检索结果-内蒙古大学图书馆

Cognitive Radio Decision Engine Based on multi-objective genetic algorithm

3rd International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2011)

作者： Wu Di Yang Shengyao Liu, J. C. Dalian Univ Technol Sch Comp Sci Dalian Peoples R China Simon Fraser Univ Sch Comp Sci Vancouver BC Canada

ISBN: (纸本)9783037850190

The performance optimization of cognitive radio is a multi-objective optimization problem. Existing genetic algorithms are difficult to assign the weight of each objective when the linear weighting method is used to simplify the multi-objective optimization problem into a single objective optimization problem. In this paper, we propose a new cognitive decision engine algorithm using multi-objective genetic algorithm with population adaptation. A multicarrier system is used for simulation analysis, and experimental results show that the proposed algorithm is effective and meets the real-time requirement.

关键词： Cognitive radio multi-objective genetic algorithm Decision engine

来源：评论

学校读者我要写书评

暂无评论

Optimized Condition for Pairing of Different Friction Factor and Viscosity Equations for the Frictional Pressure Drop of R22 and R290

引用

INTERNATIONAL JOURNAL OF AIR-CONDITIONING AND REFRIGERATION 2019年第4期27卷

作者： Yousif, Qais Abid Mohd-Ghazali, Normah Pamitran, Agus Sunjarianto Mohd-Yunos, Yushazaziah Northern Tech Univ Engn Tech Coll Mosul Cultural Grp St Mosul 41002 Iraq Univ Teknol Malaysia Fac Engn Sch Mech Engn Utm Skudai 81310 Johor Malaysia Univ Indonesia Dept Mech Engn Kampus Baru UI Depok Depok 16424 Jawa Barat Indonesia Univ Kuala Lumpur MICET Sect Tech Fdn Alor Gajah 78000 Melaka Malaysia

Accurate prediction of the friction factor and consequently the pressure drop of two-phase flow in small channels is still an issue. Many correlations exist for the determination of the viscosity and the friction factor that appear in the frictional pressure drop and their combination often determined the degree of disagreements between the experimental data and predicted outcomes. Demands for environmentally friendly refrigerants have further posed a challenge to find compatible alternatives with as good a performance as the current coolants. Despite the many available correlations developed to date, many more are studied in effort to reduce the discrepancies. This paper presents the outcomes of a study comparing the optimized conditions when three different viscosity equations are paired with eight different friction factor correlations to minimize the frictional pressure drop. The approach used multi-objective genetic algorithm (MOGA) to assist in selecting the best pairing. Comparison is then completed with available experimental data. The study showed that the Blasius friction factor paired with the Dukler viscosity produced the least percentage difference for R22, while when paired with the McAdams viscosity produced a lower difference for R290, an environmentally friendly refrigerant being considered to replace R22.

关键词： Friction factor two-phase viscosity pressure drop multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Application of multi-objective genetic algorithm (MOGA) for Design Optimization of Valve Timing at Various Engine Speeds

Application of Multi-objective Genetic Algorithm (MOGA) for ...

引用

International Conference on Advances in Materials and Processing Technologies (AMPT)

作者： Mohiuddin, A. K. M. Rahman, Md. Ataur Shin, Yap Haw Int Islamic Univ Malaysia IIUM Dept Mech Engn Kuala Lumpur Malaysia

ISBN: (纸本)9783037850534

This paper aims to demonstrate the effectiveness of multi-objective genetic algorithm Optimization and its practical application on the automobile engine valve timing where the variation of performance parameters required for finest tuning to obtain the optimal engine performances. The primary concern is to acquire the clear picture of the implementation of multi-objective genetic algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. Majority of the research works in this project were in CAE software environment and method to implement optimization to ID engine simulation. The paper conducts robust design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. This paper involves engine modelling in ID software simulation environment, GT-Power. The GT-Power model is run simultaneously with mode Frontier to perform multi-objective optimization.

关键词： Optimization Valve timing multi-objective genetic algorithm GT-Suite

来源：评论

学校读者我要写书评

暂无评论

A multi-objective genetic algorithm for Pruning Support Vector Machines

A Multi-Objective Genetic Algorithm for Pruning Support Vect...

引用

23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Hady, Mohamed Farouk Abdel Herbawi, Wesam Weber, Michael Schwenker, Friedhelm Univ Ulm Inst Neural Informat Proc Ulm Germany Univ Ulm Inst Media Informat Ulm Germany

ISBN: (纸本)9780769545967

Support vector machines (SVMs) often contain a large number of support vectors which reduce the run-time speeds of decision functions. In addition, this might cause an overfitting effect where the resulting SVM adapts itself to the noise in the training set rather than the true underlying data distribution and will probably fail to correctly classify unseen examples. To obtain more fast and accurate SVMs, many methods have been proposed to prune SVs in trained SVMs. In this paper, we propose a multi-objective genetic algorithm to reduce the complexity of support vector machines as well as to improve generalization accuracy by the reduction of overfitting. Experiments on four benchmark datasets show that the proposed evolutionary approach can effectively reduce the number of support vectors included in the decision functions of SVMs without sacrificing their classification accuracy.

