检索结果-内蒙古大学图书馆

Selection of security system design via games of imperfect information and multi-objective genetic algorithm

RELIABILITY ENGINEERING & SYSTEM SAFETY 2013年 112卷 59-66页

作者： Lins, Isis Didier Rego, Leandro Chaves Moura, Marcio das Chagas Droguett, Enrique Lopez Univ Fed Pernambuco UFPE CTG CEERMA BR-50740550 Recife PE Brazil Univ Fed Pernambuco UFPE DEP CTG BR-50740530 Recife PE Brazil Univ Fed Pernambuco UFPE DE CCEN BR-50740540 Recife PE Brazil

This work analyzes the strategic interaction between a defender and an intelligent attacker by means of a game and reliability framework involving a multi-objective approach and imperfect information so as to support decision-makers in choosing efficiently designed security systems. A multi-objective genetic algorithm is used to determine the optimal security system's configurations representing the tradeoff between the probability of a successful defense and the acquisition and operational costs. Games with imperfect information are considered, in which the attacker has limited knowledge about the actual security system. The types of security alternatives are readily observable, but the number of redundancies actually implemented in each security subsystem is not known. The proposed methodology is applied to an illustrative example considering power transmission lines in the Northeast of Brazil, which are often targets for attackers who aims at selling the aluminum conductors. The empirical results show that the framework succeeds in handling this sort of strategic interaction. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Selection of compromise solutions Security system design Game of imperfect information multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An optimal energy-efficient clustering method in wireless sensor networks using multi-objective genetic algorithm

引用

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2013年第1期26卷 114-126页

作者： Peiravi, Ali Mashhadi, Habib Rajabi Javadi, S. Hamed Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Iran

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi-objective two-nested genetic algorithm is presented. The top level algorithm is a multi-objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two-tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA-based clustering methods and the Low Energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods. Copyright (C) 2011 John Wiley & Sons, Ltd.

关键词： clustering energy-efficient algorithm multi-objective genetic algorithm wireless sensor network

来源：评论

学校读者我要写书评

暂无评论

Optimization of an aluminum alloy anti-collision side beam hot stamping process using a multi-objective genetic algorithm

引用

ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING 2013年第3期13卷 401-411页

作者： Zhou, Jing Wang, Baoyu Lin, Jianguo Fu, Lei Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Univ London Imperial Coll Sci Technol & Med Dept Mech Engn London SW7 2AZ England

The process parameters of aluminum alloy hot stamping are essential for product forming quality. In the case of an anti-collision side beam inside car doors, the finite-element model of aluminum alloy hot stamping is set up, and the forming quality is investigated under an ordinary process condition. The blank hold force (BHF) has a significant impact on the forming quality in hot stamping. Using the Latin hypercube method to sample the simulation data points and the finite-element (FE) model to calculate the forming quality indices of the data points according to the response value of the indices, the quadratic response surfaces between the process parameter inputs and the forming quality indices are initialized. Using the multi-objective genetic algorithm NSGA-II (non-dominated sorting genetic algorithm) to optimize the responses of the process parameters, the Pareto solutions corresponding to combinations of the blank hold force and stamping speed are obtained. Finally, based on the optimal process parameters, stamping tests are carried out. Compared with the results of the stamping trial and numerical simulation, it is demonstrated that the finite-element model can predict forming defects and be consistent with the actual condition and that the optimization procedure proposed in the paper is feasible. (C) 2013 Politechnika Wroclawska. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

关键词： Aluminum alloy hot stamping Process parameters Response surface model multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

FG-HFS: A feature filter and group evolution hybrid feature selection algorithm for high-dimensional gene expression data

