检索结果-内蒙古大学图书馆

For LEO Satellite Networks: Intelligent Interference Sensing and Signal Reconstruction Based on Blind Separation Technology

引用

China Communications 2024年第2期21卷 85-95页

作者： Chengjie Li Lidong Zhu Zhen Zhang The Key Laboratory for Computer Systems of State Ethnic Affairs Commission School of Computer Science and Technology(Southwest Minzu University)Chengdu 610000China National Key Laboratory of Science and Technology on Communications(University of Electronic Science and Technology of China) Chengdu 610000China College of Computer Science(Sichuan University) Chengdu 610000China

In LEO satellite communication networks,the number of satellites has increased sharply, the relative velocity of satellites is very fast, then electronic signal aliasing occurs from time to time. Those aliasing signals make the receiving ability of the signal receiver worse, the signal processing ability weaker,and the anti-interference ability of the communication system lower. Aiming at the above problems, to save communication resources and improve communication efficiency, and considering the irregularity of interference signals, the underdetermined blind separation technology can effectively deal with the problem of interference sensing and signal reconstruction in this scenario. In order to improve the stability of source signal separation and the security of information transmission, a greedy optimization algorithm can be executed. At the same time, to improve network information transmission efficiency and prevent algorithms from getting trapped in local optima, delete low-energy points during each iteration process. Ultimately, simulation experiments validate that the algorithm presented in this paper enhances both the transmission efficiency of the network transmission system and the security of the communication system, achieving the process of interference sensing and signal reconstruction in the LEO satellite communication system.

关键词： blind source separation greedy optimization algorithm interference sensing LEO satellite communication networks signal reconstruction

来源：评论

学校读者我要写书评

暂无评论

A novel multi-strategy self-optimizing SAPSO algorithm for PMSM parameter identification

引用

IET POWER ELECTRONICS 2023年第2期16卷 305-319页

作者： Wen, Dingdou Shi, Chuandong Zhang, Yang Liao, Kaixian Liu, Jianhua Luo, Bing Wang, Tingting Hunan Univ Technol Coll Elect & Informat Engn Zhuzhou Hunan Peoples R China CSG Elect Power Res Inst Co Ltd Guangzhou Guangdong Peoples R China

To address the unsatisfactory performance of particle swarm optimization (PSO), a novel multi-strategy self-optimizing simulated annealing particle swarm optimization (SOSAPSO) method for permanent magnet synchronous motor (PMSM) parameter identification is proposed. The full-rank mathematical model and the fitness function are developed. In SOSAPSO, the velocity term of the PSO is simplified and dynamic opposition-based learning (DOBL) is introduced in the inertia weight update process to avoid population monotonicity. Moreover, A Cauchy-Gaussian hybrid variation strategy based on similarity and density is devised to achieve self-learning in deep regions. Meanwhile, the simulated annealing (SA) with a memory and tempering mechanism is introduced into SOSAPSO, and the greedy optimization algorithm (GOA) is used to enhance local fine-exploitation capabilities when SOSAPSO evolution is stalled. The test results indicate the proposed method can effectively avoid local convergence problems and has better robustness and convergence speed.

关键词： greedy optimization algorithm permanent magnet synchronous motor Optimisation techniques simulated annealing particle swarm optimization method SOSAPSO evolution dynamic opposition-based learning inertia weight update process multistrategy self-optimizing SAPSO algorithm permanent magnet motors local convergence problems PSO tempering mechanism Cauchy-Gaussian hybrid variation strategy particle swarm optimisation convergence synchronous motors local fine-exploitation capabilities Synchronous machines PMSM parameter identification simulated annealing mathematical analysis full-rank mathematical model fitness function

来源：评论

学校读者我要写书评

暂无评论

Research on the coupling relationship between manufacturing technology innovation and energy consumption based on intelligent algorithms

引用

JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY 2021年第5期144卷 1689-1696页

作者： Lan, Sha Hu, Haiqing Xian Univ Technol Inst Econ & Management Xian 710054 Shaanxi Peoples R China Northwest Univ Polit Sci & Law Inst Business Xian 710063 Shanxi Peoples R China

In the current era, the energy consumption of the manufacturing industry is very serious. How to achieve optimal control of energy consumption in the manufacturing process with technological innovation as the driving force has become a current research hotspot. Based on this, this article has deeply studied the application of control technology in energy consumption management and control, and designed the sparse coupling relationship and analysis model based on the greedy optimization algorithm. From the aspects of conventional energy consumption, technical methods, output control and energy consumption in the manufacturing industry, based on production data, the optimal control strategy for energy consumption is analyzed and quantitatively evaluated through the greedy optimization algorithm. The results show that the energy consumption relationship analysis model based on the matching tracking algorithm has the advantages of high computational efficiency and high precision.

