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检索条件"主题词=artificial bee colony algorithm"

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Distributed Path Planning of Swarm Mobile Robots*

Distributed Path Planning of Swarm Mobile Robots*

引用

Asian Control Conference

作者： Ya-Ting Lee Song-Fung Zeng Chian-Song Chiu Dept. of Beauty Science National Taichung University of Science and Technology Taichung city Taiwan Dept. of Electrical Engineering Chung-Yuan Christian University Taoyuan city Chungli Taiwan

ISBN: (纸本)9781728102634

This paper is mainly to solve the path planning problem of swarm robots. If swarm robots work in the same environment at the same time, it is necessary to have appropriate planning methods to enable individuals in the group to complete their tasks. The solution is to use the artificial bee colony algorithm for the problem of robot path planning. Because the artificial bee colony algorithm has a high efficiency to solve the optimization problem, it tries to solve the problem of robot path planning in a distributed manner. The concept of organizing robots achieves efficient task of information processing and group working in the environment.

关键词： artificial bee colony algorithm Path planning Task analysis Swarm robotics Mobile robots Particle swarm optimization

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Optimal Placement and Sizing Distributed Generation (DG) Considering Energy Storage Using ABC-QP algorithm

Optimal Placement and Sizing Distributed Generation (DG) Con...

引用

International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Luthfia Fajariyanti Rony Seto Wibowo Ontoseno Penangsang Dimas Fajar Uman Putra Ni Ketut Aryani Electrical Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia

The optimal location and capacity of distributed generation (DG) is essential for electric power systems especially to satisfy the load demand. This paper proposed the hybrid optimization method to obtain optimal location and capacity of DG considering energy storage in dynamic systems. artificial bee colony (ABC) algorithm and quadratic programming (QP) is applied. The objective functions of the proposed method minimize the cost of distribution line losses and load shedding. ABC algorithm is used to find the optimal location and capacity of DG. Then, objective functions are calculated using QP with dynamic condition of the load profile for 24 hours. Load shedding is generated based on power generation which can't satisfy the load demand. The proposed method has been implemented in a modified IEEE 30 bus.

关键词： Heuristic algorithms Power system dynamics Load shedding Linear programming artificial bee colony algorithm Distributed power generation Energy storage

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A New Method for Underdetermined Convolutive Blind Source Separation in Frequency Domain

A New Method for Underdetermined Convolutive Blind Source Se...

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International Conference on Computer Science and Network Technology

作者： Yongqiang Chen Jun Liu School of Information Science and Technology Southwest Jiaotong University

ISBN: (纸本)9781467329637

We proposed a new method for underdetermined convolutive blind source separation and permutation alignment. First, we combine the full-rank spatial covariance model with time-frequency masking to separate fourier transform coefficients of speech signals at each frequency bin, which can reduce computational complexity. After converting the variance parameters to binary masking sequences, we choose only the representative sequences for clustering. Finally, the artificial bee colony algorithm (ABC) is used to implement permutation alignment. The computer results show that the proposed method works very well compared with exising method.

关键词： Permutation indeterminacy Convolutive blind source separation artificial bee colony algorithm Full-rank spatial covariance model Time-frequency masking Phase Mask artificial bee colony algorithm Blind source separation Masking Permutation Frequency-domain analysis new methods complexity classes

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An Optimal Multilevel Thresholding based Segmentation and Classification Model for Brain Tumor Diagnosis

An Optimal Multilevel Thresholding based Segmentation and Cl...

引用

International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： B. Devanathan K. Venkatachalapathy Annamalai University Chidambaram India

ISBN: (数字)9781728163871

ISBN: (纸本)9781728163888

In recent times, Brain Tumors (BT) becomes the deadliest disease, which has increased the mortality rate over the globe. The optimal multilevel thresholding based segmentation and classification model is developed to diagnose BT. Initially, it performs preprocessing in three levels to enhance the quality of the image. Next, multi-level thresholding with artificial bee colony (ABC) algorithm is used for image segmentation. Afterward, the Gray Level Co-occurrence Matrix (GLCM) technique is employed as a feature extractor to extract a useful set of feature vectors. At last, the classification process takes place using a Support Vector Machine (SVM). A set of simulations were carried out using the benchmark Kaggle dataset and the experimental outcome is investigated under different aspects. The results demonstrate the effective diagnostic performance of the presented model with the sensitivity of 97.90%, specificity of 97.91%, and accuracy of 97.56%.

关键词： Feature extraction Tumors Magnetic resonance imaging Histograms Image segmentation Brain modeling artificial bee colony algorithm

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Modeling Smart Cloud Computing Resource Allocation in E-Learning

Modeling Smart Cloud Computing Resource Allocation in E-Lear...

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Computer Vision, Image and Deep Learning (CVIDL), International Conference on

作者： Nada M. Alhakkak Baghdad College for Economic Science University

ISBN: (数字)9781728194813

ISBN: (纸本)9781728194820

Resource allocation is one of the main factors that affect the performance of cloud computing and its applications. E-learning as one of cloud computing applications helps busy schedule learners with great facilities related to time and place, that's why e-learning had great attention over the last years. This paper introduced a smart resource allocation algorithm for e-learning systems in cloud computing environment, called Modeling Smart Cloud Computing Resource Allocation in E-Learning MS2CRAE that uses the ABC strategy in its work; ABC belongs to the swarm intelligent family. The proposed algorithm assigned resources depending on the calculated probability value for each resource.

关键词： Resource management Electronic learning Cloud computing Computational modeling Task analysis Optimization artificial bee colony algorithm

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Optimized Output Impedance for Parallel Inverters in Microgrids Utilizing ABC algorithm and Droop Control Method

Optimized Output Impedance for Parallel Inverters in Microgr...

