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Stabilization of multi-rotation unstable periodic orbits through dynamic extended delayed feedback control

CHAOS SOLITONS & FRACTALS 2022年 161卷

作者： Zheng, Y. G. Yu, J. L. Nanchang Hangkong Univ Sch Math & Informat Sci Nanchang 330063 Jiangxi Peoples R China

The dynamic extended delayed feedback control (DEDFC) is developed to stabilize multi-rotation unstable peri-odic orbits (UPOs). The multi-rotation UPO here refers to the UPO that rotates more than once in a period. The DEDFC is derived by applying a dynamic control technique on the standard extended delayed feedback control (EDFC), to improve its control performance. The DEDFC is designed to meet two objectives, including enlarging the stability region of the controlled UPOs and minimizing the magnitude of the greatest Floquet multiplier. Then, a multi-objective optimization problem (MOP) is formulated for the control design and is solved with the genetic algorithm and cell mapping hybrid method. Case studies indicate that the control effect of DEDFC sig-nificantly outperforms that of standard EDFC when the control parameters are appropriately designed. The DEDFC can stabilize some multi-rotation UPOs in a large stability region. However, the standard EDFC can keep those multi-rotation UPOs stable only in a small stability region or cannot stabilize them at all.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Chaoscontrol Multi-rotationperiodicorbit Delayedfeedbackcontrol Floquetmultiplier geneticalgorithm

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A hybrid intelligent genetic algorithm for truss optimization based on deep neutral network

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SWARM AND EVOLUTIONARY COMPUTATION 2022年 73卷

作者： Liu, Jiepeng Xia, Yi Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China Chongqing Univ Key Lab New Technol Construct Cities Mt Area Minist Educ Chongqing 400045 Peoples R China

The truss optimization problem has been extensively investigated, and the optimized trusses have been widely used in various fields. Truss optimization is a challenging optimization involving many difficulties, such as discrete variables and non-convex problems. In order to solve these problems, various metaheuristic optimization methods have been proposed. Due to the stochastic feature of these methods, it is always computationally intensive, and the optimization results may vary greatly in different optimization runs. In this paper, a hybrid intelligent genetic algorithm (HIGA) is proposed to improve the effectiveness and efficiency of truss optimization problems. This method systematically integrates deep neural network (DNN) and genetic algorithm (GA) in the optimization process. A two-step training procedure is proposed where the data generated during the optimization process is exploited to update DNN. Next, based on the generated DNN model, an optimization prediction procedure is proposed to seek more optimized trusses in an efficient manner. Through the investigation of three classical truss problems (size optimization, shape optimization and size-shape integrated optimization), the effectiveness of the proposed method is validated. In addition, the influence of different settings on the optimization performance and efficiency is investigated to demonstrate the applicability and robustness of the proposed method.

关键词： Trussoptimization Deepneuralnetwork geneticalgorithm Hybridintelligentoptimization Trussbridge

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Bio-inspired optimization design and fluid-solid-thermal multi-field verification analysis of labyrinth seal

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MATERIALS & DESIGN 2022年 220卷

作者： Cao, Xiaojian Li, Jialiang Liu, Jianlin China Univ Petr East China Coll Pipeline & Civil Engn Qingdao 266580 Peoples R China Shandong Univ Sci & Technol Coll Energy & Min Engn State Key Lab Min Disaster Prevent & Control Cofou Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Minist Sci & Technol Qingdao 266590 Peoples R China

Labyrinth seals are widely used in turbomachinery devices to prevent the leakage of fluid medium in seal structures. Under high parametrical environments, the heat generated by frictional resistance of the tur-bulence between the stator and rotor walls not only increases the temperature of the fluid and the solid, but also reduces the operation efficiency of the device. Therefore, it is necessary to implement the fluid- solid-thermal multi-field analysis of labyrinth seals and propose a comprehensive optimization design of the load-bearing and heat insulation. In the present study, inspired by a bionic snail shell, a sandwich structure with load-bearing material on both upper and lower surfaces and the heat insulation material in the middle is obtained through the genetic algorithm optimization. Then, the luid-solid-thermal multi -field analysis of the labyrinth seal with the sandwich structure is carried out. It is verified that the layer arrangement and layer thickness ratio of the bionic structure ensured the optimal performance of load -bearing and heat insulation. After changing the layer arrangement or layer thickness ratio, the compre-hensive performance of load-bearing and heat insulation is obviously weakened. The result shows that the bionic multilayer sandwich structure can be applied to the labyrinth seal to achieve optimal compre-hensive performance of load-bearing and heat insulation. (c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Labyrinthseal Bionicprototype geneticalgorithm Fluid-solid-thermalmulti-fieldanalysis Heatinsulation

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Order Optimization in Supply Chains for Small and Mediumsized International Trading Enterprises

Order Optimization in Supply Chains for Small and Mediumsize...

