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Introducing Competitive Mechanism to Differential Evolution for Numerical Optimization 30th

Introducing Competitive Mechanism to Differential Evolution...

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30th international conference on Parallel and distributed Processing Techniques, PDPTA 2024, held as part of the World Congress in Computer Science, Computer Engineering and Applied computing, CSCE 2024

作者： Zhong, Rui Cao, Yang Zhang, Enzhi Munetomo, Masaharu Graduate School of Information Science and Technology Hokkaido University Sapporo Japan Information Initiative Center Hokkaido University Sapporo Japan

ISBN: (纸本)9783031856372

this paper introduces a novel competitive mechanism into differential evolution (DE), presenting an effective DE variant named competitive DE (CDE). CDE features a simple yet efficient mutation strategy: DE/winner-to-best/1. Essentially, the proposed DE/winner-to-best/1 strategy can be recognized as an intelligent integration of the existing mutation strategies of DE/rand-to-best/1 and DE/cur-to-best/1. the incorporation of DE/winner-to-best/1 and the competitive mechanism provide new avenues for advancing DE techniques. Moreover, in CDE, the scaling factor F and mutation rate Cr are determined by a random number generator following a normal distribution, as suggested by previous research. To investigate the performance of the proposed CDE, comprehensive numerical experiments are conducted on CEC2017 and engineering simulation optimization tasks, with CMA-ES, JADE, and other state-of-the-art optimizers and DE variants employed as competitor algorithms. the experimental results and statistical analyses highlight the promising potential of CDE as an alternative optimizer for addressing diverse optimization challenges. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Competitive Mechanism Differential Evolution (DE) Evolutionary Computation (EC) Novel Mutation Strategy Numerical Optimization

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MoReco: AI Model Recommendation and Optimization for B5G Networks 4th

MoReco: AI Model Recommendation and Optimization for B5G N...

引用

4th international conference on Advanced Network Technologies and intelligent computing, ANTIC 2024

作者： Jaisawal, Sandeep Kumar Chawla, Ditya Mittal, Prerna Roopalakshmi, R. Paul, Ankita Singh, Sukhdeep Samsung R&D Institute India Bangalore Bangalore India Department of CSE Manipal Institute of Technology Manipal Academy of Higher Education Karnataka Manipal576104 India

ISBN: (纸本)9783031837951

the deployment of Artificial Intelligence and Machine Learning (AIML) models in 5G networks has become increasingly critical for optimizing network performance, particularly in applications such as Self-Organizing Networks (SON) and Open Radio Access Networks (O-RAN). However, the dynamic nature of cloud-based network infrastructures presents significant challenges, as changes in underlying resources can adversely affect the inference time and prediction accuracy of these models. this paper introduces MoReco, a novel framework designed to predict and optimize the performance of AIML models in continuously changing deployment environments. MoReco features a "trade-off analyzer" that selects the most suitable ML algorithm and hyperparameters, ensuring that the trained model meets predefined thresholds for both inference time and accuracy. By maintaining a comprehensive record of previous iterations and dynamically tuning models in response to network changes, MoReco eliminates the need for repeated retraining and redeployment. the system also includes a predictive mechanism that estimates model performance without actual deployment, significantly improving the efficiency of the model deployment process. the proposed framework is evaluated within the context of 5G networks, demonstrating its potential to enhance reliability and operational efficiency in intelligent network management. the paper concludes by discussing future work aimed at expanding MoReco’s capabilities and exploring its application in other domains such as IoT and smart cities. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Efficiency

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Multi-stage Feature Clustering Approach for Sorting Retired Batteries 8th

Multi-stage Feature Clustering Approach for Sorting Retired ...

引用

8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on intelligent computing for Sustainable Energy and Environment, ICSEE 2024

作者： Liu, Zhuo Meng, Bumin Luo, Xianguang Xiao, Xiangyu Wang, Xuelian Luo, Kaiyu Zhang, Da Pan, Rui School of Automation and Electronic Information Xiangtan University Xiangtan411105 China State Key Laboratory of Heavy-Duty and Express High-Power Electric Locomotive CRRC Zhuzhou Locomotive Co. Ltd. Zhuzhou412001 China Contemporary Amperex Technology Co. Limited Ningde352000 China

ISBN: (纸本)9789819602247

Retired battery laddering is an effective means to maximize the value of batteries. Targeting poor consistency of retired batteries, combining the comprehensive characteristics of discharge depth, charging capacity, open-circuit voltage and charge/discharge curves, a multi-stage sorting method for retired batteries is proposed. In the first stage, outliers are removed using the DBSCAN algorithm;In the second stage, the depth of discharge, open-circuit voltage and charging capacity are used as static features, and the K-means algorithm is used for clustering to realize the coarse sorting of retired battery;In the third stage, the ohmic internal resistance of different SOCs under HPPC conditions is used as a dynamic feature, and the t-distributed Stochastic Neighbor Embedding(t-SNE) is used for dimensionality reduction, and the category labels of retired batteries are obtained through clustering computation to realize the segmentation of retired batteries for selection. Finally, experiments were conducted using 60 retired batteries, and the consistency of the sorted retired batteries was significantly improved. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： State of charge

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BBDAS: Blockchain-Assisted Blinded Data Auditing Scheme for Cloud-Edge Systems 6th

BBDAS: Blockchain-Assisted Blinded Data Auditing Scheme for...

