer Coefficients multi objective evolutionary algorithms Thermal Management Turbulent Flow Numerical Modeling Thermoelectric Cooling Total Mass Flow Rate Heat Transfer Fluid

来源：评论

学校读者我要写书评

暂无评论

multi-objective Optimization of Helicopter Airfoils Using Surrogate-Assisted Memetic algorithms

引用

JOURNAL OF AIRCRAFT 2012年第2期49卷 375-383页

作者： Massaro, Andrea Benini, Ernesto Univ Padua I-35131 Padua Italy

An effective strategy for airfoil numerical optimizations is presented that deals with multi-objective and multipoint problems and is specifically designed for helicopter applications. This technique is tested on several realistic problems of airfoil optimization with the aim of improving their aerodynamic performance by searching for optimal shape. The procedure is based On a multi-objective surrogate-assisted memetic algorithm coupled to a Navier-Stokes solver. First, the peculiar features of the algorithm are described with particular attention to its advantages when compared with more traditional evolutionary or gradient-based algorithms. Finally, the results of the optimizations carried out using different operating conditions are presented;starting from the optimal Pareto fronts, several solutions are selected and compared in terms of shapes and performance.

关键词： multi objective evolutionary algorithms Helicopter Blade Thin Airfoil Navier Stokes Solver Aerodynamic Performance Numerical Optimization Aerodynamic Simulation Neural Networks Reynolds Averaged Navier Stokes Numerical Simulation

来源：评论

学校读者我要写书评

暂无评论

Optimization of Rotating Cooling Channel with Pin Fins Downstream of Turning Region

引用

JOURNAL OF THERMOPHYSICS AND HEAT TRANSFER 2012年第1期26卷 85-97页

作者： Moon, Mi-Ae Kim, Kwang-Yong Inha Univ Dept Mech Engn Inchon 402751 South Korea

The heat transfer performance of a rotating two-pass rectangular channel with staggered pin-fin arrays is optimized through Reynolds-averaged Navier-Stokes analysis, a surrogate method, and a multi-objective evolutionary algorithm. As the Pareto-optimal front produces a set of optimal solutions, the trends in the objective functions in relation to the design variables are predicted by a hybrid multi-objective evolutionary algorithm. Two objective functions related to heat transfer and friction loss, respectively, have been considered to estimate the performance of the cooling channel in turbine blades. Two design variables are selected, viz., the ratio of the diameter to height of the pin fins and the ratio of the streamwise spacing between the pin fins to height of the pin fins, and 20 designs are generated by Latin hypercube sampling. A response surface approximation model as a surrogate model is constructed for each objective function, and a hybrid multi-objective evolutionary algorithm is applied to obtain the Pareto-optimal front. The Reynolds number that is based on the hydraulic diameter of the channel is fixed at 10,000, while the rotation number is held constant at 0.15. The turning region upstream of the pin fins enhances the heat transfer through the channel, since a strong vortical flow structure is created in this region. At some optimal points on the Pareto-optimal front, it is found that the present multi-objective optimization enhances both the heat transfer performance and the pressure-loss characteristics. The effects of the rotation number on the heat transfer and pressure loss are also discussed.

关键词： Enhancing Heat Transfer Rate Reynolds Averaged Navier Stokes multi objective evolutionary algorithms multigrid Methods Reynolds Number Turbine Inlet Temperature Friction Factor Aspect Ratio Horseshoe Vortex Coolant

来源：评论

学校读者我要写书评

暂无评论

Linguistic Summarization of Time Series Data using Genetic algorithms

Linguistic Summarization of Time Series Data using Genetic A...

引用

7th Biannual Conference of the European-Society-for-Fuzzy-Logic-and-Technology (EUSFLAT)/17th Annual LFA Meeting

作者： Castillo-Ortega, Rita Marin, Nicolas Sanchez, Daniel Tettamanzi, Andrea G. B. Univ Granada Granada Spain European Ctr Soft Comp Mieres Asturias Spain Univ Milan Crema CR Italy

ISBN: (纸本)9789078677000

In this paper, the use of an evolutionary approach when obtaining linguistic summaries from time series data is proposed. We assume the availability of a hierarchical partition of the time dimension in the time series. The use of natural language allows the human users to understand the resulting summaries in an easy way. The number of possible final summaries and the different ways of measuring their quality has taken us to adopt the use of a multi objective evolutionary algorithm. We compare the results of the new approach with our previous greedy algorithms.

关键词： Linguistic Summarization multi objective evolutionary algorithms Time Series Dimensional Data Model Fuzzy Logic

来源：评论

学校读者我要写书评

暂无评论

A Cognitive Approach to Load Balancing for Green Houses

A Cognitive Approach to Load Balancing for Green Houses

引用

General Meeting of the IEEE-Power-and-Energy-Society (PES)

作者： Lugo-Cordero, Hector M. Fuentes-Rivera, Abigail Guha, Ratan K. Ortiz-Rivera, Eduardo I. Univ Cent Florida Dept Elect Engn & Comp Sci Orlando FL 32816 USA Univ Puerto Rico Dept Elect & Comp Engn Mayaguez PR 00681 USA

ISBN: (纸本)9781457710018

In this paper the case study of a smart home powered by solar and wind energy is presented. The benefits of having a smart home that can control the amount of power needed, according to the context of the usage, are also shown. Simulation shows that with a good control of the load it might be possible to reduce the installation costs of the Green Energy System. Furthermore, to support the results, a load balancing algorithm is created based on the Knapsack problem. An economic analysis of the approach is also shown to demonstrate the viability of the project, and how can the intelligence in the home lower the cost.

关键词： Smart Home Context Reasoning Green Energy multi objective evolutionary algorithms

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：