检索结果-内蒙古大学图书馆

Packet loss rate monitoring model of IoT based on differential evolution algorithm

WEB INTELLIGENCE 2021年第3期19卷 215-226页

作者： Feng, Yinghua Yang, Wei Huainan Union Univ Sch Publ Educ Huainan 232001 Anhui Peoples R China Guangxi Vocat & Tech Inst Ind Dept Basic Course Nanning 530001 Guangxi Peoples R China

In order to overcome the problems of high energy consumption and low execution efficiency of traditional Internet of things (IoT) packet loss rate monitoring model, a new packet loss rate monitoring model based on differential evolution algorithm is proposed. The similarity between each data point in the data space of the Internet of things is set as the data gravity. On the basis of the data gravity, combined with the law of gravity in the data space, the gravity of different data is calculated. At the same time, the size of the data gravity is compared, and the data are classified. Through the classification results, the packet loss rate monitoring model of the Internet of things is established. differential evolution algorithm is used to solve the model to obtain the best monitoring scheme to ensure the security of network data transmission. The experimental results show that the proposed model can effectively reduce the data acquisition overhead and energy consumption, and improve the execution efficiency of the model. The maximum monitoring efficiency is 99.74%.

关键词： differential evolution algorithm IoT packet loss rate monitoring model

来源：评论

学校读者我要写书评

暂无评论

Integrated Renewable Energy Storage System with Enhanced Self-Adaptive differential evolution algorithm on Profit Maximization

引用

ELECTRIC POWER COMPONENTS AND SYSTEMS 2023年第8期52卷 1474页

作者： Kani, J. Shanmuga Ulagammai, M. Anna Univ Dept Elect & Elect Engn Chennai India Saveetha Engn Coll Dept Elect & Elect Engn Chennai 602105 India

In this work addresses the surge in greenhouse gas emissions and fuel costs resulting from heightened energy demand, especially in developing nations. To counter these challenges, the focus is on optimizing renewable energy sources, which, though advantageous, are weather-dependent and require intricate management. The study introduces the Enhanced Self-Adaptive differential evolution (SADE) algorithm, encompassing solar, battery, and thermal sources, to maximize profitability. Real-time (RT) load profiles are used for performance analysis, comparing the proposed algorithm with existing techniques like PSO, differential evolution (DE) algorithm, and SADE algorithm. Improved energy storage technologies complement the increased utilization of renewable energy, enabling electricity storage during off-peak hours and release during peak demand, providing promising solutions for the energy industry.

关键词： battery energy storage profit maximization Self-Adaptive differential evolution algorithm particle swarm optimization differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Hybrid differential evolution algorithm Integrating Operations Research and Reinforcement Learning approaches 24

Hybrid Differential Evolution Algorithm Integrating Operatio...

引用

Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and Informatics

作者： Panagiotis G. Giannopoulos Gregory P. Chondrokoukis Thomas K. Dasaklis School of Social Sciences Hellenic Open University Patras Greece Department of Industrial Management and Technology University of Piraeus Piraeus Greece

来源：评论

学校读者我要写书评

暂无评论

differential evolution algorithm of Basis Vector Scaling and Mirror Crossover 39

Differential Evolution Algorithm of Basis Vector Scaling and...

引用

39th Chinese Control Conference (CCC)

作者： Zhang, Chunmei Yang, Haibin Guo, Hongge Shi, Yanjun Taiyuan Univ Sci & Technol Coll Elect & Informat Engn Taiyuan 030024 Peoples R China

ISBN: (纸本)9789881563903

In order to avoid the problem of local optimality and low convergence accuracy, an improved differential evolution algorithm was proposed by combining the base vector scaling with the mirror crossover operation. Based on the basic difference algorithm, the base vector scaling coefficient is introduced to jump out of the local optimal value. In the process of crossover, mirror crossover is introduced to improve the probability of the better trial vector entering the selection step and promote the algorithm evolution. In order to verify the effectiveness of the improved differential evolution algorithm, the simulation results of 10 benchmark functions are compared with those of other algorithms in this paper. The results show that the proposed algorithm can avoid the algorithm from falling into local optimum and achieve better convergence performance.

