检索结果-内蒙古大学图书馆

Toward improved mechanical, tribological, corrosion and in-vitro bioactivity properties of mixed oxide nanotubes on Ti-6Al-7Nb implant using multi-objective pso

引用

JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS 2017年 69卷 1-18页

作者： Rafieerad, A. R. Bushroa, A. R. Nasiri-Tabrizi, B. Kaboli, S. H. A. Khanahmadi, S. Amiri, Ahmad Vadivelu, J. Yusof, F. Basirun, W. J. Wasa, K. Univ Malaya Fac Engn Dept Mech Engn Kuala Lumpur 50603 Malaysia Univ Malaya Ctr Adv Mfg & Mat Proc AMMP Kuala Lumpur 50603 Malaysia Univ UCLA Fac Engn Dept Mech Engn Los Angeles CA 90032 USA Univ Calif Los Angeles Dept Mech & Aerosp Engn Los Angeles CA 90095 USA Islamic Azad Univ Najafabad Branch Mat Engn Dept Adv Mat Res Ctr Najafabad Isfahan Iran Univ Malaya UM Power Energy Dedicated Adv Ctr Kuala Lumpur Malaysia Univ Munster Inst Plant Biotechnol & Biol Schlosspl 8 D-48143 Munster Germany Univ Malaya Fac Med Dept Med Microbiol Kuala Lumpur 50603 Malaysia Univ Malaya Fac Sci Dept Chem Kuala Lumpur 50603 Malaysia Yokohama City Univ Grad Sch Nanobio Sci Yokohama Kanagawa 2360027 Japan

Recently, the robust optimization and prediction models have been highly noticed in district of surface engineering and coating techniques to obtain the highest possible output values through least trial and error experiments. Besides, due to necessity of finding the optimum value of dependent variables, the multi-objective metaheuristic models have been proposed to optimize various processes. Herein, oriented mixed oxide nanotubular arrays were grown on Ti-6Al-7Nb (Ti67) implant using physical vapor deposition magnetron sputtering (PVDMS) designed by Taguchi and following electrochemical anodization. The obtained adhesion strength and hardness of Ti67/Nb were modeled by particle swarm optimization (pso) to predict the outputs performance. According to developed models, multi-objective pso (MOpso) run aimed at finding PVDMS inputs to maximize current outputs simultaneously. The provided sputtering parameters were applied as validation experiment and resulted in higher adhesion strength and hardness of interfaced layer with Ti67. The as-deposited Nb layer before and after optimization were anodized in fluoride-base electrolyte for 300 min. To crystallize the coatings, the anodically grown mixed oxide TiO2-Nb2O5-Al2O3 nanotubes were annealed at 440 degrees C for 30 min. From the FESEM observations, the optimized adhesive Nb interlayer led to further homogeneity of mixed nanotube arrays. As a result of this surface modification, the anodized sample after annealing showed the highest mechanical, tribological, corrosion resistant and in-vitro bioactivity properties, where a thick bone-like apatite layer was formed on the mixed oxide nanotubes surface within 10 days immersion in simulated body fluid (SBF) after applied MOpso. The novel results of this study can be effective in optimizing a variety of the surface properties of the nanostructured implants.

关键词： multi-objective pso PVD magnetron sputtering Anodic mixed oxide nanotubes Mechanical properties Tribo/corrosion resistance In-vitro bioactivity

来源：评论

学校读者我要写书评

暂无评论

multi-objective pso based feature selection for intrusion detection in IoT based wireless sensor networks

引用

OPTIK 2023年 273卷

作者： Subramani, Shalini Selvi, M. Vellore Inst Technol Sch Comp Sci & Engn Vellore India

Internet of Things (IoT) utilization is increasing every day in both industry and other applications recently. However, the IoT communication is under security threats from malicious users. In spite of the availability of multiple security solutions in the literature, the intruders are targeting the IoT sensor networks through multiple type of attacks. Therefore, an effective Intrusion Detection System (IDS) is required for safe-guarding the communication in the IoT environment. For this purpose, we propose an Intelligent Intrusion Detection System for detecting intruders in IoT based wireless sensor networks so that it is possible to handle such intrusions. For the development of this intelligent IDS, we propose a rule and multi-objective pso based feature selection algorithm and also propose an intelligent rule based enhanced multiclass Support Vector Machines classi-fication algorithm for detecting the intruders more accurately. From the experiments conducted in this work by using KDD'99 Cup data set and CIDD data set for evaluation, it is proved that the proposed IDS is able to capture the intruders more accurately by enhancing the detection accu-racy and also by reducing the false positive rate.

