检索结果-内蒙古大学图书馆

Modeling and Parameter Extraction of OFET Compact Models Using Metaheuristics-Based Approach

IEEE ACCESS 2019年 7卷 180438-180450页

作者： Akkan, Nihat Altun, Mustafa Sedef, Herman Yildiz Tech Univ Elect & Commun Engn Dept TR-34220 Istanbul Turkey Istanbul Tech Univ Elect & Commun Engn Dept TR-34469 Istanbul Turkey

Research on the fabrication of organic field effect transistors (OFETs) has been dramatically increased in the last decade, considering their lightweight and flexible structure as well as their practical and low-cost production. In the next step of fabrication, building compact models and developing parameter extraction methods have critical importance in designing electronic circuits using fabricated OFETs. In this paper, we propose a parameter extraction approach which benefits from the power of metaheuristics. Although direct extraction tools offer analytical solutions in successive steps to extract model parameters, metaheuristics-based global optimization methods can find all parameters at once by exploring a wide range of parameters. Direct extraction tools are cumbersome and need human expertise. On the other hand, global optimization methods are very flexible, adaptive and can be automated as parameter extraction tools of any compact model. In this study, we introduce three different global optimization algorithms, namely, a genetic algorithm (GA), a hybrid artificial bee colony (h-ABC) algorithm, and bacterial foraging optimization (BFO) algorithm, for the parameter extraction. To the best of our knowledge, h-ABC and BFO algorithms have been used for the first time in extracting parameters of OFET compact models. We use two OFET compact models developed by Estrada et al. and Marinov et al. for two different datasets of OFET transistors, both having pentacene as organic semiconductor. While one of the dataset of transistor (T1) is available in literature, the dataset of the other transistor fabricated in our laboratory (T2) is generated as a new dataset. In order to tune control parameters of the developed algorithms, Taguchi's orthogonal experimental design (OED) method is used. Experimental results show that the proposed metaheuristics-based approach can extract model parameters successfully and can perform better than direct extraction methods. The studie

关键词： Compact models organic field effect transistor (ofet) parameter extraction artificial bee colony algorithm bacterial foraging algorithm genetic algorithm Taguchi method

来源：评论

学校读者我要写书评

暂无评论

A metaheuristic solution approach to capacitied vehicle routing and network optimization

引用

ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH 2019年第3期22卷 727-735页

作者： Simsir, Fuat Ekmekci, Dursun Karabuk Univ Ind Engn Dept Karabuk Turkey Karabuk Univ Comp Engn Dept Karabuk Turkey

The vehicle routing problem (VRP) is one of the problem types that are sought after for a long time by trying out different techniques and attracting attention in terms of optimization. In most VRP types, route cost is associated with distance, and a shorter distance solution is considered a more successful solution. While the shortest distance goal provides significant advantages in terms of cost and time to businesses, this makes it attractive for further research. When examining the types of problems having different directions and areas devised from different points of view on vehicle routing, it can be said that the closest approach to practical application is the vehicle routing problem with simultaneous delivery and pickup (VRPSDP). In this study, a solution proposal is presented for the VRPSDP using the artificial bee colony (ABC) algorithm and the application is tested with the benchmark problem data sets commonly used for VRPSDP in the literature. When the results are compared with the least cost route solutions in the literature, it is observed that despite the few parameters, the proposed method can produce low-cost solutions very close to the most successful solutions in the literature. (C) 2019 Karabuk University. Publishing services by Elsevier B.V.