关键词： differential evolution algorithm Base vector scaling Crossover operation Mirror Crossover

来源：评论

学校读者我要写书评

暂无评论

Inverse Design of Broadband Dispersion Compensation Fiber Based on Deep Learning and differential evolution algorithm

IEEE PHOTONICS JOURNAL

引用

IEEE PHOTONICS JOURNAL 2023年第3期15卷

作者： Ma, Fuxiao Ma, Yunjie Li, Peili Shi, Weihua Nanjing Univ Posts & Telecommun Coll Elect & Opt Engn Nanjing 210023 Peoples R China Nanjing Univ Posts & Telecommun Coll Flexible Elect Future Technol Nanjing 210023 Peoples R China

A Ge-doped dual-core dispersion compensation photonic crystal fiber (DC-DCPCF) is proposed. The small diameters of two layers' air holes make DC-DCPCF form a dual-core structure, which is conducive to broadband dispersion compensation. Low Ge-doped silica as the only background material reduces the preparation difficulty and cost. It is inversely designed by using artificial neural network (ANN) combined with differential evolution algorithm (DE) to obtain target dispersion compensation. ANN replaces the finite element method to accomplish fast forward prediction of DC-DCPCF properties. DE solves the single solution problem of single or cascade network that makes it flexible and reproducible. The results demonstrate that the designed DC-DCPCF can not only compensate 45 and 25 times its length of Corning single-mode fiber 28 (SMF28) in S+C+L+U bands and E+S+C+L+U bands respectively, but also accurately compensate the residual dispersion with effective dispersion compensation being only +0.005 similar to+0.842ps/(***) and -0.03 similar to+1.31ps/(***), respectively. In addition, the kappa values of DCP-PCF are well matched with SMF28 in the broadband wavelength range. It takes only about 10 seconds to complete the inverse design of the target DC-DCPCF. It provides a design method for custom DC-DCPCF and an efficient inverse design solution for photonic automation in fiber optical communication systems.

关键词： Deep learning differential evolution algorithm dual-core dispersion compensation fiber enter keywords or phrases in alphabetical order inverse design photonic crystal fiber

来源：评论

学校读者我要写书评

暂无评论

A NEW METHOD OF PARAMETER IDENTIFICATION FOR PROTON EXCHANGE MEMBRANE FUEL CELL BASED ON HYBRID PARTICLE SWARM OPTIMIZATION WITH differential evolution algorithm

引用

THERMAL SCIENCE 2023年第5B期27卷 4209-4222页

作者： Liu, Dong Yang, Xiangguo Guan, Cong Qi, Tianxi Zheng, Qinggen Wuhan Univ Technol Key Lab High Performance Ship Technol Minist Educ Wuhan Peoples R China

With the characteristics of high energy conversion efficiency, high energy density and low operating temperature, the proton exchange membrane fuel cells (PEMFC) have become one of the green energy sources with broad prospects. The establishment of accurate mathematical model of the PEMFC is the basis of simulation and control strategy. At present, some intelligent algorithms have certain drawbacks, and can hardly find the balanced point between precision and computational time. In this study, a novel parameter identification approach combining the hybrid particle swarm optimization (PSO) algorithm with differential evolution, i.e. hybrid DEPSO, is proposed to obtain the unknown parameters in the PEMFC mathematical model and solve the problems of premature convergence of PSO and poor global search ability of differential evolution. Six benchmark functions are applied to verify the performance of the algorithm. The results prove that the hybrid DEPSO can evade local optimum preferably while having swifter convergence rate. Two PEMFC stacks are investigated and modeled. In order to evaluate the accuracy of model, the sum of squared errors between the measured voltage and the estimated output voltage are examined. Numerical results show higher accuracy of the hybrid DEPSO-based model comparing with other recently published optimization approaches. Furthermore, the simulation results indicate that the accuracy of the PEMFC model optimized by the hybrid DEPSO algorithm improves 0.19-1.86%, which can provide a new solution the multi-objective optimization problem and promote the practical application of the PEMFC.