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Global Energy Conference (GEC)

作者： Mohammed Jouda Mohammed Wadi Mohammed Salemdeeb Mehmet Rida Tur Department of Electrical and Electronics Engineering Istanbul Sabahattin Zaim University Istanbul Turkey Department of Electrical and Electronics Engineering Batman University Batman Turkey

ISBN: (数字)9798331532611

ISBN: (纸本)9798331532628

One of the highly recognized options in the efficient electrical power distribution manners of modern electrical grids involves the integration of distributed generation systems. The critical operation challenge in a microgrid is actually how to perform parallel operation for inverters that possess effective control strategies to hold stability within the system while developing appropriate power sharing. This paper describes an effective parallel inverter output impedance optimization technique based on the artificial bee colony with an advanced droop control approach. In this method, power-sharing accuracy increases considerably with the minimum range of circulating currents, thus enhancing overall stability during dynamic load transitions of the system. Extensive simulation results confirm the effectiveness of optimized droop control parameters in substantially improving stable and efficient power distribution within microgrid applications.

关键词： Simulation Microgrids Power system stability Electrical power distribution artificial bee colony algorithm Inverters Stability analysis Impedance Reliability Optimization

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Identification and nonlinear model predictive control of MIMO Hammerstein system with constraints

Identification and nonlinear model predictive control of MIM...

引用

第26届中国过程控制会议（CPCC2015）

作者： Li Dazi Jia Yuanxin Qibing Jin College of Information Science and Technology Beijing University of Chemical Technology

This paper is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and Sub-model Method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.

关键词： Model predictive control system identification constrained systems Hammerstein model Polymerization reactor artificial bee colony algorithm

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Research on Optimization of Microbial Metabolic Network Model and its Application in Metabolite Synthesis

Research on Optimization of Microbial Metabolic Network Mode...

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Computer Science and Blockchain (CCSB), International Conference on

作者： Yuchen Xiang College of Life Science and Medicine Zhejiang Sci-Tech University Hangzhou Zhejiang China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

Microbial engineering has entered a new era, and the optimization of microbial metabolic network modeling and its application to metabolite synthesis has entered a new phase. Based on the EUC-GSMM concept centering on enzyme utilization constraints, it is necessary to make optimization proposals that meet the needs of metabolite synthesis in microbial engineering. Based on the dynamic evolution of the development of the microbial metabolic network model, the theoretical analysis framework of the improved ABC algorithm is constructed according to the internal logic of multi-objective optimization, and the scheduling mechanism generated by the search and update mechanism involving enzyme set function and fitness function is explained. In addition, the possibility of optimizing the microbial metabolic network model is analyzed from the parameter change and practice of EUC-GSMM. The purpose of developing EUC-GSMM is to provide a metabolite synthesis scheme that meets the expected standard for microbial engineering. We are committed to improving the quality of the program and program satisfaction. Therefore, we took a series of measures, including strengthening EUC-GSMM control based on the enzyme utilization constraint quality internal loop, constructing an interaction and feedback mechanism between the enzyme set function and enzyme utilization constraint quality perception, and establishing the EUC-GSMM and metabolite synthesis evaluation system of the program, thereby promoting the high-quality development of the field. Finally, it promotes microbial engineering, microbial metabolic network model optimization, and its application in metabolite synthesis.

关键词： Enzymes Analytical models Biological system modeling Dynamic scheduling artificial bee colony algorithm Biochemistry Logic Proposals Optimization Standards

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Finding Optimum Location for a Mobile Aerial Base Station with Harmony Search algorithm

Finding Optimum Location for a Mobile Aerial Base Station wi...

引用

International Conference on Computer Science and Engineering (UBMK)

作者： Serhat Celil İleri Selçuk Aslan Sercan Demirci Bilgisayar Mühendisliği Ondokuz Mayıs Üniversitesi Samsun Türkiye Bilgisayar Mühendisliği Nevşehir Hacı Bektaş Veli Üniversitesi Nevşehir Türkiye

ISBN: (数字)9781728175652

ISBN: (纸本)9781728175669

In recent years, unmanned aerial vehicles (UAVs) with the increased flying times, improved command-control systems and carrying capacities have been used successfully for the various military and commerical projects. However, the time and qualities of the services provided by the mentioned vehicles are directly related with the locations determined previously or found instantly. In this study, an appropriate location of an UAV equipped with the base station capability for serving to the users is tried to be determined by utilizing from the Harmony Search (HS) algorithm. The results obtained by the HS algorithm are also compared with the results obtained by the PSO and ABC algorithms. Comparative results show that the mobile base station is capable of serving more successfully when its location is determined with the HS algorithm compared to the locations determined by the PSO or ABC algorithms.

关键词： Dogs Base stations Computer science Unmanned aerial vehicles artificial bee colony algorithm Nanoelectromechanical systems Computational modeling

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Research on Media Data Analysis System Based on Big Data Technology

Research on Media Data Analysis System Based on Big Data Tec...

引用

Information Technology and Computer Application (ITCA), International Conference on

作者： Qiang Lin Xiaohan Gao Yang Guo Xilin Zhang Dalian University of Science and Technology

The system designed in the paper uses the method of collecting Twitter tweets to test the collection system. The specific collection content is tweet collection based on keywords, testing the collection rate of tweets and system stability. In the test, the bandwidth of each collection node is limited by using bandwidth limiting software to simulate different network agent environments. The collection system in different environments is tested by changing the collection task and the bandwidth limit of each collection node. The results prove that the algorithm proposed in the paper can significantly improve the evaluation accuracy of media data, and has a significant effect on analyzing the collected objects.

关键词： Scheduling algorithms Social networking (online) Software algorithms Bandwidth Media artificial bee colony algorithm Stability analysis

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