关键词： Vehicle routing problem Optimization artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Joint Optimization Method of Airborne MIMO Radar Track and Radiated Power Based on Mutual Information

引用

IEEE ACCESS 2020年 8卷 136278-136295页

作者： Fan, Xiangyu Bai, Peng Wang, Hongwei Zhang, Jiaqiang Li, Huanyu Air Force Engn Univ Air Traff Control & Nav Coll Xian 710051 Peoples R China Air Force Engn Univ Shaanxi Prov Lab Metasynth Elect & Informat Syst Xian 710051 Peoples R China Air Force Engn Univ Coll Aeronaut Engn Xian 710051 Peoples R China

The mutual information (MI) is used as the target function to jointly optimize the space trajectory and radiated power of the airborne MIMO radar. By adjusting the space position of the radar and radiating energy in real time, the detection efficiency of the MIMO radar is improved. Firstly, the cooperative detection model of aviation swarm MIMO radar is constructed to quantitatively describe the relationship between radar position and radiated power parameters and echo. Therefore, the MI between the transmitted signal and the received signal at the same time is derived, and the MI of the radar echo at the current time and the next time is derived. Maximizing the amount of MI sent and received signals can improve the amount of information detected, and minimizing the amount of MI at adjacent moments can improve the quality of information. This paper designs a time-sharing optimization algorithm, and improves the artificial bee colony algorithm (ABC) to optimize the above two MI to achieve real-time adjustment of radar position and power. Through simulation verification and algorithm comparison, the advantages of this algorithm are reflected.

关键词： MIMO radar Optimization Radar detection Aircraft Radar tracking Radar cross-sections Mutual information airborne MIMO radar space trajectory radiated power artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Low-carbon Marine Logistics Network Design under Double Uncertainty of Market Demand and Carbon Trading Price

引用

JOURNAL OF COASTAL RESEARCH 2019年第Sup94期35卷 30-39页

作者： Wang, Wei Ren, Ying Bian, Wenliang Jia, Xinyue Beijing Jiaotong Univ Sch Econ & Management Beijing 100044 Peoples R China

This paper discusses the low-carbon marine logistics network design problem under the uncertainty of market demand and carbon emission price, and aims at the minimum cost of shipping logistics network operation (including carbon emission cost), and constructs a three-level marine logistics network site-distribution model based on scenario. The problem is transformed into an unconstrained optimization problem by the penalty function method, and the artificial bee colony algorithm (ABC) is used to solve the model. The study found that the moderate fluctuation of demand is conducive to the integration effect of the marine logistics network, which reduces the total cost of the logistics network. Finally, the validity of the model is verified by an example analysis of a domestic industrial product manufacturer.

关键词： Carbon trade low-carbon marine logistics logistics network design penalty function artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

High-efficient energy saving processing of big data of communication under mobile cloud computing

引用

International Journal of Modeling, Simulation, and Scientific Computing 2019年第4期10卷 96-106页

作者： Yazhen Liu Pengfei Fan Jiyang Zhu Liping Wen Xiongfei Fan Information Communication Operation and Maintenance Center Information and Communication Branch State Grid Inner Mongolia Eastern Electric Power Co. Ltd.HohhotInner Mongolia Autonomous Region 010020P.R.China Hohhot Power Supply Bureau Inner Mongolia Power(Group)Co.Ltd.HohhotInner Mongolia Autonomous Region 010020P.R.China Training Center Inner Mongolia Power(Group)Co.Ltd.HohhotInner Mongolia Autonomous Region 010020P.R.China

From 21st century,it is hard for traditional storage and algorithm to provide service with high quality because of big data of communication which grows ***,cloud computing technology with relatively low cost of hardware facilities is ***,to guarantee the quality of service in the situation of the rapid growth of data volume,the energy consumption cost of cloud computing begins to exceed the hardware *** order to solve the problems mentioned above,this study briefly introduced the virtual machine and its energy consumption model in the mobile cloud environment,introduced the basic principle of the virtual machine migration strategy based on the artificial bee colony algorithm and then simulated the performance of processing strategy to big data of communication based on artificial bee colony algorithm in mobile cloud computing environment by CloudSim3.0 software,which was compared with the performance of two algorithms,resource management(RM)and genetic algorithm(GA).The results showed that the power consumption of the migration strategy based on the artificial bee colony algorithm was lower than the other two strategies,and there were fewer failed virtual machines under the same number of requests,which meant that the service quality was higher.

