检索结果-内蒙古大学图书馆

Efficient method for estimation of smooth and nonsmooth fuel cost curves for thermal power plants

INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2018年第3期28卷 1-1页

作者： Sayah, Samir Hamouda, Abdellatif Ferhat Abbas Univ Dept Elect Engn QUERE Lab Setif 1 Algeria Ferhat Abbas Univ Dept Opt & Fine Mech QUERE Lab Setif 1 Algeria

For accurate economic dispatch solution, it is necessary to periodically estimate the parameters of fuel cost function. This paper proposes an improved differential evolution algorithm for computing the optimal parameters of fuel cost functions for thermal power plants. A new mutation strategy is suggested to enhance convergence rate and improve solution quality of original differential evolution. The proposed approach is examined on different test systems with several generator cost curve models involving smooth and nonsmooth/nonconvex functions. The results using the proposed approach are compared to those available in recent literature. The results show the efficiency of the proposed estimation approach for obtaining accurate fuel cost parameters without any restriction on the mathematical model of the generator cost curve.

关键词： economic dispatch fuel cost function improved differential evolution algorithm optimal power flow parameters estimation valve-point loading

来源：评论

学校读者我要写书评

暂无评论

Design of multipurpose digital FIR double-band filter using hybrid firefly differential evolution algorithm

引用

APPLIED SOFT COMPUTING 2017年 59卷 529-545页

作者： Dash, Judhisthir Dam, Bivas Swain, Rajkishore Silicon Inst Technol Dept ECE Bhubaneswar Orissa India Jadavpur Univ Dept IEE Kolkata India Silicon Inst Technol Dept EEE Bhubaneswar Orissa India

Signal filtering can be treated as one of the basic requisite of communication networks. Design of an appropriate digital filter demands such filter coefficients that will create the desired frequency response with tolerable amount of ripples in the stop band(s) and pass band(s) along with high attenuation in the stop band(s). Now-a-days, artificial evolutionary methods are employed in the modern digital filter design due to lots of advantages over typical methods. In this paper, multipurpose digital linear phase double band filter (LPDBF) is designed proposing a hybrid meta-heuristic technique called hybrid firefly differential evolution (HFDE) algorithm. Generally these filters are required in different specific modern digital system networks for the simultaneous processing of signals present in two or three different channels. The proposed HFDE is an efficient evolutionary hybrid technique and is modelled considering both the optimization advantages of improved differential evolution (IDE) and firefly techniques. The global searching capability of IDE technique is strengthened by improved firefly movement. The performance of the proposed HFDE method of LPDBF design is contrasted with few popular optimal methods of design. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Double-band filter improved differential evolution algorithm HFDE algorithm Fitness error

来源：评论

学校读者我要写书评

暂无评论

A disjunctive belief rule-based expert system for bridge risk assessment with dynamic parameter optimization model

引用

COMPUTERS & INDUSTRIAL ENGINEERING 2017年 113卷 459-474页

作者： Yang, Long-Hao Wang, Ying-Ming Chang, Lei-Lei Fu, Yang-Geng Fuzhou Univ Decis Sci Inst Fuzhou 350116 Fujian Peoples R China Xian High Tech Inst Dept Management Xian 710025 Shaanxi Peoples R China Fuzhou Univ Sch Math & Comp Sci Fuzhou 350116 Fujian Peoples R China

Bridge risk assessment is an important approach to avoiding the safety accidents of bridges and ensuring the safety of the public. This can be done by investigating the relationship between bridge risks and bridge criteria. However, such relationship usually is highly complicated in actual situations. In this regard, many approaches were proposed to model bridge risks in the past decades. Particularly, four alternative approaches including the artificial neural network (ANN), evidential reasoning with learning (ERL), multiple regression analysis (MRA), and adaptive neuro-fuzzy inference system (ANFIS) were deeply analyzed and compared for bridge risk assessment. However, these approaches are restricted by their shortages. Thus, this paper utilizes the disjunctive belief rule-based (DBRB) expert system to model bridge risks, where the DBRB expert system is one type of the belief rule-based (BRB) expert system by considering disjunctive belief rules (DBRs) rather than conjunctive belief rules (CBRs) in a BRB. Furthermore, the dynamic parameter optimization model and improved differential evolution (IDE) algorithm are proposed to train the parameters of the DBRB expert system, where the model is applied to ensure the completeness of a DBRB and the algorithm is used to get the global optimal solution. For justification purpose, two existing parameter optimization models and nine alternative models developed by the ANN, ERL, MRA, and ANFIS are applied to assess bridge structures. Comparison results indicate that the DBRB expert system with the dynamic parameter optimization model is better than those alternative models and existing parameter optimization models.

关键词： Bridge risk assessment Disjunctive belief rule-based expert system Dynamic parameter optimization model improved differential evolution algorithm Completeness

来源：评论

学校读者我要写书评

暂无评论

Energy-aware Resource Allocation Scheme for Device-to-Device Communication Based on NOMA Underlaying Cellular Networks 17

Energy-aware Resource Allocation Scheme for Device-to-Device...

