检索结果-内蒙古大学图书馆

multi-objective optimization for RNA design with multiple target secondary structures

BMC BIOINFORMATICS 2015年第1期16卷 1-20页

作者： Taneda, Akito Hirosaki Univ Grad Sch Sci & Technol Hirosaki Aomori Japan

Background: RNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available. Results: We developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed. Conclusions: Currently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algori

关键词： RNA switch Artificial riboswitch multi-objective genetic algorithm Pseudoknot

来源：评论

学校读者我要写书评

暂无评论

Evolutionary algorithm-based multi-objective task scheduling optimization model in cloud environments

引用

WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS 2015年第6期18卷 1737-1757页

作者： Ramezani, Fahimeh Lu, Jie Taheri, Javid Hussain, Farookh Khadeer Univ Technol Sydney Decis Support & E Serv Intelligence Lab Ctr Quantum Computat & Intelligent Syst Sch SoftwareFac Engn & Informat Technol Sydney NSW 2007 Australia Univ Sydney Sch Informat Technol Ctr Distributed & High Performance Comp Sydney NSW 2006 Australia

Optimizing task scheduling in a distributed heterogeneous computing environment, which is a nonlinear multi-objective NP-hard problem, plays a critical role in decreasing service response time and cost, and boosting Quality of Service (QoS). This paper, considers four conflicting objectives, namely minimizing task transfer time, task execution cost, power consumption, and task queue length, to develop a comprehensive multi-objective optimization model for task scheduling. This model reduces costs from both the customer and provider perspectives by considering execution and power cost. We evaluate our model by applying two multi-objective evolutionary algorithms, namely multi-objective Particle Swarm Optimization (MOPSO) and multi-objective genetic algorithm (MOGA). To implement the proposed model, we extend the Cloudsim toolkit by using MOPSO and MOGA as its task scheduling algorithms which determine the optimal task arrangement among VMs. The simulation results show that the proposed multi-objective model finds optimal trade-off solutions amongst the four conflicting objectives, which significantly reduces the job response time and makespan. This model not only increases QoS but also decreases the cost to providers. From our experimentation results, we find that MOPSO is a faster and more accurate evolutionary algorithm than MOGA for solving such problems.

关键词： Cloud computing Task scheduling multi-objective particle swarm optimization multi-objective genetic algorithm Jswarm Cloudsim

来源：评论

学校读者我要写书评

暂无评论

A Knee-Point Based NSAG-Ⅱ for Urban Tourism Path Planning

A Knee-Point Based NSAG-Ⅱ for Urban Tourism Path Planning

引用

2016战略管理国际会议

作者： Zhang Zhenzhong Ge Peng Ren Peiyu Zheng Weimin Liao Zhixue Business school Sichuan University

With the rapid development of tourism, people begin to pursue personalized and experience-oriented travelling ways. These new demands can be satisfied by the tourist route optimization with tourist preference, which is also an important way to improve tourist satisfaction and increase the competitiveness of scenic spots. Therefore how to provide tourist an optimum route is an important concern both for scenic manager and tourists. In order to provide the best tourism route for tourists, this paper firstly builds a multi-objective optimization model which takes minimum cost and maximum revenue as two objectives of this model. Furthermore, a knee-point based NSAG-Ⅱ was designed as solution methods.

关键词： tourism route multi-objective optimization model multi-objective genetic algorithm tourist preference

来源：评论

学校读者我要写书评

暂无评论

multi-objective Optimization of Different Management Scenarios to Control Seawater Intrusion in Coastal Aquifers

引用

WATER RESOURCES MANAGEMENT 2015年第6期29卷 1843-1857页

作者： Javadi, Akbar Hussain, Mohammed Sherif, Mohsen Farmani, Raziyeh Univ Exeter Sch Engn Comp Sci & Math Exeter EX4 4QF Devon England UAE Univ Civil & Environm Engn Dept Fac Engn Al Ain U Arab Emirates

