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Enhanced fireworks algorithm based on particle swarm optimization and reverse learning of small-hole imaging experiment

Enhanced fireworks algorithm based on particle swarm optimiz...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Jiao, Jiao Li, Jun Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Since the traditional fireworks algorithm (FWA) is easy to fall into local optimization and has insufficient global optimization capability and low optimization accuracy, this paper proposes the enhanced fireworks algorithm (EFWA-SI) based on particle swarm optimization and small-hole imaging reverse learning. First, a dynamic explosion amplitude mechanism based on the evolution speed of the population is designed. The evolution speed of the population is dynamically adjusted by evaluating the evolution speed of the fitness in each iteration process, and the global and local search information is controlled. Secondly, the small-hole imaging reverse learning strategy combined with the idea of optimal-worst reverse learning is proposed. This strategy increases the diversity of the optimal-seeking positions and improves the ability of the algorithm to jump out of the local optimum;Finally, the current position is updated according to the position and speed of each firework, and the globally optimal fireworks and personally optimal fireworks are updated simultaneously to improve the individual heuristic learning ability. Through the simulation experiments on the CEC2015 test function and comparison with related algorithms, the results show that the algorithm performs better in convergence speed, computational accuracy, and stability. © 2022 IEEE.

关键词： Global optimization

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TransCGAN-based Parameter Extraction Framework for SAR Image Simulation

TransCGAN-based Parameter Extraction Framework for SAR Image...

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Signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Sidan Deng Jingfei He Yongfei Mao Liangbo Zhao Liang Chen Hao Shi National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing & Chongqing Innovation Center Beijing Institute of Technology Chongqing China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing Institute of Technology Beijing China Institute of Remote Sensing Satellite China Academy of Space Technology Beijing China National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing & Chongqing Innovation Center Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Synthetic Aperture Radar (SAR) images have a wide range of applications due to their all-weather and all-day working conditions. However, SAR images with different scenarios and imaging conditions are insufficient or even rare, which is required in specific SAR image tasks. Fortunately, SAR image simulation technology can provide ample simulated images under these conditions at a low cost, addressing the scarcity of specific real SAR data. Accurate parameters are crucial for obtaining high-quality simulated images. However, it is time-consuming and labour-intensive to adjust parameters manually, and it often fails to achieve accurate simulation parameters. To tackle this problem, this paper proposes a TransCGAN-based SAR image simulation method that combines deep learning with traditional methods. By training TransCGAN, a conditional generative adversarial network (CGAN) integrated with Transformer architecture, a mapping between SAR images and simulation parameters is established. This enables the extraction of simulation parameters directly from the real SAR image, guided by the corresponding real SAR image. Ultimately, the parameters are subsequently converted into simulated SAR images via simulation software. Experimental results demonstrate that our TransCGAN-based method can effectively extract accurate simulation parameters from real SAR images, resulting in simulated images holding high similarity to real images.

关键词： Training Accuracy Imaging Radar imaging Transformers Generative adversarial networks Radar polarimetry Software Synthetic aperture radar Parameter extraction

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Research on low energy task allocation and scheduling algorithm based on imprecise heterogeneous multi-core technology

Research on low energy task allocation and scheduling algori...

引用

2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Gu, Haonan Wu, Jing Hu, Wei Ma, Tianao Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

In heterogeneous embedded systems, we try to find a new non real-time scheduling algorithm, which can not only meet the reliability requirements, but also achieve low energy consumption. 'Resource reservation time deterministic cyclic scheduling (RRTDCS)' algorithm is a kind of scheduling for offline cache pre-allocation. This scheduling algorithm combines time reservation and priority strategy. The algorithm can dynamically adjust according to different task sets. It can also adjust its own scheduling process to adapt to different scheduling environments. The periodic cyclic strategy enables low power consumption in task allocation. In the experimental part, we compared the algorithm proposed in this paper with the current mainstream real-time scheduling scheme. Experimental results show that RRTDCS algorithm has better performance. © 2022 IEEE.

关键词： Scheduling

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Two-sided Online Stable Task Assignment with Incomplete Lists and Ties in Spatial Crowdsourcing 19

Two-sided Online Stable Task Assignment with Incomplete List...