关键词： PEMFC parameters identification PSO algorithm differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimization of power distribution for electrothermal anti-icing systems by differential evolution algorithm

引用

APPLIED THERMAL ENGINEERING 2023年第1期221卷

作者： Guo, Xiaofeng Yang, Qian Zheng, Haoran Dong, Wei Shanghai Jiao Tong Univ Mech Engn 800 Dongchuan Rd Shanghai 200240 Peoples R China

Ice accretion on windward components of aircraft will seriously threaten flight safety. Electrothermal anti-icing systems can prevent icing on the critical components. They have great potential for lightweight and energy-saving aircraft. This paper develops a numerical anti-icing model coupled with heat conduction in a multi-layer composite structure to evaluate the anti-icing performance. Furthermore, a differential evolution algorithm is adopted to optimize the power distribution of an electrothermal anti-icing system with a fixed heating element layout to find the minimal power consumption to ensure that no runback water flows out of the protection area. The maximum anti-icing surface temperature, runback water range, and the maximum temperature in the multi-layer composite structure are selected as constraints during optimization to guarantee the effectiveness of the anti-icing protection system. The feasibility rule based on a constraint violation is deployed to handle the constraints. The distributions of internal temperature of the multi-layer structure, anti-icing surface temperature, and runback water are chosen to evaluate the performance of the electrothermal anti-icing system. Comparing these performance parameters of optimized and baselines cases shows that the differential evolution algorithm can obtain minimal power consumption based on the anti-icing model under fixed icing conditions and heating element layout. The analysis of different heat flux terms indicates that the heat power distribution of the electrothermal anti-icing system should match convection heat transfer coefficient distribution on the surface to increase the energy efficiency.

关键词： Electrothermal anti-icing systems Composite Optimization differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

A Multi-Strategy Improved differential evolution algorithm for UAV 3D trajectory planning in complex mountainous environments

引用

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年第1期125卷

作者： Zhang, Miaohan Han, Yuhang Chen, Shiyun Liu, Mingxian He, Zhaolei Pan, Nan Kunming Univ Sci & Technol Fac Civil Aviat & Aeronaut Kunming Peoples R China Yunnan Power Grid Co Lijiang Power Supply Bur Kunming Peoples R China Yunnan Power Grid Co Ltd Metering Ctr Kunming Peoples R China Kunming Holy Intelligent Technol Co Ltd Kunming Peoples R China

In response to the complexity of power repair in mountainous areas and the limitations of traditional vehicles due to terrain constraints, this study focuses on the three-dimensional trajectory planning problem of UAVs (Unmanned Aerial Vehicles) in mountainous environments. Our goal is to provide effective solutions for the trajectory planning problem of UAVs in mountainous environments. Firstly, a UAV trajectory planning model is established, incorporating optimization objectives such as energy consumption, trajectory cost, obstacle avoidance cost, smoothing cost, and stability cost. The trajectory planning problem is transformed into an objective function optimization task with multiple performance constraints. To overcome the inefficiency and infeasibility of traditional algorithms in solving complex three-dimensional flight environments, we propose improvements to the differential evolution (DE) algorithm through three strategies: incorporating mutation crossover factor optimization strategy, an adaptive guidance mechanism, and an elite disturbance mechanism based on population classification. The Multi-Strategy Improved differential evolution (MSIDE) algorithm is introduced, and its time and space complexity are analyzed. Finally, the proposed method is compared with various algorithms through benchmark functions tests, Friedman test, Wilcoxon rank-sum test, simulation experiments in three-dimensional environments, and parameter sensitivity analysis experiments. The simulation results show that compared with the current state-of-the-art algorithms, the MSIDE algorithm improves the objective function value by 11.34% on average in regular terrain and 5.04% on average in complex terrain environments. The results demonstrate the convergence, multi-objective search capability, and global search ability of MSIDE, validating its effectiveness in solving the trajectory planning problem of UAVs in complex mountainous environments.