关键词： Mobile cloud computing big data processing artificial bee colony algorithm energy saving

来源：评论

学校读者我要写书评

暂无评论

Heuristic Optimization of Virtual Inertia Control in Grid-Connected Wind Energy Conversion Systems for Frequency Support in a Restructured Environment

引用

ENERGIES 2020年第3期13卷 564-564页

作者： Aluko, Anuoluwapo Oluwatobiloba Dorrell, David George Pillay Carpanen, Rudiren Ojo, Evan E. Univ KwaZulu Natal Discipline Elect Elect & Comp Engn ZA-4041 Durban KwaZulu Natal South Africa Durban Univ Technol Dept Elect Power Engn ZA-4000 Durban KwaZulu Natal South Africa

In the work reported in this paper, a novel application of the artificial bee colony algorithm is used to implement a virtual inertia control strategy for grid-connected wind energy conversion systems. The proposed control strategy introduces a new heuristic optimization technique that uses the artificial bee colony (ABC) algorithm to calculate the optimal gain value of an additional derivative control loop added to the control scheme of the machine side converter in a wind energy system to enable wind farms to participate in frequency control as specified by recent grid codes. This helps to minimize the frequency deviations, reduce active power deviation in the system, and increase the penetration level of wind energy in power systems. The study was performed in a restructured power system environment. The proposed control scheme and its robustness were evaluated using load-frequency analysis for three real-life transaction scenarios that can occur in an interconnected open-energy market and the validation was carried out using eigenvalue analysis. The results in this study show that the optimal gain of the proposed controller reduces the frequency deviations and improves stability and overall performance of the system.

关键词： artificial bee colony algorithm deregulation load frequency control heuristic optimization power system stability wind energy

来源：评论

学校读者我要写书评

暂无评论

An optimization model for container inventory management

引用

ANNALS OF OPERATIONS RESEARCH 2019年第1-2期273卷 433-453页

作者： Poo, Mark Ching-Pong Yip, Tsz Leung Liverpool John Moores Univ Liverpool Logist Offshore & Marine Res Inst Liverpool Merseyside England Hong Kong Polytech Univ Fac Business Dept Logist & Maritime Studies Hung Hom Hong Kong Peoples R China

This paper formulates the empty container repositioning (ECR) problem, which is one of the most important issues in the container shipping industry, by running a model to generate the service route of feeder shipping in a dynamic environment. The objective is to reduce the disequilibrium of laden and empty containers. This paper first provides a literature review with the emphasis on the shipping scheduling and modelling of ECR. Second, a network model has been designed to find the optimum size of ship servicing a particular region. A simply ECR policy is tested to demonstrate an essential impact on the profit of a container transport system. With the aid of this heuristic shipping model, ECR is integrated with the tramp ship routing problem under dynamic condition.

关键词： Empty container repositioning Container inventory management artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Integrated Optimization Approach of Hybrid Flow-Shop Scheduling Based on Process Set

引用

IEEE ACCESS 2020年 8卷 223782-223796页

作者： Li, Xixing Tang, Hongtao Yang, Zhipeng Wu, Rui Luo, Yabo Hubei Univ Technol Sch Mech Engn Hubei Key Lab Modern Mfg & Qual Engn Wuhan 430068 Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Hubei Key Lab Digital Mfg Wuhan 430070 Peoples R China

Considering that process planning and production scheduling are independent of each other in a hybrid flow-shop, this study categorizes the process route into parallel process-set, batch set and unordered process-set, and builds a multi-objective optimization model to minimize the maximum completion time and the minimum processing cost. An improved artificial bee colony algorithm has been developed to solve the model. A segmented decoding method based on the insertion principle and the release time of the predecessor process is proposed to effectively use the idle time of the machine. A dynamic triggering neighborhood mechanism is introduced to enhance the local searchabilit of the algorithm. Finally, the feasibility and effectiveness of this algorithm to solve such problems are verified via simulation experiments.