关键词： Intrusion detection system Feature selection Particle swarm optimization Enhanced multiclass SVM multi-objective pso

来源：评论

学校读者我要写书评

暂无评论

A multi-objective pso Strategy for Energy-efficient Ad-Hoc Networking

A Multi-objective PSO Strategy for Energy-efficient Ad-Hoc N...

引用

IEEE International Conference on Systems, Man and Cybernetics (SMC)

作者： Olascuaga-Cabrera, J. Guadalupe Lopez-Mellado, Ernesto Mendez-Vazquez, Andres CINVESTAV Unidad Guadalajara Col El Bajio 45015 Zapopan Jal Mexico

ISBN: (纸本)9781457706530

In this work, virtual backbone generation in ad-hoc networks under constraints of limited energy resources is addressed through a novel global optimization method. It is based on the maximal independent set approach which is stated as a multi-objective optimization problem to represent the different functional constraints of the backbone generation. A discrete version of a Particle Swarm Optimization strategy is proposed for searching Pareto optimal solutions under the multi-objective cost function. Finally, a diversity-based indicator is applied to prove that the Pareto frontier has a uniform distribution in the non-dominated solutions.

关键词： Ad-hoc networking multi-objective pso Energy-efficient Maximal independent set

来源：评论

学校读者我要写书评

暂无评论

multi-objective pso based optimal placement of solar power DG in radial distribution system

引用

JOURNAL OF ELECTRICAL SYSTEMS 2017年第2期13卷 322-331页

作者： Kumar, Mahesh Nallagownden, Perumal Elamvazuthi, Irraivan Univ Teknol PETRONAS Bandar Seri Iskandar Dept Elect & Elect Engn Perak Darul Ridzuan Malaysia Mehran Univ Engn & Technol Jamshoro Dept Elect Engn Sindh Pakistan

Ever increasing trend of electricity demand, fossil fuel depletion and environmental issues request the integration of renewable energy into the distribution system. The optimal planning of renewable distributed generation (DG) is much essential for ensuring maximum benefits. Hence, this paper proposes the optimal placement of probabilistic based solar power DG into the distribution system. The two objective functions such as power loss reduction and voltage stability index improvement are optimized. The power balance and voltage limits are kept as constraints of the problem. The non-sorting pareto-front based multi-objective particle swarm optimization (MOpso) technique is proposed on standard IEEE 33 radial distribution test system.

关键词： Distributed generation solar PV module distribution system multi-objective pso

来源：评论

学校读者我要写书评

暂无评论

Optimizing Effort and Time Parameters of COCOMO II Estimation using Fuzzy multi-objective pso 4

Optimizing Effort and Time Parameters of COCOMO II Estimatio...

引用

4th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)

作者： Langsari, Kholed Sarno, Riyanarto Inst Teknol Sepuluh Nopember Dept Informat Engn Surabaya Indonesia

ISBN: (纸本)9781538605493

The estimation of software effort is an essential and crucial activity for the software development life cycle. Software effort estimation is a challenge that often appears on the project of making a software. A poor estimate will produce result in a worse project management. Various software cost estimation model has been introduced to resolve this problem. Constructive Cost Model II (COCOMO II Model) create large extent most considerable and broadly used as model for cost estimation. To estimate the effort and the development time of a software project, COCOMO II model uses cost drivers, scale factors and line of code. However, the model is still lacking in terms of accuracy both in effort and development time estimation. In this study, we do investigate the influence of components and attributes to achieve new better accuracy improvement on COCOMO II model. And we introduced the use of Gaussian Membership Function (GMF) Fuzzy Logic and multi-objective Particle Swarm Optimization method (MOpso) algorithms in calibrating and optimizing the COCOMO II model parameters. The proposed method is applied on Nasa93 dataset. The experiment result of proposed method able to reduce error down to 11.891% and 8.082% from the perspective of COCOMO II model. The method has achieved better results than those of previous researches and deals proficient with inexplicit data input and further improve reliability of the estimation method.