关键词： UAV Trajectory planning Multi-strategy improvement differential evolution algorithm Mountainous areas

来源：评论

学校读者我要写书评

暂无评论

Siegel distance-based fusion strategy and differential evolution algorithm for cooperative spectrum sensing

引用

DIGITAL SIGNAL PROCESSING 2023年 142卷

作者： Zhuang, Jiawei Wang, Yonghua Peng, Shiguo Zhang, Shunchao Liu, Yang Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China Guangdong Univ Finance Sch Internet Finance & Informat Engn Guangzhou 510521 Peoples R China Guangdong Univ Technol Sch Informat Engn Guangzhou 510006 Peoples R China

Cooperative spectrum sensing (CSS) offers cognitive radio networks a promising solution to efficiently address the issue of spectrum scarcity. To enhance the detection performance of CSS, we investigate a novel cooperative spectrum sensing scheme that incorporates a data fusion strategy based on Siegel distance and a differential evolution algorithm. Specifically, we utilize the Siegel distance-based data fusion strategy to acquire effective signal features. Additionally, to tackle the challenge of deriving the decision threshold, we design a novel symmetrized Kullback-Leibler divergence-based differential evolution algorithm to train the decision classifier, enabling it to detect the availability of licensed spectrum. Finally, we present simulation results that clearly demonstrate the effectiveness of our developed scheme.(c) 2023 Elsevier Inc. All rights reserved.

关键词： Cooperative spectrum sensing Siegel distance Data fusion Symmetrized Kullback-Leibler divergence differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

Research on Active Disturbance Rejection Control of Small Modular Reactor Once-Through Steam Generator Based on differential evolution Optimization algorithm

引用

NUCLEAR TECHNOLOGY 2025年第5期211卷 974-993页

作者： Guo, Wei Shi, Bo Zhang, Tao Wu, Zhijiang Xiong, Guohua Peng, Minjun Harbin Engn Univ Coll Nucl Sci & Technol Harbin 150006 Heilongjiang Peoples R China China Nucl Power Technol Res Inst TT&P Res Inst Shenzhen 518000 Peoples R China

The pressure control of once-through steam generator (OTSG) is critical for the operation and safety of small modular reactors. However, the dynamics of the OTSG are quite nonlinear, time varying, and uncertain. Classical control methods face significant challenges in keeping the pressure within acceptable limits in an environment with frequent load variations and multiple sources of external *** this paper, a robust control strategy based on active disturbance rejection control (ADRC) optimized by the differential evolution (DE) algorithm is proposed to satisfy the requirements of steam pressure control in an optimum and efficient way. First, a lumped parameter model for the OTSG is developed based on the notion of moving boundaries and linearized to introduce a transfer function model for control design purposes. Then a feedforward cascade control system based on an ADRC controller and a proportional integral differential (PID) controller is designed, which mainly consists of a pressure ADRC controller, a feedwater PID controller, and a feedforward *** improve the pressure control performance and parameter tuning efficiency of the OTSG control system, a DE algorithm is applied to optimize the ADRC parameters, and the frequency domain and time domain characteristics are compared with particle swarm optimization and the genetic algorithm. Transient simulation experiments were used to evaluate the control performance at 100%, 50%, and 25% power levels, respectively. Moreover, a performance robustness criterion is proposed to demonstrate the robust stability of the ADRC, and the robustness metric is compared with that of the PID control schemes. The simulation results show that DE-ADRC control strategy has better set point tracking, interference rejection, and robust stability than DE-PID control strategy.

关键词： Once-through steam generator lumped parameter model active disturbance rejection control parameter tuning differential evolution 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：