引用

IEEE 17th International Conference on Communication Technology (ICCT)

作者： Li, Bingshan Zhang, Heli Ji, Hong Li, Xi Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing Peoples R China

ISBN: (纸本)9781509039449

In this paper, power-domain NOMA is applied to D2D communications, and then an optimization problem to maximize the system total energy efficiency (EE) is formulated while guarantying the quality of service (QoS) of both cellular users and D2D users. This optimization problem is a mixed integer fractional programming (MIFP) with a large-scale solution space. Then in order to solve the problem with low complexity, a novel energy aware resource allocation scheme based on improved differential evolution algorithm (EARASIDE) is developed. It is a joint physical resource block (RB) allocation and power control scheme. Finally, extensive simulation results show that the proposed EARAS-IDE algorithm with a low complexity is able to converge quickly and approximate the optimal solution after introducing the dynamic mutation factor F. Additionally, compared with OMA scheme, the NOMA scheme achieves higher EE performance gains at the cost of slightly increased receiver complexity.

关键词： D2D communication NOMA energy efficiency quality of service improved differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

New Stochastic Bi-Objective Optimal Cost and Chance of Operation Management Approach for Smart Microgrid

引用

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2016年第6期12卷 2031-2040页

作者： Zare, Mohsen Niknam, Taher Azizipanah-Abarghooee, Rasoul Ostadi, Amir Univ Jahrom Dept Elect Engn Jahrom *** Iran Shiraz Univ Technol Dept Elect & Elect Engn Shiraz 71555313 Iran Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

This paper develops a new probabilistic optimization framework based on chance constrained programming for bi-objective optimal energy management in microgrids considering intermittent characteristics of wind and photovoltaic power, and customers' load profile. The proposed approach uses a method based on jointly distributed random variables to calculate the chance of meeting the load requirements while maintaining the operation cost below a present value. The framework benefits from the new improved hybrid artificial bee colony and differential evolution algorithm as the optimization technique to solve the optimal energy management of a grid-connected microgrid. A sample average approximation approach is used to verify the results of the proposed method in comparison with the scenario-based and the Monte Carlo-based stochastic programming.

关键词： Artificial bee colony chance constrained programming (CCP) improved differential evolution algorithm jointly distributed random variables (JDRV) microgrid

来源：评论

学校读者我要写书评

暂无评论

A PD-type Multi Input Single Output SSSC damping controller design employing hybrid improved differential evolution-pattern search approach

引用

APPLIED SOFT COMPUTING 2015年 32卷 532-543页

作者： Panda, Sidhartha Kiran, S. Harish Dash, S. S. Subramani, C. VSSUT Dept Elect & Elect Engn Burla 768018 Odisha India SRM Univ Dept Elect Engn Madras 603203 Tamil Nadu India

In this paper, a Proportional Derivative (PD)-type Multi Input Single Output (MISO) damping controller is designed for Static Synchronous Series Compensator (SSSC) controller. Both local and remote signals with associated time delays are chosen as the input signal to the proposed MISO controller. The design problem is formulated as an optimization problem and a hybrid improved differential evolution and Pattern Search (hIDEPS) technique is employed to optimize the controller parameters. The improvement in differential evolution (DE) algorithm is introduced by changing two of its most important control parameters i.e. Scaling Factor F and Crossover Constant CR with an objective of achieving improved performance of the algorithm. The superiority of proposed improved DE (IDE) over original DE and hIDEPS over IDE has also been demonstrated. To show the effectiveness and robustness of the proposed design approach, simulation results are presented and compared with DE and Particle Swarm Optimization (PSO) optimized Single Input Single Output (SISO) SSSC based damping controllers for both Single Machine Infinite Bus (SMIB) power system and multi-machine power system. It is noticed that the proposed approach provides superior damping performance compared to some approaches available in literature. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Power system stability Static Synchronous Series Compensator (SSSC) improved differential evolution algorithm Pattern search Multi Input Single Output controller

来源：评论

学校读者我要写书评

暂无评论

Multi-Input Single Output SSSC based damping controller design by a hybrid improved differential evolution-Pattern Search approach

引用

ISA TRANSACTIONS 2015年 58卷 173-185页

作者： Panda, Sidhartha Yegireddy, Narendra Kumar Veer Surendra Sai Univ Technol Dept Elect & Elect Engn Burla 768018 Odisha India