引用

EXPERT SYSTEMS WITH APPLICATIONS 2024年 245卷

作者： Xu, Zhaozhao Yang, Fangyuan Tang, Chaosheng Wang, Hong Wang, Shuihua Sun, Junding Zhang, Yudong Henan Polytech Univ Sch Comp Sci & Technol Jiaozuo 454000 Henan Peoples R China Henan Polytech Univ Dept Gynecol Oncol Affiliated Hosp 1 Jiaozuo 454000 Henan Peoples R China Univ Leicester Sch Comp & Math Sci Leicester LE1 7RH England Xian Jiaotong Liverpool Univ Dept Biol Sci Suzhou 215123 Jiangsu Peoples R China Southeast Univ Sch Comp Sci & Engn Nanjing 210096 Jiangsu Peoples R China

High dimensional and small samples characterize gene expression data and contain a large number of genes unrelated to disease. Feature selection improves the efficiency of disease diagnosis by selecting a small number of important genes. Unfortunately, existing algorithms do not consider the correlation between features, and search algorithms tend to fall into the local optimal solution in the feature search process. To this end, this paper proposes a feature filter and group evolution hybrid feature selection algorithm (FG-HFS) for high-dimensional gene expression data. Unlike existing algorithms, we propose using spectral clustering to group redundant features into a group. Then, we propose a redundant feature filter algorithm. According to the principle of approximate Markov blanket, grouped feature groups are filtered to delete these redundant features. Among them, filtered features are evenly divided by density according to the feature exponential strategy. Most importantly, we propose using the group evolution multi-objective genetic algorithm to search the filtered feature subsets and evaluate the candidate feature subsets according to the in-group and out-group so as to select the feature subsets with the highest accuracy and the least number. Experimental results show that the average accuracy (ACC) and Matthews correlation coefficient (MCC) indexes of the selected feature subsets (FSs) by the FG-HFS algorithm on 5 gene expression datasets are 92.76% and 88.76%, respectively, which are significantly better than the existing algorithms. In addition, the FSs and ACC/FSs indexes of the FG-HFS algorithm are also better than the existing algorithms, which fully proves the superiority of the FG- HFS algorithm. More importantly, the Wilcoxon and Friedman statistical experiments results show that the feature selection effect of FG-HFS algorithm is significantly better than that of existing algorithms, no matter in pairwise comparison or multiple comparison.

关键词： Gene expression data Feature selection Spectral clustering Symmetric uncertainty multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Study of multiobjective genetic algorithm on Taylor External Fixation

引用

IEEE ACCESS 2022年 10卷 46986-46999页

作者： Guo, Jianmin Su, Jialong Tiangong Univ Sch Comp Sci & Technol Tianjin 300387 Peoples R China

The rapid development of today's society and the rapidly increasing incidence of skeletal injuries caused by traffic and industrial accidents have led to a significant increase in the number of patients with fractures accompanied by severe soft tissue injuries, as well as an increased incidence of osteomyelitis and bone defects. Many of these patients cannot be treated with internal fixators and can only be treated with external fixators. The Taylor Bone External Fixator is the most advanced bone external fixation brace in the field of orthopedics, in which the algorithm study of the forward and backward solution of the computer software that accompanies the Taylor Bone External Fixator is the key. In this paper, we analyze the positional kinematic model based on the Taylor Spatial Frame and derive the equations for solving the six positional parameters of the fracture segment in the dynamic platform with this model. A multi-objective genetic algorithm and Pareto optimization theory are combined to propose a solution to the kinematic positive solution problem. The algorithm proposed in this paper has a minimum accuracy improvement of about 0.8 mm compared to the conventional Newton-Raphson in terms of the accuracy of the Taylor frame mounting parameters solution. Finally, based on the human tibial fracture as the test object, the healing process of the tibial fracture end was simulated using the prescription data generated by the orthopedic system, and the experimental results proved the accuracy and feasibility of the software system, and achieved the expected orthopedic effect.