关键词： Job shop scheduling Hafnium Batch production systems artificial bee colony algorithm Heuristic algorithms Manufacturing Optimization Process planning production scheduling hybrid flow-shop improved artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

An Efficient Universal bee colony Optimization algorithm

引用

TEHNICKI VJESNIK-TECHNICAL GAZETTE 2020年第1期27卷 320-332页

作者： Han, Xuming Wang, Yidan Cai, Chen Wang, Limin Hou, Xiuping Wang, Linlin Changchun Univ Technol Sch Comp Sci & Engn Changchun 130012 Peoples R China North China Elect Power Univ Sch Control & Comp Engn Changchun 130012 Peoples R China Jilin Univ Finance & Econ Sch Management Sci & Informat Engn Changchun 130117 Peoples R China

The artificial bee colony algorithm is a global optimization algorithm. The artificial bee colony optimization algorithm is easy to fall into local optimal. We proposed an efficient universal bee colony optimization algorithm (EUBCOA). The algorithm adds the search factor u and the selection strategy of the onlooker bees based on local optimal solution. In order to realize the controllability of algorithm search ability, the search factor u is introduced to improve the global search range and local search range. In the early stage of the iteration, the search scope is expanded and the convergence rate is increased. In the latter part of the iteration, the algorithm uses the selection strategy to improve the algorithm accuracy and convergence rate. We select ten benchmark functions to testify the performance of the algorithm. Experimental results show that the EUBCOA algorithm effectively improves the convergence speed and convergence accuracy of the ABC algorithm.

关键词： artificial bee colony algorithm fitness search factor universal optimization

来源：评论

学校读者我要写书评

暂无评论

A novel machine learning technique for computer-aided diagnosis

引用

ENGINEERING APPLICATIONS OF artificial INTELLIGENCE 2020年 92卷 103627-103627页

作者： Tang, Cheng Ji, Junkai Tang, Yajiao Gao, Shangce Tang, Zheng Todo, Yuki Univ Toyama Fac Engn Toyama 9308555 Japan Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Peoples R China Cent South Univ Forestry & Technol Coll Econ Changsha 410004 Peoples R China Kanazawa Univ Fac Elect & Comp Engn Kanazawa Ishikawa 9201192 Japan

The primary motivation of this paper is twofold: first, to employ a heuristic optimization algorithm to optimize the dendritic neuron model (DNM) and second, to design a tidy visual classifier for computer-aided diagnosis that can be easily implemented on a hardware system. Considering that the backpropagation (BP) algorithm is sensitive to the initial conditions and can easily fall into local minima, we propose an evolutionary dendritic neuron model (EDNM), which is optimized by the gbest-guided artificial bee colony (GABC) algorithm. The experiments are performed on the Liver Disorders Data Set, the Wisconsin Breast Cancer Data Set, the Haberman's Survival Data Set, the Diabetic Retinopathy Debrecen Data Set and Hepatitis Data Set, and the effectiveness of our model was rigorously validated in terms of the classification accuracy, the sensitivity, the specificity, the F_measure, Cohen's Kappa, the area under the receiver operating characteristic curve (AUC), convergence speed and the statistical analysis of the Wilcoxon signed-rank test. Moreover, after training, the EDNM can simplify its neural structure by removing redundant synapses and superfluous dendrites by the neuronal pruning mechanism. Finally, the simplified structural morphology of the EDNM can be replaced by a logic circuit (LC) without sacrificing accuracy. It is worth emphasizing that once implemented by an LC, the model has a significant advantage over other classifiers in terms of speed when handling big data. Consequently, our proposed model can serve as an efficient medical classifier with excellent performance.

关键词： Computer-aided diagnosis artificial neural network artificial bee colony algorithm Pruning Logic circuit

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：