In this paper, a hybrid improved differential evolution and Pattern Search (hIDEPS) approach is proposed for the design of a PI-Type Multi-Input Single Output (MISO) Static Synchronous Series Compensator (SSSC) based damping controller. The improvement in differential evolution (DE) algorithm is introduced by a simple but effective scheme of changing two of its most important control parameters i.e. step size and crossover probability with an objective of achieving improved performance. Pattern Search (PS) is subsequently employed to fine tune the best solution provided by modified DE algorithm. The superiority of a proposed hIDEPS technique over DE and improved DE has also been demonstrated. At the outset, this concept is applied to a SSSC connected in a Single Machine Infinite Bus (SMIB) power system and then extended to a multi-machine power system. To show the effectiveness and robustness of the proposed design approach, simulation results are presented and compared with DE and Particle Swarm Optimization (PSO) optimized Single Input Single Output (SISO) SSSC based damping controllers. It is observed that the proposed approach yield superior damping performance compared to some approaches available in the literature. (C) 2015 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Power system stability Static Synchronous Series Compensator (SSSC) improved differential evolution algorithm Pattern Search Multi-Input Single Output controller

来源：评论

学校读者我要写书评

暂无评论

Energy-aware Resource Allocation Scheme for Device-to-Device Communication Based on NOMA Underlaying Cellular Networks

Energy-aware Resource Allocation Scheme for Device-to-Device...

引用

2017 17th IEEE International Conference on Communication Technology (ICCT 2017)

作者： Bingshan Li Heli Zhang Hong Ji Xi Li Key Laboratory of Universal Wireless Communications Ministry of Education Beijing University of Posts and Telecommunications

In this paper, power-domain NOMA is applied to D2 D communications, and then an optimization problem to maximize the system total energy efficiency（EE） is formulated while guarantying the quality of service（QoS） of both cellular users and D2 D users. This optimization problem is a mixed integer fractional programming（MIFP） with a large-scale solution space. Then in order to solve the problem with low complexity, a novel energy aware resource allocation scheme based on improved differential evolution algorithm（EARASIDE） is developed. It is a joint physical resource block（RB） allocation and power control scheme. Finally, extensive simulation results show that the proposed EARAS-IDE algorithm with a low complexity is able to converge quickly and approximate the optimal solution after introducing the dynamic mutation factor F. Additionally, compared with OMA scheme, the NOMA scheme achieves higher EE performance gains at the cost of slightly increased receiver complexity.

关键词： D2D communication NOMA energy efficiency quality of service improved differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Hybrid improved differential evolution and Wavelet Neural Network with load forecasting problem of air conditioning

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2014年 61卷 673-682页

作者： Liao, Gwo-Ching Fortune Inst Technol Dept Elect Engn Kaohsiung 83160 Taiwan

Air-conditioning load forecasting accuracy precludes high efficacy air-conditioning operation, and is also a key advantage in developing Smart Microgrid (SMG) power generating system control. The Wavelet Neural Network (WNN) was adopted as a principle element in air-conditioning load forecasting with improved differential evolution algorithm (IDEA) as an optimizing method for adjusting WNN parameters. This approach has replaced the formal feedback method used in solving network parameters. IDEA is an optimizing technique with simple calculation and fewer adjustable parameters, allowing the optimum solution for the entire system to be acquired more accurately and rapidly. After solving the optimum parameters WNN is further applied to accomplish air-conditioning load forecasting. A Fuzzy Expert System is adopted as an adjustment measure for special conditions, allowing ideal forecasting results to be reached. This study made practical comparisons among the generally applied methods for optimizing air-conditioning forecasting, such as the Artificial Neural Network (ANN), evolutionary Programming-Artificial Neural Network (EP-ANN), Genetic algorithm-Artificial Neural Network (GA-ANN), Ant Colony Optimization-Artificial Neural Network (ACO-ANN) and Particle Swarm Optimization-Artificial Neural Network (PSO-ANN), to prove the advantages and applicability of the proposed method. (c) 2014 Elsevier Ltd. All rights reserved.

关键词： improved differential evolution algorithm Wavelet Neural Network Fuzzy Expert System Load forecasting of air-conditioning

来源：评论

学校读者我要写书评

暂无评论

Structure control classification and optimization model of hollow carbon nanosphere core polymer particle based on improved differential evolution support vector machine

引用

APPLIED MATHEMATICAL MODELLING 2013年第12-13期37卷 7442-7451页

作者： Yang, Zhen Yu, Qingni Dong, Wenping Gu, Xingsheng Qiao, Wenming Liang, Xiaoyi E China Univ Sci & Technol Inst Informat Sci Minist Educ State Key Lab Chem EngnKey Lab Special Funct Pol Shanghai 200237 Peoples R China China Astronaut Res & Training Ctr Natl Key Lab Human Factors Engn Beijing 100095 Peoples R China

The structure of core polymer particle is an important index of efficiency in hollow carbon nanosphere. How to control and optimize the structure of core polymer particle has been investigated using pattern recognition method in this research. A novel method of pattern recognition material design based on differential evolution support vector machine was proposed. The control model was established and software was adopted to carry out a digital simulation for the model. Using the model, we found the control criteria and optimized conditions for pore structure of composite polymer. Then, the results are compared to other classification methodologies. Experimental results show this model has higher classification accuracy in most of data sets. Experimental and dynamics results show that the properties of hollow carbon nanosphere have been greatly improved. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Hollow carbon nanosphere Structure control Support vector machine improved differential evolution algorithm Classification Optimization

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：