引用

6th international conference on Blockchain and Trustworthy Systems, BlockSys 2024

作者： Wang, Chen Cui, Yuxin Yang, Bing Shen, Wei Tong, Wei School of Information Science and Engineering Zhejiang Sci-Tech University Hangzhou310018 China School of Computer Science Nanjing University of Information Science Technology Jiangsu210044 China Zhejiang Sci-Tech University Hangzhou310018 China Hangzhou Institute of Technology Xidian University Hangzhou311200 China

ISBN: (纸本)9789819614134

In distributed large-scale intelligent computing, efficient collaboration between the cloud and edge devices is essential to provide rapid data access for a vast number of users, which is crucial for optimal data storage services. the edge servers are utilized to meet the data access requirements of adjacent group users. Numerous data auditing schemes for cloud computing have been proposed to protect user data integrity and avoid the threat of data leakage, loss, or tampering. However, secure cloud-edge storage of group users remains to be further studied. this paper proposes a novel blockchain-assisted blinded data auditing scheme for cloud-edge systems. Firstly, blockchain technology is utilized to monitor the activities of a semi-trusted third-party auditor (TPA). Secondly, user identifiers are utilized to trace the malicious behaviors in the systems. In addition, a data blinding algorithm is utilized to ensure that the raw data is unavailable to a curious TPA. Both security analysis and performance assessment demonstrate that this scheme conducts data auditing for cloud-edge systems with reliability and efficiency. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data integrity

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Study of multi-distributed generation behavior when fault occurrence in distribution system using wavelet transform 8

Study of multi-distributed generation behavior when fault oc...

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Joint 8th international conference on Soft computing and intelligent Systems (SCIS) / 17th international Symposium on Advanced intelligent Systems (ISIS)

作者： Ananwattanaporn, Santipont Ngaopitakkul, Atthapol King Mongkuts Inst Technol Ladkrabang Fac Engn Dept Elect Engn Chalongkrung Rd Bangkok 10520 Thailand

ISBN: (纸本)9781509026784

In the last decade the number of power generation using renewable energy has been rapidly increased due to the energy and environmental issue. this trend in renewable energy has shifting power generation system from Centralized Generation (CG) to distributed Generation (DG). With the new power generation on conventional distribution system, Analysis on disturbance must be done to ensure safety and reliability of the system. this paper aim to analyze behavior of transient signal when disturbance occur in distribution system with distributed generation. System under study is 22kV distribution system consist of wind power generation unit. Simulation was done by using PSCAD/EMTP program. the Discrete Wavelet Transform (DWT) is applied for decomposition of fault signal. To evaluate wavelet characteristic when fault occur in the system, Comparison in case of distribution system with and without wind power generation were done. Result indicated that with distributed generation, fault level is increasing and cause a changing in wavelet signal characteristic.

关键词： Distribution System distributed Generation Wind Power Fault Wavelet Transform

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Music recommendation system improvement using distributed genetic algorithm 8

Music recommendation system improvement using distributed ge...

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Joint 8th international conference on Soft computing and intelligent Systems (SCIS) / 17th international Symposium on Advanced intelligent Systems (ISIS)

作者： Inoue, Masayoshi Takenouchi, Hiroshi Tokumaru, Masataka Kansai Univ Grad Sch 3-3-35 Yamate Cho Suita Osaka 5648680 Japan Fukuoka Inst Technol Fukuoka 8110295 Japan Kansai Univ 3-3-35 Yamate Cho Suita Osaka 5648680 Japan

ISBN: (纸本)9781509026784

Existing music recommendation systems don't suit user subjectivity and are not naturally intuitive. We previously proposed a music recommendation system to address these problems. Our music recommendation system uses Kansei agents and a Kansei retrieval system. the Kansei agents employ a Kansei model and are characterized by a three-layered neural network. Music fluctuation properties are defined as inputs to the neural networks of the Kansei agents. Our previously proposed system returns recommendations based on user subjectivity. However, this system incurs significant user evaluation load. In this study, we introduce a distributed genetic algorithm (DGA) as an optimization method to address this problem. We compare the proposed DGA method to our previous method by simulation. the simulation results indicate that the proposed DGA method significantly outperforms previous method.

关键词： distributed genetic algorithm Kansei retrieval Music recommendation system Neural network

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Vector Register Sharing Mechanism for High Performance Hardware Acceleration 30th

Vector Register Sharing Mechanism for High Performance Hard...