关键词： greedy optimization algorithm Manufacturing industry Technological innovation Energy consumption

来源：评论

学校读者我要写书评

暂无评论

Solving randomized time-varying knapsack problems by a novel global firefly algorithm

引用

ENGINEERING WITH COMPUTERS 2018年第3期34卷 621-635页

作者： Feng, Yanhong Wang, Gai-Ge Wang, Ling Hebei GEO Univ Sch Informat Engn Shijiazhuang 050031 Hebei Peoples R China Ocean Univ China Dept Comp Sci & Technol Qingdao 266100 Peoples R China Northeast Normal Univ Inst Algorithm & Big Data Anal Changchun 130117 Jilin Peoples R China Northeast Normal Univ Sch Comp Sci & Informat Technol Changchun Jilin Peoples R China Tsinghua Univ Dept Automat Beijing Peoples R China

In this paper, a novel global firefly algorithm (GFA) is proposed for solving randomized time-varying knapsack problems (RTVKP). The RTVKP is an extension from the generalized time-varying knapsack problems (TVKP), by dynamically changing the profit and weight of items as well as the capacity of knapsack. In GFA, two-tuples which consists of real vector and binary vector is used to represent the individual in a population, and two principal search processes are developed: the current global best-based search process and the trust region-based search process. Moreover, a novel and effective two-stage repair operator is adopted to modify infeasible solutions and optimize feasible solutions as well. The performance of GFA is verified by comparison with five state-of-the-art classical algorithms over three RTVKP instances. The results indicate that the proposed GFA outperform the other five methods in most cases and that GFA is an efficient algorithm for solving randomized time-varying knapsack problems.

关键词： Firefly algorithm greedy optimization algorithm Dynamic optimization Knapsack problem

来源：评论

学校读者我要写书评

暂无评论

Research on fault-tolerant relay node placement based on greedy optimization algorithm in wireless sensor networks

Research on fault-tolerant relay node placement based on gre...

引用

International Conference on Industry, Information System and Material Engineering

作者： Wang, Zhu Wang, Qi Wei, DeBao Harbin Inst Technol Sch Informat Sci & Engn Weihai 264209 Peoples R China Harbin Inst Technol Sch Elect Engn & Automat Harbin 150001 Peoples R China

ISBN: (纸本)9783037850275

In this paper, relay node's communication capacity was introduced into the existing model of relay node placement. And we presented a new evaluation standard based on the minimum distance factor of communication network. A new relay node placement algorithm was implemented in solutions, and the algorithm was based on greedy optimization algorithm. The simulation result demonstrates that the algorithm can limit the communication capacity of relay nodes conveniently. Compared with other placement algorithms, improvement of energy-efficiencies in this algorithm is obvious.

关键词： fault-tolerant relay node placement the minimum distance factor of communication network greedy optimization algorithm communication capacity wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Solving 0-1 knapsack problem by a novel binary monarch butterfly optimization

引用

NEURAL COMPUTING & APPLICATIONS 2017年第7期28卷 1619-1634页

作者： Feng, Yanhong Wang, Gai-Ge Deb, Suash Lu, Mei Zhao, Xiang-Jun Shijiazhuang Univ Econ Sch Informat Engn Shijiazhuang 050031 Hebei Peoples R China Jiangsu Normal Univ Sch Comp Sci & Technol Xuzhou 221116 Jiangsu Peoples R China Northeast Normal Univ Inst Algorithm & Big Data Anal Changchun 130117 Peoples R China Northeast Normal Univ Sch Comp Sci & Informat Technol Changchun 130117 Peoples R China

This paper presents a novel binary monarch butterfly optimization (BMBO) method, intended for addressing the 0-1 knapsack problem (0-1 KP). Two tuples, consisting of real-valued vectors and binary vectors, are used to represent the monarch butterfly individuals in BMBO. Real-valued vectors constitute the search space, whereas binary vectors form the solution space. In other words, monarch butterfly optimization works directly on real-valued vectors, while solutions are represented by binary vectors. Three kinds of individual allocation schemes are tested in order to achieve better performance. Toward revising the infeasible solutions and optimizing the feasible ones, a novel repair operator, based on greedy strategy, is employed. Comprehensive numerical experimentations on three types of 0-1 KP instances are carried out. The comparative study of the BMBO with four state-of-the-art classical algorithms clearly points toward the superiority of the former in terms of search accuracy, convergent capability and stability in solving the 0-1 KP, especially for the high-dimensional instances.