关键词： Kinematics Heuristic algorithms Bones genetic algorithms Mathematical models Optimization Strain Taylor bone external fixator multi-objective genetic algorithm Pearson correlation coefficient kinematic positive solution correction prescription

来源：评论

学校读者我要写书评

暂无评论

Optimization of energy ratio, benefit to cost and greenhouses gasses using metaheuristic techniques (genetic and particular swarm algorithms) and data envelopment analysis: Recommendations for mitigation of inputs consumption (a case crop: edible onion)

引用

ENVIRONMENTAL PROGRESS & SUSTAINABLE ENERGY 2022年第6期41卷

作者： Elhami, Behzad Raeini, Mahmoud Ghasemi Nejad Taki, Morteza Marzban, Afshin Heidarisoltanabadi, Mohsen Agr Sci & Nat Resources Univ Khuzestan Dept Agr Machinery & Mechanizat Engn Mollasani Iran AREEO Agr Engn Res Dept Isfahan Agr & Nat Resources Res & Educ Ctr Esfahan Iran

The present study aimed to optimize the energy, economic, and greenhouse effects indices for edible onion production in Fereydan (85 growers), and Buin (15 growers) regions in Isfahan. Required data were collected through direct measurement, interview, and questionnaire. Total energy input was obtained before and after optimization using data envelopment analysis (DEA), multi-objective genetic algorithm (MOGA), and multi-objective particle swarm algorithm (MOPSA), and was determined as 236,335, 213,068 (8.75% saving), 125,663 (48.63% saving), and 320,657 MJ ha(-1) (35.67%), respectively. In addition, energy ratio (ER) was improved from 0.79 to 0.84, 1.81, and 0.8 using DEA, MOGA, and MOPSA, respectively. By reducing the production costs by 10.2%, 63.12%, and 29.4% using DEA, MOGA, and MOPSA, respectively, benefit-to-cost ratio (BCR) index was improved from 1.44 to 1.88, 5.21, and 1.94, respectively. Also results showed that GHG emissions were mitigated by 18.39%, 47.56%, and 27.94%, respectively. Based on the findings, MOGA showed better performance compared to DEA, and MOPSA in terms of ER, BCR, and GHG factors. Despite applying metaheuristic, and artificial intelligence methods by MOPSA, this algorithm was not able to optimize the target factors, and applied the energy, and production costs in negative status (in reverse).

关键词： data envelopment analysis multi-objective genetic algorithm multi-objective particle swarm algorithm transplanting onion

来源：评论

学校读者我要写书评

暂无评论

Ensembled local mean decomposition and genetic algorithm approach to investigate tool chatter features at higher metal removal rate

引用

JOURNAL OF VIBRATION AND CONTROL 2022年第1-2期28卷 30-44页

作者： Gupta, Pankaj Singh, Bhagat Jaypee Univ Engn & Technol Guna 473226 Madhya Pradesh India

Improper selection of cutting parameters leads to regenerative chatter and loss in productivity. In the present work, a methodology has been proposed to select a proper combination of input cutting parameters for stable turning with improved metal removal rate. Chatter signals generated during the turning of Al6061-T6 have been acquired using a microphone. Stability lobes diagram has been plotted to access the stability regime. Further, to study the effect of feed rate on stability, the recorded signals have been processed using local mean decomposition signal processing technique, followed by the selection of dominating product functions using Fourier transform. The decomposed signals have been used to evaluate the new output parameter, that is, chatter index. Prediction models of chatter index and metal removal rate have been developed. Moreover, these prediction models have been optimized using multi-objective genetic algorithm for ascertaining the optimal range of cutting parameters for stable turning with higher metal removal rate. Finally, obtained stable range has been validated by performing more experiments.

关键词： Tool chatter local mean decomposition nonstationary signal processing response surface methodology multi-objective genetic algorithm Nakagami distribution

来源：评论

学校读者我要写书评

暂无评论

multi-objective optimization of comprehensive performance in airfoil channel PCHEs using Bezier curves

引用

APPLIED THERMAL ENGINEERING 2025年 261卷

作者： Liu, Rui Zhang, Chuanliang Zhao, Bin Chen, Jiaxiang Wang, Ziyi Changsha Univ Sci & Technol Coll Energy & Power Engn Changsha 410114 Peoples R China Changsha Univ Sci & Technol Sch Elect & Informat Engn Changsha 410114 Peoples R China