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作者： Xiao Yang Beijing Huayun Transportation Consulting Development Co. LTD

Inventory control is important for the sustainable development of small and medium-sized international trading enterprises and reducing inventory levels is an effective means of lowering carbon emissions. This paper analyzes the characteristics of the key links in the supply chain of small and medium-sized international trading enterprises, such as ordering, transportation, storage and sales. It considers the constraints of time-varying demand, multiple product categories, multiple order cycles, average lead time, allowable proportion of out-of-stock items, limited inventory capacity, limited liquidity and container loading capacity. We constructed an integer linear programming(ILP) model for ordering with the goal of minimizing the transportation, inventory and additional costs, based on the genetic algorithm approach to solve the problem. Taking a small-to-medium-sized international trading company as an example, the validity of the model and the fitness of the algorithm were verified. Sensitivity analysis revealed that controlling storage management costs is the predominant way to reduce the total cost.

关键词： InventoryControl SupplyChainManagement OrderQuantity IntegerLinearProgramming geneticalgorithm

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V2V Online Data Offloading Method Based on Vehicle Mobility

V2V Online Data Offloading Method Based on Vehicle Mobility

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2020国际计算机前沿大会

作者： Xianlang Hu Dafang Zhang Shizhao Zhao Guangsheng Feng Hongwu Lv Jiangsu Automation Research Institute College of Computer Science and Technology Harbin Engineering University

As people are accustomed to getting information in the vehicles,mobile data offloading through Vehicular Ad Hoc Networks(VANETs) becomes prevalent nowadays. However, the impacts caused by the vehicle mobility(such as the relative speed and direction between vehicles) have great effects on mobile data offloading. In this paper, a V2 V online data offloading method is proposed based on vehicle mobility. In this mechanism, the network service process was divided into continuous and equal-sized time slots. Data were transmitted in a multicast manner for the sake of fairness. The data offloading problem was formalized to maximize the overall satisfaction of the vehicle users. In each time slot, a genetic algorithm was used to solve the maximizing problem to obtain a mobile data offloading strategy. And then, the performance of the algorithm was enhanced by improving the algorithm. The experiment results show that vehicle mobility has a great effect on mobile data offloading, and the mobile data offloading method proposed in the paper is effective.

关键词： VehicularAdHocNetworks Mobiledataoffloading Vehiclemobility Multicastmanner geneticalgorithm

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Breast Cancer Recognition Based on BP Neural Network Optimized by Improved Genetic Algorithm

Breast Cancer Recognition Based on BP Neural Network Optimiz...

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2020国际计算机前沿大会

作者： Wenqing Xie Wenhan Li Zhifang Wang Department of Electronic Engineering Heilongjiang University

In recent years, the incidence of breast cancer is increasing and becomes one of the main causes of female death. The BP neural network optimized by standard genetic algorithm has slow convergence speed and is prone to local optimization, which makes the diagnosis accuracy of breast cancer decrease. This paper uses the improved genetic algorithm to optimize BP neural network by improving the selection operator of the standard genetic algorithm. The population diversity was first increased, and the probability of crossover and mutation was adaptively adjusted. Then deep optimization was executed on the initial weight threshold of BP network to speed up the network's convergence, and the number of iterations was reduced. Finally breast cancer diagnose was performed. The experiment results show that both the fitness of the improved genetic algorithm and the recognition accuracy of breast cancer are improved. The shortcomings of the standard genetic algorithm optimized BP neural network algorithm in breast cancer diagnosis are well solved.

关键词： Breastcancer geneticalgorithm BPneuralnetwork

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Image Segmentation Edge Detection Techniques using - Soft Computing Approaches

Image Segmentation Edge Detection Techniques using - Soft Co...