引用

作者： Tanaka, Tomoaki Kato, Michiya Osana, Yasunori Miyoshi, Takefumi Tada, Jubee Tanaka, Kiyofumi Nakajo, Hironori Department of Electrical Engineering and Computer Science Graduate School of Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Tokyo Koganei-shi184-8588 Japan Research and Education Institute for Semiconductors and Informatics Kumamoto University 2-39-1 Kurokami Kumamoto Chuo-ku860-8555 Japan WasaLabo LLC. K-2 Buransyu 6-5-20 Minaminaruse Tokyo Machida-shi194-0045 Japan Graduate School of Science and Engineering Yamagata University 1-4-12 Kojirakawa-machi Yamagata Yamagata-shi990-8560 Japan Japan Advanced Institute of Science and Technology 1-1 Asahidai Ishikawa Nomi923-1292 Japan Division of Advanced Information Technology Computer Science Institute of Engineering Tokyo University of Agriculture and Technology 2-24-16 Nakacho Tokyo Koganei-shi184-8588 Japan

ISBN: (纸本)9783031856372

In recent years, demand for data-parallel processing has been growing, and this parallelism often appears in AI processes. One method to accelerate these processes is using DSA, domain-specific architecture. A common data transfer method on DSA is DMA, which is direct memory access. there are several studies on DMA-based accelerators. However, few studies focus on data transfer methods. In this paper, a vector register-sharing mechanism has been proposed as a new data transfer method. Our proposed mechanism is named "SHAVER". In this mechanism, a part of vector registers is directly shared with an accelerator. An open-source RISC-V vector co-processor is used to evaluate the mechanism’s potential. It has been implemented on an FPGA and a simulator for the evaluations. the results indicate the possibility of the proposal mechanism to achieve a maximum of 7.13% speedup over DMA transfer. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Vectors

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Analysis on the Development Status of ICV 17

Analysis on the Development Status of ICV

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17th IEEE international Wireless Communications and Mobile computing conference (IEEE IWCMC)

作者： Yang, Liu Liu, Shunan Changchun SCI TECH Univ Inst Intelligent Mfg Changchun Peoples R China

ISBN: (纸本)9781728186160

Under the background of the continuous improvement of artificial intelligence technology, the research technology of intelligent networked vehicle has become one of the hot topics in the global automotive technology research. It is not only a brand-new attempt for automobile structure and development, but also has a huge development space in the field of artificial intelligence technology. In this paper, the development status of intelligent network connected vehicle is analyzed and some suggestions are put forward.

关键词： icv development status key technology countermeasures and suggestions

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An Integrated Method for Mining Association and Sequential Rules in distributed Databases 17

An Integrated Method for Mining Association and Sequential R...

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Joint 17th World Congress of international-Fuzzy-Systems-Association / 9th international conference on Soft computing and intelligent Systems (IFSA-SCIS)

作者： Huang, Jih-Jeng Soochow Univ Comp Sci & Informat Management 56Sect 1Kueiyang St Taipei 100 Taiwan

ISBN: (纸本)9781509049172

Association and sequential rules have received much attention in both academia and in practice for quite some time. A number of algorithms have been proposed to improve the efficiency of mining decision rules. However, these centralized algorithms have been criticized for their inapplicability to distributed environments. Although many sophisticated distributed algorithms for mining association and sequential rules have been proposed in recent years, they are not supported by most popular software programs;this decreases the possible applications of decision rules. In addition, past decision rules have only focused on the rules for which items exist. Some important decision rules might be lost if suitable items do not exist. In this paper, we propose an integrated framework to combine centralized algorithms, such as the Frequent Pattern Growth (FP-Growth), Sequential Pattern Discovery using Equivalence classes ( SPADE), and rough set algorithms, to mine decision rules in a distributed environment. In addition, our method finds some significant rules that other algorithms cannot. the experiments also demonstrate that the proposed method is well suited to finding association and sequential rules in a distributed environment.

关键词： Data mining Association rules sequential rules distributed environment centralized algorithms

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Application of Stereo Vision technology In 3D Reconstruction of Traffic Objects 17

Application of Stereo Vision Technology In 3D Reconstruction...

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17th international Symposium on distributed computing and Applications for Business Engineering and Science (DCABES)

作者： Ren Jingfu Wang Hanbo Wuxi City Coll Vocat Technol CCVT Wuxi Jiangsu Peoples R China

ISBN: (纸本)9781538674451

the extensive use of modern intelligent transportation system is inseparable from computer technology, especially stereo vision technology, which has become an important technology for 3D reconstruction and detection of mixed traffic scenes. On the basis of the comprehensive description of the technology used in the traffic environment acquisition based on computer stereo vision, this paper analyzes the related object segmentation, shadow detection and 3D reconstruction and model recognition related technology in complex background traffic scene, and the 3D reconstruction technology in stereo vision matching. the development trend and difficulties of 3D reconstruction technology in stereo vision matching are also prospected.

关键词： stereo vision traffic scene 3D reconstruction camera calibration

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