The airfoil fin (AFF) Printed circuit heat exchanger (PCHE) has attracted significant attention for its excellent comprehensive performance. This study proposes an optimized design for AFF PCHE to enhance the comprehensive performance by integrating Bezier curves, computational fluid dynamics (CFD), and multi-objective genetic algorithm (MOGA). A set of 12 Bezier curve-based variables is utilized to define and control the airfoil geometry, with optimization targets set on two comprehensive evaluation criteria: the first enhanced ratio (n1) and the third enhanced ratio (n3). The MOGA-generated Pareto front reveals the evolution of AFF structures in relation to n1 and n3. Results show that as the leading and trailing edges of the AFFs become sharper and the thickness decreases, the n1 of the PCHE channel gradually increases, while n3 decreases. Conversely, as the thickness of the AFFs increases and the trailing edge shape transitions from blunt to elliptical and finally to round, n3 significantly increases while n1 decreases. Furthermore, when changes focus mainly on the leading edge of the AFFs, n3 improves without markedly affecting n1. Compared to the traditional airfoil channel, the n1 of the Fin-b channel increases by 3.1%-10.8%, demonstrating its greater suitability under identical flow rate conditions. Similarly, the n3 of the Fin-g channel is 1.4%-11.6% higher than that of the traditional airfoil channel, highlighting its superior performance under identical pumping power conditions. The present work provides a valuable reference for optimizing the design of AFF PCHEs under identical flow rate and pumping power conditions.

关键词： Airfoil fin PCHE Bezier curves Pareto front multi-objective genetic algorithm Comprehensive performance

来源：评论

学校读者我要写书评

暂无评论

Experimental investigation on the optimal control of vortex shedding of a circular cylinder with rotating rods at moderate Reynolds numbers

引用

JOURNAL OF FLUIDS AND STRUCTURES 2024年 124卷

作者： Silva, Paulo H. N. Assi, Gustavo R. S. Univ Sao Paulo Dept Naval Architecture & Ocean Engn Escola Politecn Sao Paulo Brazil

This paper presents an experimental study of fluid-structure interaction conducted at Reynolds numbers around 104 with scale models in a water channel. A circular cylinder was equipped with eight control rods positioned around its perimeter to interact with the external flow. Each rod could be driven independently to rotate about its axis. The controlled rotation of the rods interfered with the vortex generation mechanism mitigating the formation of a coherent wake. The results showed that it is possible to simultaneously reduce the mean drag and fluctuating lift forces when the rods rotate at a uniform speed or with each rod set at a different rate. A multi-objective genetic algorithm was employed to find the optimum rotation speeds. The optimum rotation produced a more significant reduction in both objectives and also consumed less energy. The contribution of each rod depends significantly on its angular position around the body and the flow conditions resulting from the upstream control rods. The present work clarifies the physical principles of the phenomenon and paves the way for the development of technological applications.

关键词： Bluff body Flow control Vortex shedding Control rods multi-objective genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Development and simulation of a gridded thermionic cathode electron gun for a high-energy photon source

引用

Nuclear Science and Techniques 2023年第3期34卷 73-81页

作者： Sheng-Chang Wang Da-Yong He Cai Meng Jing-Yi Li Zu-Sheng Zhou Jin-Dong Liu Institute of High Energy Physics Chinese Academy of SciencesBeijing 100049China

A gridded thermionic cathode electron gun was developed for the linear accelerator of the High Energy Photon Source(HEPS).An electron gun should provide a large maximum bunch charge with a wide adjustable *** satisfy these requirements,the shape of the electrode was optimized using a multi-objective genetic algorithm.A large bunch charge with an adjustable range was achieved using the grid-limited gun,the flow of which was analyzed using 3-D *** electron gun has been manufactured and tested,and the measured data of the grid-limited current and simulation results are compared and discussed in this study.

关键词： Electron gun multi-objective genetic algorithm Grid CST

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：