关键词： COCOMO II Model Effort Estimation Time Development Estimation Fuzzy multi-objective pso Optimizaton

来源：评论

学校读者我要写书评

暂无评论

A multi-objective pso approach of mining association rules for affective design based on online customer reviews

引用

JOURNAL OF ENGINEERING DESIGN 2018年第7期29卷 381-403页

作者： Jiang, Huimin Kwong, C. K. Park, W. Y. Yu, K. M. Shenzhen Univ Coll Management Shenzhen Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

Affective design is an important aspect of new product development that can enhance customer satisfaction of new products. Previous studies generally conducted customer surveys based on questionnaires and interviews to collect customers' views and preferences of affective design of products. However, the process could be time-consuming and the survey data does not contain much sentiment expression. Presently, a large number of online customer reviews on products can be found on various websites that contain rich information of customer opinions and expectations. However, the generation of useful information based on online customer reviews for affective design has not been addressed in previous studies. In this paper, a methodology for generating association rules for supporting affective design based on online customer reviews is proposed which mainly involves opinion mining of affective dimensions from online customer reviews and association rule mining based on multi-objective particle swarm optimisation (pso). Opinion mining is adopted to analyze online reviews and conduct sentiment analysis for affective dimensions. Based on the mined information and morphological analysis of products, a multi-objective pso approach is proposed to generate association rules that depict the relationships between affective dimensions and design attributes. A case study was conducted to illustrate the proposed methodology.

关键词： Affective design opinion mining association rule mining multi-objective pso

来源：评论

学校读者我要写书评

暂无评论

Distribution Network Expansion Planning Based on multi-objective pso Algorithm

引用

Energy and Power Engineering 2013年第4期5卷 975-979页

作者： Chunyu Zhang Yi Ding Qiuwei Wu Qi Wang Jacob Φstergaard Center for Electric Power and Energy Technical University of DenmarkCopenhagenDenmark

This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (pso). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective pso algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective pso have been verified by the 18-node typical system.

关键词： Distribution Network Expansion Planning Two-phase multi-objective pso

来源：评论

学校读者我要写书评

暂无评论

pso Based multi-objective Approach for Controlling PID Controller

引用

Computers, Materials & Continua 2022年第6期71卷 4409-4423页

作者： Harsh Goud Prakash Chandra Sharma Kashif Nisar Ag.Asri Ag.Ibrahim Muhammad Reazul Haque Narendra Singh Yadav Pankaj Swarnkar Manoj Gupta Laxmi Chand Indian Institute of Information Technology NagpurIndia School of Computing&Information Technology Manipal UniversityJaipur(Rajasthan)India Faculty of Computing and Informatics University Malaysia SabahJalan UMS88400Kota Kinabalu SabahMalaysia Faculty of Computing&Informatics Multimedia UniversityPersiaran Multimedia63100CyberjayaSelangorMalaysia Maulana Azad National Institute of Technology BhopalIndia Department of Electronics and Communication Engineering JECRC UniversityJaipur(Rajasthan)India

CSTR(Continuous stirred tank reactor)is employed in process control and chemical industries to improve response characteristics and system *** has a highly nonlinear characteristic that includes complexities in its control and *** performance is compassionate to change in system parameterswhich need more effort for planning a significant controller for *** reactor temperature changes in either direction from the defined reference *** is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature,and deviation from reference values may cause degradation of biomass *** and implementation of an appropriate adaptive controller for such a nonlinear system are *** this paper,a conventional Proportional Integral Derivative(PID)controller is *** conventional techniques to deal with constraints suffer severe limitations like it has fixed controller ***,A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller’s *** the proposed technique,PID parameters are tuned by Particle Swarm Optimization(pso).It is not easy to choose the suitable objective function to design a PID controller using pso to get an optimal *** this article,a multi-objective function is proposed for pso based controller design of CSTR.