关键词： machine learning data mining Support vector machines multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimization Control of Internal Combustion Engine-Compressed Air Energy Storage Cogeneration System Based on genetic algorithm

Optimization Control of Internal Combustion Engine-Compresse...

引用

第37届中国控制会议

作者： Xiaopeng Hai Xingguo Wei Ke Li Junjie Gao Chenghui Zhang School of Control Science and Engineering Shandong University

In order to make better use of new energy and improve the utilization rate of energy, much concern have been paid to large-scale energy storage and combined cooling, heating and power（CCHP） technology. This study proposes a novel combined cooling, heating and power（CCHP） system with compressed air energy storage（CAES）. In order to improve the power generation efficiency and operating economy of the system, the multi-objective optimization algorithm based on genetic algorithm is used to control the output power of the two subsystems. The results show that the efficiency of the gas internal combustion engine can be maintained at a high level, while operating cost is low, the output power can be selected according to the actual requirements.

关键词： combined cooling, heating and power compressed air energy storage multi-objective genetic algorithm generation efficiency economic analysis

来源：评论

学校读者我要写书评

暂无评论

multi-objective Optimization of a Solar Chimney Power Plant with Inclined Collector Roof Using genetic algorithm

引用

ENERGIES 2016年第11期9卷 971页

作者： Gholamalizadeh, Ehsan Kim, Man-Hoe Kyungpook Natl Univ Sch Mech Engn Daegu 41566 South Korea

This paper presents an optimization of a solar chimney power plant with an inclined collector roof using genetic algorithms. Five design parameters that affect the system performance are the collector radius, collector inlet height, collector outlet height, chimney height and diameter. A multi-objective design to simultaneously optimize three conflicting objectives including system efficiency, power output and expenditure is used. Based on this approach, obtaining the best combination of the possible geometrical parameters, performance of two built pilot power plants in Kerman (Iran) and Manzanares (Spain) are optimized thermo-economically. The heights of the zero-slope collectors of the Kerman and Manzanares systems are 2 m and 1.85 m, respectively. The results show that in the Kerman pilot the optimal collector inlet and outlet heights are 1.5 m and 2.95 m, respectively, while those optimal heights in the Manzanares prototype are 1.5 m and 4.6 m, respectively. It is found that selecting the optimal collector roof configuration in addition to the other design parameters has a significant effect in the system optimization process.

关键词： solar chimney power plant inclined collector roof renewable energy multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An Inventive Method for Eco-Efficient Operation of Home Energy Management Systems

引用

ENERGIES 2018年第11期11卷 3091-3091页

作者： Hussain, Bilal Javaid, Nadeem Ul Hasan, Qadeer Javaid, Sakeena Khan, Asif Malik, Shahzad A. COMSATS Univ Islamabad Dept Elect Engn Islamabad 44000 Pakistan COMSATS Univ Islamabad Dept Comp Sci Islamabad 44000 Pakistan

A demand response (DR) based home energy management systems (HEMS) synergies with renewable energy sources (RESs) and energy storage systems (ESSs). In this work, a three-step simulation based posteriori method is proposed to develop a scheme for eco-efficient operation of HEMS. The proposed method provides the trade-off between the net cost of energy (CEnet) and the time-based discomfort (TBD) due to shifting of home appliances (HAs). At step-1, primary trade-offs for CEnet, TBD and minimal emissions TEMiss are generated through a heuristic method. This method takes into account photovoltaic availability, the state of charge, the related rates for the storage system, mixed shifting of HAs, inclining block rates, the sharing-based parallel operation of power sources, and selling of the renewable energy to the utility. The search has been driven through multi-objective genetic algorithm and Pareto based optimization. A filtration mechanism (based on the trends exhibited by TEMiss in consideration of CEnet and TBD) is devised to harness the trade-offs with minimal emissions. At step-2, a constraint filter based on the average value of TEMiss is used to filter out the trade-offs with extremely high values of TEMiss. At step-3, another constraint filter (made up of an average surface fit for TEMiss) is applied to screen out the trade-offs with marginally high values of TEMiss. The surface fit is developed using polynomial models for regression based on the least sum of squared errors. The selected solutions are classified for critical trade-off analysis to enable the consumer choice for the best options. Furthermore, simulations validate our proposed method in terms of aforementioned objectives.