关键词： Evolutionary computation Monarch butterfly optimization Knapsack problems greedy optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

An Improved Hybrid Encoding Firefly algorithm for Randomized Time-varying Knapsack Problems 2

An Improved Hybrid Encoding Firefly Algorithm for Randomized...

引用

2nd International Conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Feng, Yanhong Wang, Gai-Ge Shijiazhuang Univ Econ Sch Informat Engn Shijiazhuang Peoples R China Jiangsu Normal Univ Sch Comp Sci & Technol Xuzhou Peoples R China

ISBN: (纸本)9781467398190

In this paper, an improved hybrid encoding firefly algorithm (IFA) is proposed for solving randomized time varying knapsack problems (RTVKP). The RTVKP is an extension from the generalized time-varying knapsack problems (TVKP) by dynamically changing the profit and weight of items as well as the capacity of knapsack. In IFA, two-tuples composed of real vector and binary vector is used to represent the individuals in a population, and two principal search processes are developed: the current global best-based search process and the trust region-based search process. Moreover, a novel and effective repair operator is adopted to modify infeasible solutions, optimize feasible solutions and calculate the fitness of individual. The performance of IFA is verified by comparison with FA, cuckoo search (CS), shuffled frog leaping algorithm (SFLA), genetic algorithms (GAs) and differential evolution (DE) over three instances of RTVKP. The results indicate that IFA outperformed the other five methods in most cases and the proposed IFA is an efficient algorithm for solving randomized time-varying knapsack problems.

关键词： Firefly algorithm greedy optimization algorithm Dynamic optimization Knapsack problem

来源：评论

学校读者我要写书评

暂无评论

optimization of Catalytically Active Sites Positioning in Porous Cathodes of Lithium/Air Batteries Filled with Different Electrolytes

引用

JOURNAL OF THE ELECTROCHEMICAL SOCIETY 2015年第14期162卷 A2796-A2804页

作者： Dabrowski, Tatjana Struck, Alexander Fenske, Daniela Maass, Peter Ciacchi, Lucio Colombi Univ Bremen Bremen Ctr Computat Mat Sci Fac Prod Engn Hybrid Mat Interfaces Grp D-28359 Bremen Germany Univ Bremen Ctr Environm Res & Sustainable Technol D-28359 Bremen Germany Fraunhofer Inst Mfg Technol & Adv Mat IFAM D-26129 Oldenburg Germany Rhine Waal Univ Appl Sci Fac Technol & Bion D-47533 Kleve Germany Univ Bremen MAPEX Ctr Mat & Proc D-28359 Bremen Germany Univ Bremen Ctr Ind Math D-28359 Bremen Germany

The capacity of current lithium/air cells is severely limited first and foremost by the electrochemical stability of the employed electrolyte and second by the occlusion of the pores of the active cathode surface due to non-uniform deposition of Li2O2 as the discharge product. Here we solve numerically a reaction-diffusion equation to determine the Li2O2 deposition profiles in a model porous cathode in the absence and presence of discrete catalytic sites, considering five commonly used electrolytes. We implement a greedy optimization algorithm to maximize the cathode capacity before pore clogging by optimal positioning of the discrete catalysts along the pore. The results indicate that, under the assumption of equal electrochemical stability, a maximal theoretical capacity is limited by the oxygen solubility and diffusivity in each electrolyte in the absence of catalysts and vary widely in the five cases considered. However, optimal catalyst distributions can effectively compensate for these differences, suggesting a rational way of designing cathode structures with high performances according to the required operation conditions. (C) 2015 The Electrochemical Society. All rights reserved.

关键词： Catalysts Finite-difference method greedy optimization algorithm Lithium/air battery Organic electrolytes Reaction-diffusion equation

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：