关键词： Particle swarm optimization multi-objective pso continuous stirred tank reactor proportional integral derivative controller

来源：评论

学校读者我要写书评

暂无评论

An Improved multi-objective Bare-Bones pso for Optimal Design of Solar Dish Stirling Engine Systems

An Improved Multi-objective Bare-Bones PSO for Optimal Desig...

引用

International Conference on Life System Modeling and Simulation (LSMS) / International Conference on Intelligent Computing for Sustainable Energy and Environment (ICSEE)

作者： Niu, Qun Sun, Ziyuan Hua, Dandan Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200071 Peoples R China

ISBN: (纸本)9789811063640;9789811063633

An improved bare-bones multi-objective particle swarm optimization, namely IMOBBpso is proposed to optimize the solar-dish Stirling engine systems. A new simple strategy for updating particle's velocity is developed based on the conventional bare-bones pso, aiming to enhance the diversity of the solutions and accelerate the convergence rate. In order to test the effectiveness of IMOBBpso, four benchmarks are used. Compared with the non-dominated sorting genetic algorithm-II (NSGAII) and multi-objective particle swarm optimization algorithm (MOpso), it is revealed that IMOBBpso can quickly converge to the true Pareto front and efficiently solve practical problems. IMOBBpso is then used to solve the design of the solar-dish Stirling engine. It is shown that IMOBBpso obtains the best optimization results than NSGAII and MOpso. It further achieves significant improvements 25.6102% to 29.2926% in terms of the output power and entropy generation rate when it is compared with existing results in the literature.

关键词： Stirling engine Solar dish multi-objective pso Bare bones

来源：评论

学校读者我要写书评

暂无评论

Constrained multi-objective particle swarm optimization for bistatic RFID network planning with distributed antennas

引用

SWARM AND EVOLUTIONARY COMPUTATION 2025年 94卷

作者： Wang, Yamin Ma, Shuai Li, Yuan Qian, Hongyu Jia, Qianfan Xiao, Shanpeng Huang, Yuhong China Mobile Res Inst Beijing 100053 Peoples R China

Radio Frequency Identification (RFID) network planning (RNP) is crucial for optimizing network performance by setting system parameters. The new bistatic RFID architecture with a distributed antenna system (DAS) offers advantages for the passive Internet of Things (IoT). It separates transmission and reception to minimize self-interference and extend uplink communication range, while using distributed antennas for broader coverage. Bistatic DAS RNP differs from monostatic in various aspects. Monostatic RNP focuses on factors like reader number, location, and power, while bistatic DAS RNP involves more parameters, including antenna and device numbers, locations, and interconnections. Coverage and interference are more complex, and practical planning faces constraints on antenna ports and feeder line length. Consequently, bistatic DAS RFID network planning (BDRNP) problems are novel, complex, high-dimensional, and constrained, making them relatively unexplored and highly challenging. This paper analyzes bistatic DAS RFID network coverage and interference, and proposes a mathematical model for BDRNP problems. A modified multi-objective discrete particle optimization (M2Dpso) algorithm is introduced, incorporating a modified k-means clustering method to group antennas, which ensures satisfaction constraints and reduces decision variable dimensionality from 4|CS| + |CS|2 to 4|CS| to 4|CS| where |CS| is the problem size. Redundant SDRs/carrier emitters are dynamically eliminated based on global best solution set changes. Experimental results show that M2Dpso algorithm significantly outperforms three existing popular algorithms - nondominated sorting genetic algorithm II (NSGAII), discrete particle swarm optimization (Dpso), and multi-objective evolutionary algorithm based on decomposition (MOEAD) - by 265%, 361%, and 726% respectively, in average inverted generational distance (IGD) metrics.

关键词： Bistatic network planning Distributed antenna system multi-objective pso Modified k-means clustering Dynamic redundancy elimination

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：