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2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Huang, Weiyi Li, Peng Li, Bo Liu, Jing Nie, Lei Bao, Haizhou Wuhan University of Science and Technology School of Computer Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China

ISBN: (纸本)9798350346558

For the application of task assignment in crowdsourcing, previous research has focused on offline version or one-sided online version. Some of them draw extra attention to stability in task assignment. Our work extends a one-sided task assignment and its stable generalization. In particular, we present a two-sided online stable task assignment (TS-OSTA) problem in which any vertex from two sides can maintain an incomplete neighbor list and ties. We first give the fundamental definitions of task assignment in spatial crowdsourcing and stable matching. Then, we analyze and present the matching condition and formulate the TS-OSTA problem. As a warm-up, we investigate and analyze two classical baseline algorithms Greedy and Random Threshold. Then we present a bipartite ranking algorithm that maintains the efficiency of Greedy and effectiveness of Random Threshold. Through extensive experiments, we examine the performance of our algorithm in size, memory, and time. The results show that our algorithm performs better than the baselines. © 2022 IEEE.

关键词： Crowdsourcing

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Low Energy Consumption and Time Deterministic Energy-saving Workflow Task Scheduling Algorithm based on DVFS 9

Low Energy Consumption and Time Deterministic Energy-saving ...

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9th IEEE International Conference on Cyber Security and Cloud Computing and 8th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2022

作者： Liu, Xun Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan China

ISBN: (数字)9781665480666

ISBN: (纸本)9781665480666

With the development of streaming media, soft real-time system in today's life could participate in the use of more extensive areas. The use frequency was also increasing. Consequently, modern processors were equipped with software control mechanisms such as DVFS (Dynamic Voltage Frequency Scaling) to allow operating systems to meet required performance while reducing power consumption. Therefore, we propose a task scheduling algorithm combined DVFS technology and time deterministic cyclic scheduling to achieve energy saving effect. First, the algorithm needed to minimize the preemption between tasks to reduce latency, so we created a buffer to save periodic tasks to avoid preemption. Second, to reduce the computational cost of the scheduling scheme, a scheduling template were designed to perform tasks. In this paper, the scheduling of periodic tasks, task scheduling would be designed when the task scheduling template would be fixed length. Besides, this algorithm supported that task could adopt appropriate voltage and frequency through DVFS technology in idle time under the condition of satisfying task dependence. Experimental analysis showed that the proposed algorithm could effectively reduce the system energy consumption while ensuring the completion of the task. © 2022 IEEE.

关键词： Scheduling

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Distributed Secondary Control of DC Microgrids with Operation Loss Reduction

Distributed Secondary Control of DC Microgrids with Operatio...

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第43届中国控制会议

作者： Maoxiang Qiu Zhicheng Zhang Zhiqiang Zuo Yijing Wang Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In DC microgrids, current sharing and voltage regulation are two main objectives for real-time control, while the operation loss reduction is typically achieved by steady-state optimization. However, the ratio of current sharing is generally determined by the result of the centralized optimization in the classical hierarchical control framework of DC microgrids. Such an issue brings insufficient capability in respond to the changes of photovoltaic power and stored energy in the solar-powered energy systems. To handle this, this work proposes a distributed control scheme for single-bus DC microgrids. Under the proposed controller, the objectives of current sharing, bus voltage regulation and the total operation loss(converter loss and line loss) reduction can be guaranteed simultaneously. Moreover, the constraints on line currents and bus voltage are tackled as ***, simulations verify the performance of the proposed control scheme.

关键词： DC Microgrids Current Sharing Voltage Regulation Operation Loss Reduction Distributed Secondary Control

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Improving energy consumption forecasting using DLnet based on periodic modeling

Improving energy consumption forecasting using DLnet based o...

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2022 International Conference on Networks, Communications and information technology, NCIT 2022

作者： Liao, XueChao Huang, Xiang School of Computer Science and Technology Wuhan University of Science and Technology Hubei China Key Laboratory of Intelligent Information Processing and Real-Time Industrial Systems Hubei China

ISBN: (纸本)9783800760190

Improving the prediction accuracy of energy consumption in office buildings is necessary to achieve high energy efficiency in smart buildings. The existing forecasting methods rarely analyze the periodic characteristics of energy consumption independently. In this paper, a short-term office building energy consumption prediction model (DLnet) is proposed to address the problem of inefficiency in the utilization of periodic energy consumption ***, the period component of the energy consumption data is decomposed using STL, and the optimal period of the energy consumption data is searched for by a grid search algorithm, and then the Periodic block is constructed based on the optimal period;Secondly, the Time-series block data is constructed according to the data shape of the Periodic block;then the Time-series block data and the Periodic block data are trained and learned using LSTM;Finally, the prediction results of the Time-series block data and the Periodic block data are fused by linear *** four prediction accuracy indicators of the proposed model have been demonstrated to be 7%, 21%, 25%,and 26% higher than those of the LSTM model. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Office buildings

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Feature Selection Method Based on Ant Colony Optimization Algorithm and Improved Neighborhood Discernibility Matrix 16th

Feature Selection Method Based on Ant Colony Optimization Al...