Seawater intrusion (SWI) is a widespread environmental problem, particularly in arid and semi-arid coastal areas. Therefore, appropriate management strategies should be implemented in coastal aquifers to control SWI with acceptable limits of economic and environmental costs. This paper presents the results of an investigation on the efficiencies of different management scenarios for controlling saltwater intrusion using a simulation-optimization approach. A new methodology is proposed to control SWI in coastal aquifers. The proposed method is based on a combination of abstraction of saline water near shoreline, desalination of the abstracted water for domestic consumption and recharge of the aquifer by deep injection of the treated wastewater to ensure the sustainability of the aquifer. The efficiency of the proposed method is investigated in terms of water quality and capital and maintenance costs in comparison with other scenarios of groundwater management. A multi-objective genetic algorithm based evolutionary optimization model is integrated with the numerical simulation model to search for optimal solution of each scenario of SWI control. The main objective is to minimize both the total cost of management process and the total salinity in aquifer. The results indicate that the proposed method is efficient in controlling SWI as it offers the least cost and least salinity in the aquifer.

关键词： Seawater intrusion Simulation-optimization multi-objective genetic algorithm Treated wastewater Management scenarios

来源：评论

学校读者我要写书评

暂无评论

A Radial Basis Function Classifier for the Automatic Diagnosis of Cerebral Vascular Accidents

A Radial Basis Function Classifier for the Automatic Diagnos...

引用

Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges Conference

作者： M.G. Ruano E. Hajimani A. E. Ruano Faculty of Science and Technology University of Algarve Faro Portugal and CISUC University of Coimbra Portugal Faculty of Science and Technology University of Algarve Faro Portugal Faculty of Science and Technology University of Algarve Faro Portugal and IDMEC Instituto Superior Técnico Universidade de Lisboa Portugal

ISBN: (纸本)9781509024872

A Radial Basis Function Neural Network (RBFNN) based diagnosis system for automatic identification of Cerebral Vascular Accident (CVA) through analysis of Computer Tomographic images (CT) is presented. For the design of a neural network classifier, most published methods just focus on the feature selection aspect and do not consider any approach for determining a model structure that best fits the application at their hand. Moreover, considering the domain of lesion detection from brain tissues, their feature space rarely contains symmetry/asymmetry information with respect to ideal mid-sagittal line. Another issue is how to handle multiple conflicting objectives in the design process, such as the maximization of both specificity and sensitivity, enforcing as well generalization. To deal with these challenges, a multi objective genetic algorithm (MOGA) based approach is used to determine the architecture of the classifier, its corresponding parameters and input features subject to multiple objectives, as well as their corresponding restrictions and priorities.

关键词： Cerebral Vascular Accident Intelligent support systems multi-objective genetic algorithm Neural Networks Symmetry Features

来源：评论

学校读者我要写书评

暂无评论

Optimization of shape and angle of attack of winglet vortex generator in a rectangular channel for heat transfer enhancement

引用

APPLIED THERMAL ENGINEERING 2015年 81卷 376-387页

作者： Abdollahi, Azita Shams, Mehrzad KN Toosi Univ Technol Dept Mech Engn Tehran Iran

A three dimensional numerical simulation was performed to study the effect of the shape and the angle of attack of the winglet vortex generator on the heat transfer and fluid flow characteristics in a rectangular heat sink. The mass, momentum and energy equations were solved using finite volume method by considering the steady state, laminar and incompressible fluid flow. The average and local Nusselt number and pressure drop were investigated in the presence of the vortex generators at different shapes and angles of attack. To achieve a maximum heat transfer enhancement and a minimum pressure drop, the optimal values of these parameters were calculated using the Pareto optimal strategy. For this purpose, computational fluid dynamics analyses, multi-objective genetic algorithm and artificial neural networks were combined together and used in the optimization process. Finally, the optimal values of these parameters were presented. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Heat transfer enhancement Vortex generator multi-objective genetic algorithm Artificial neural network

来源：评论

学校读者我要写书评

暂无评论

Partially Optimized Cyclic Shift Crossover for multi-objective genetic algorithms for the multi-objective Vehicle Routing Problem with Time-Windows

Partially Optimized Cyclic Shift Crossover for Multi-Objecti...