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IEEE International Conference on Soft-Computing and Network Security (ICSNS)

作者： Senthilkumar, R. Bharathi, A. Sowmya, B. Sugunamuki, K. R. SNS Coll Technol Coimbatore 641035 Tamil Nadu India Bannari Amman Inst Technol Sathyamangalam 6380401 India

ISBN: (纸本)9781538645529

Delicate Computing is a rising field that comprises of corresponding components of fluffy rationale, neural pro-cessing and developmental calculation. Delicate figuring pro-cedures have discovered wide applications. A standout amongst the most imperative applications is edge identifica-tion for picture division. The way toward parceling an ad-vanced picture into various districts or sets about pixels may be known as picture division. Edge will be a farthest point the middle of two homogeneous areas. Edge identification alludes to the way against acquainted and award aciculate discontinuities in a picture. In this paper, the assumption point is to abstraction the antecedent of bend analysis for picture division utilizing delicate registering approach in light of the Fuzzy rationale, Genetic Algorithm and Neural Network.

关键词： ImageSegmentation EdgeDetection Fuzzylogic geneticalgorithm NeuralNetwork

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Prediction of air quality index based on improved neural network

Prediction of air quality index based on improved neural net...

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International Conference on Computer Systems, Electronics and Control (ICCSEC)

作者： Wang Zhenghua Tian Zhihui Zhengzhou Univ Zhengzhou 450000 Henan Peoples R China

ISBN: (纸本)9781538635735

In order to realize the prediction of city air quality status, this paper uses the improved BP neural network to establish a prediction model of air quality index. The model uses the characteristics of nonlinear fitting approximation of BP neural network to solve the problem that air quality has many influencing factors and is nonlinear and difficult to predict. Aiming at the problem of slow convergence and easy to fall into local optimal solution of BP neural network, genetic algorithm is used to optimize. This paper takes Xuchang city as an example. Results show that the average relative error of the air quality index is 22%. The accuracy rate was 80.44%. The accuracy level of air quality is 82.5%. Compared with the BP neural network, BP neural network prediction improved has a higher accuracy. The model has certain feasibility and adaptability.

关键词： Xuchang city air quality index prediction geneticalgorithm neural network

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Survey of Genetic Algorithm Effectiveness in Intrusion Detection

Survey of Genetic Algorithm Effectiveness in Intrusion Detec...

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International Conference on Intelligent Computing and Control (I2C2)

作者： Gnanaprasanambikai, L. Munusamy, Nagarajan CMS Coll Sci & Commerce Coimbatore Tamil Nadu India

ISBN: (纸本)9781538603741

Intrusion Detection is a technology which is used to provide security to network by preserving security objectives. The Intrusion Detection undergoes many difficulties in construction while providing security to a network. Soft Computing is a research field which encompasses many methods for solving the problems in Intrusion Detection. Genetic Algorithm is a soft computing approach which is build on the concept of survival of fittest is use to solve various difficulties in intrusion detection. This paper surveys the work done by various researchers in different periods and specifies the suitable features of Genetic Algorithm to solve difficulties in intrusion detection. It also reviews the commonly used dataset in intrusion detection for research.

关键词： Softcomputing geneticalgorithm Intrusion Detection

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Application of Differential Evolution for Wind Turbine Micrositing

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MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY 2017年第2期36卷 353-366页

作者： Massan, Shafiq-Ur-Rehman Wagan, Asim Imdad Shaikh, Muhammad Mujtaba Shah, Muhammad Saleh Shaheed Zulfikar Ali Bhutto Inst Sci & Technol Karachi Pakistan Mohammad Ali Jinnah Univ Karachi Pakistan Mehran Univ Engn & Technol Dept Basic Sci & Related Studies Jamshoro Pakistan Govt Saifee Zahabi Edhi Coll Educ Karachi Pakistan

WTM (Wind Turbine Micrositing) has been an important topic of discussion in recent times. A number of Evolutionary Algorithms have been applied to the WTM problem. The DEA (Differential Evolution Algorithm) is used for a bi-constrained optimization for getting maximum power production at the least cost from a 2x2 km space. It is shown that the DEA performs comparably to the GA (Genetic Algorithms) for wind farm optimization. The optimal configuration obtained enlists the number of turbines, the cost of power generated as well as the power produced. Moreover, this study is augmented by comparison with past approaches by using the GA for the same purpose.

关键词： Wind Turbine Micro-Siting N.O. Jensen Model Heuristics Wind Turbine Optimization Differential Evolution Algorithm geneticalgorithm

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