关键词： eco-efficient home energy management dispatch of renewables and energy storage systems load-shedding-compensating dispatchable generators optimization using surface fitting techniques multi-objective genetic algorithm Pareto optimization

来源：评论

学校读者我要写书评

暂无评论

genetic algorithm-based Optimization of ELM for On-line Hyperspectral Image Classification

Genetic Algorithm-based Optimization of ELM for On-line Hype...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Echanobe, J. del Campo, I. Martinez, Victoria Basterretxea, K. Univ Basque Country UPV EHU Dept Elect & Elect Leioa Basque Country Spain Univ Basque Country UPV EHU Dept Elect Technol Bilbao Basque Country Spain

ISBN: (纸本)9781509061822

Hyperspectral remote sensing is becoming an active research field in the last decades thanks to the availability of efficient machine learning algorithms and also to the ever-increasing computation power. However, there exist application domains (e.g., embedded applications) in which the deployment of this kind of systems becomes unfeasible due to the high requirements related to the size, power consumption or processing speed. A way to overcome this trouble consists on using any method able to scale-down the dimensionality of the problem and/or to reduce the complexity of the machine learning models. In this paper, we propose the use of a multiobjective genetic algorithm to minimize both the dimension of the input space and the size of the machine learning model. In particular, we have developed a hyperspectral image classifier based on an Extreme Learning Machine (ELM) for which the number of system inputs (dimensionality) and the number of hidden neurons are minimized without decreasing its performance. The system is evaluated by using a known benchmark dataset.

关键词： Extreme Learning Machines (ELM) multi-objective genetic algorithm Machine Learning Hyperspectral remote sensing Dimensionality reduction

来源：评论

学校读者我要写书评

暂无评论

A numerical investigation and design optimization of impingement cooling system with an array of air jets

引用

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2017年第PartA期108卷 880-900页

作者： Lam, Prasanth Anand Kumar Prakash, K. Arul IIT Madras Dept Appl Mech Fluid Mech Lab Madras 600036 Tamil Nadu India

In the present study, fluid flow, heat transfer and entropy generation in impingement cooling system with an array of air jets for different values of Reynolds number (Re), Velocity Ratio (VR) and Channel Height (H/L) are investigated. The magnitude of overall Nusselt number ((NUo) over bar((v)) over bar) and global total entropy generation (S-tot,(Omega)) is found to increase with increasing Re,VR and decreasing H/L. Further, spectral and proper orthogonal decomposition analyses are performed to analyze spatio-temporal dynamics of vortex structures for unsteady configurations of impingement cooling system. It is observed that, along the interface of jet (both primary and secondary) and ambient fluid, the destabilizing effect of shear forces overcome the stabilizing effect of momentum diffusion. This results in evolution of counter-rotating vortex rings along the interfaces of jet and ambient fluid due to shear layer instability. Finally, multi objective genetic algorithm (MOGA) has been implemented to obtain optimum configurations of impingement cooling system where a trade-off between two performance parameters,(NUo) over bar((v)) over bar and S-tot,S-Omega is obtained. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Impinging jet array SUPG-finite element method Entropy generation Proper orthogonal decomposition multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Streamline-based history matching of bottomhole pressure and three-phase production data using a multiscale approach

引用

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 154卷 217-233页

作者： Kam, Dongjae Jichao Datta-Gupta, Akhil Texas A&M Univ Dept Petr Engn College Stn TX 77843 USA

Reconciling geological models to the available dynamic information, commonly known as history matching, is an essential step for optimizing reservoir management and field development strategies, including improved recovery methods. There are several challenges in the current history matching workflow, particularly for high resolution geologic models with multimillion cells and complex geologic architecture. Streamline-based inverse modeling has shown great promise in this respect because of computational efficiency and analytic calculation of sensitivity of production response to reservoir properties. However, the current streamline-based approach has mostly been applied to history matching water-cut and tracer response in two-phase flow. More recently streamline-based sensitivity calculations have been extended to bottomhole pressure and gas oil ratio. This allows for generalization of streamline-based history matching to the three-phase. In this paper we present an integrated application of the streamline-based three-phase history matching by incorporating water-cut, gas-oil ratio and bottomhole pressure data while updating high resolution geologic models. The crux of our approach lies in the analytic computation of well response sensitivities based on streamline which allows for efficient inversion of production and pressure data. We also validate the accuracy and efficiency of the streamline-based bottomhole pressure sensitivities by comparison with an adjoint-based method using a finite difference simulator. In the history matching workflow, we incorporate the streamline-based method within a multiscale framework to account for the disparity in resolution of different types of history data. This integrated method proposed in this paper leads to capturing of the large- and fine-scale heterogeneity while matching the pressure and production responses efficiently. We demonstrate the power and utility of the streamline-based approach using synthetic and field appli

关键词： Three-phase history matching Bottomhole pressure matching Streamlines multiscale approach multi-objective genetic 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：