引用

2014 IEEE Symposium on Computational Intelligence in multi-Criteria Decision-Making (MCDM)

作者： Pierre, Djamalladine Mahamat Zakaria, Nordin Univ Teknol PETRONAS Ctr High Performance Comp Perak Malaysia

ISBN: (纸本)9781479944675

The complexity of the Vehicle Routing Problems (VRPs) and their applications in our day to day life has garnered a lot of attentions in the area of optimization. Recently, attentions have turned to multi-objective VRPs with multi-objective genetic algorithms (MOGAs). MOGAs, thanks to its genetic operators such as selection, crossover, and/or mutation, constantly modify a population of solutions in order to find optimal solutions. However, given the complexity of VRPs, conventional crossover operators have major drawbacks. The Best Cost Route Crossover is lately gaining popularity in solving multi-objective VRPs. It employs a brute force approach to generate new children. Such approach may be unacceptable when presented with a relatively large problem instance. In this paper, we introduce a new crossover operator, called Partially Optimized Cyclic Shift Crossover (POCSX). A comparative study, between a MOGA based on POCSX, and a MOGA which is based on the Best Cost Route Crossover affirms the level of competitiveness of the former.

关键词： multi-objective Vehicle Routing Problem multi-objective genetic algorithm Crossover Mutation

来源：评论

学校读者我要写书评

暂无评论

Proportional integral controller gain tuning using real time digital simulation models and multi-objective optimization based co-simulation

Proportional integral controller gain tuning using real time...

引用

9th IFAC Symposium on Control of Power and Energy Systems (CPES 2015)

作者： Prabakar, Kumaraguru Li, Fangxing Univ Tennessee Knoxville TN USA

Proportional integral (PI) controller is a widely used controller strategy. It has two gain constants: proportional(k(p)) and integral(k(i)) gain constant. The dynamics of the PI controller depends on the values of the gain constant used. If gains of these control terms are not selected properly, instability Will occur. Gain tutting methodologies are available to tune these controllers to avoid instability. Hut, these gain tuning strategies and algorithms utilize simplified mathematical model of the plant ut order to obtain gain values. This approach might, not provide optimal gain values for models used in real time digital simulator. In the proposed approach, the algorithm utilizes the step response of the system to obtain optimal gain constants. The plant is modeled using the real time digital simulator (RIDS). A multi-objective optimization formulation is used to find the optimal gain constants. Results are presented here to support the effectiveness of proposed multi-objective gain tutting strategy. (C) 2015, IFAC (International Rderation or Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Proportional integral control Gain tuning multi-objective optimization multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Co-ordinated Design of AVR-PSS Using multi objective genetic algorithm

引用

1st International Conference on Swarm, Evolutionary, and Memetic Computing

作者： Selvabala, B. Devaraj, D. Sri Manakula Vinayagar Engn Coll Dept EEE Pondicherry India kalasalingam Univ krishnankoil Tamil Nadu India

ISBN: (纸本)9783642175626

Automatic Voltage Regulator (AVR) regulates the generator terminal voltage by controlling the amount of current supplied to the generator field winding by the exciter. Power system stabilizer (PSS) is installed with AVR to damp the low frequency oscillations in power system by providing a supplementary signal to the excitation system. Optimal tuning of AVR controller and PSS parameters is necessary for the satisfactory operation of the power system. When applying tuning method to obtain the optimal controller parameters individually, AVR improves the voltage regulation of the system and PSS improves the damping of the system. Simultaneous tuning of AVR and PSS is necessary to obtain better both voltage regulation and oscillation damping in the system. This paper deals with the optimal tuning of AVR controller and PSS parameters in the synchronous machine. The problem of obtaining the optimal controller parameters is formulated as an optimization problem and multi-objective genetic algorithm (MOGA) is applied to solve the optimization problem. The suitability of the proposed approach has been demonstrated through computer simulation in a Single Machine Infinite Bus (SMIB) system.

关键词： Automatic Voltage Regulator Power System Stabilizer multi-objective genetic algorithm Single Machine Infinite Bus system

来源：评论

学校读者我要写书评

暂无评论

Kansei Engineering System for Test Generation Using multi-objective Optimization 2

Kansei Engineering System for Test Generation Using Multi-Ob...

引用

2nd International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Choudhary, Kavita Shilpa ITM Univ Dept CSE&IT Gurgaon India ITM Univ Gurgaon India

SoftwareQuality plays a critical role in software development. This paper emphasize on involvement of Kansei Engineering in the field of test case generation. multi-objective genetic algorithm under multi-objective op... 详细信息

ISBN: (纸本)9789380544168

关键词： Kansei engineering multi-objective optimization multi-objective genetic algorithm Pareto-optimal Boolean-specific conditions etc

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：