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16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021

作者： Yang, Zhenyu Ye, Jun Ao, Jiaxin Ji, Yuxuan College of Information Engineering Nanchang Institute of Technology Nanchang330000 China Jiangxi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang330000 China

ISBN: (纸本)9789811912559

Under the condition that the classification ability of the characterization data remains unchanged, selecting the smallest feature subset from the feature set is one of the problems that many researches try to solve. In view of the existing neighborhood rough set and ant colony optimization feature selection methods, the algorithms are premature, and the searched feature subset contains redundancy and other problems. Improvements have been made in three aspects. One is to extend the discrimination matrix based on equivalence to the rough set of neighborhoods, and define a neighborhood discernibility matrix;second, to give a method for the importance of neighborhood discrimination matrix features;The third is to use the importance of the neighborhood feature as the heuristic information factor of the ant colony algorithm, and propose a feature selection method based on the ant colony optimization algorithm and the improvement of the neighborhood discernibility matrix. Numerical examples and data set experiments show that the new feature selection method improves accuracy and reduces the number of iterations. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Feature Selection

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Mining Alarm Association Rules in Optical Transmission Networks Using a Statistical Approach 24

Mining Alarm Association Rules in Optical Transmission Netwo...

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24th IEEE International Conference on High Performance Computing and Communications, 8th IEEE International Conference on Data Science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Deng, Miao Li, Peng Liu, Yu Zhu, Rongjing Zhang, Yujie School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China

ISBN: (纸本)9798350319934

Due to the interconnection between devices in the optical transmission network (OTN), when one device fails and generates alarm information, a large number of other invalid alarms are generated in OTN. How to mining association rules in alarm data is an important problem. In this paper, we investigate the association rules mining problem based on a statistical method. First, we remove the chattering alarm in preprocess to reduce data redundancy. Second, we propose a statistics-based association rule mining algorithm. We use a sliding time window to scan the alarm data, and we exploit the matrix to record the corresponding results. According to the matrix, we calculate the support and confidence of association rules. Compared with other traditional association rule mining algorithms, the proposed algorithm does not need to set the minimum support artificially, and the obtained association rules have strong causality. Through extensive experiments on syn-thetic and real OTN alarm datasets, we verify the effectiveness of our proposed algorithm and the correctness of the obtained association rules. © 2022 IEEE.

关键词： Association rules

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Influence Maximization With Graph Neural Network in Multi-Feature Social Network 24

Influence Maximization With Graph Neural Network in Multi-Fe...

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作者： Wang, Yuhao Li, Peng Huang, Weiyi School of Computer Science and Technology Wuhan University of Science and Technology China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China

ISBN: (纸本)9798350319934

The classical influence maximization (IM) prob-lem aims to select a set of nodes as seed nodes for information propagation. Most related studies focus on one-dimensional information dissemination. However, the diffusion of information should be a multi-dimensional (or multi-feature) diffusion process. The user's judgment of information often depends on the combined judgment of multiple-dimensional information. Based on this, we consider a multi-feature diffusion model. In-formation will be decomposed into multi-dimensional features for diffusion. The user will receive these features and integrate them into a complete message. In addition, we consider seed node selection as a network node classification task. Consid-ering that social networks satisfy a graph structure, we use the node classification technique of graph neural networks. This technique classifies the nodes by the network topology to find the set of influential nodes. We propose a multi-feature influence (MFI) algorithm to improve the performance of the prediction. The set of candidate nodes obtained by classification is used as a benchmark to find the set of nodes with maximum influence. Our experiment results on real datasets show that the proposed algorithm has better algorithmic efficiency than the traditional greedy algorithm and better effectiveness than similar heuristic algorithms. © 2022 IEEE.

关键词： information dissemination

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