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Memetic Algorithm Small Survey For 2019 Published Papers 3

Memetic Algorithm Small Survey For 2019 Published Papers

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3rd international conference on Creative Communication and Innovative Technology, ICCIT 2024

作者： Hendric Spits Warnars, Harco Leslie Spits Warnars, Laurens Utomo, Wiranto Herry Doucet, Antoine Ramadhan, Arief Siswanto, Teddy Bina Nusantara University Computer Science Department of Computer Science Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Department of Information Systems Jakarta11480 Indonesia President University Master of Science and Technology West Java17530 Indonesia Université de La Rochelle Laboratoire L3i La Rochelle France Telkom University School of Computing Bandung40257 Indonesia Trisakti University Department of Information Systems Jakarta11440 Indonesia

ISBN: (纸本)9798350367492

The Memetic Algorithm (MA), introduced by Pablo Moscato in 1989, integrates Evolutionary Algorithms with local search methods, enhancing its effectiveness in solving complex optimization problems. This paper provides a comprehensive survey of MA research published in 2019, reviewing 75 selected papers from an initial pool of 112 identified through Google Scholar. The selected papers were categorized into five types: optimization problems (40 papers), image processing (10 papers), parallel processing (5 papers), gene/DNA datasets (4 papers), and other applications (16 papers). The survey highlights MA's versatility and effectiveness across various domains, particularly its potential for solving complex optimization problems. Key findings include the adaptability of MA for diverse applications, its ongoing relevance in addressing challenging issues, and promising opportunities for combining MA with other algorithms to enhance performance. The paper also emphasizes the significance of MA in fields such as image processing, where it improves pattern recognition and image enhancement, and in bioinformatics, where it optimizes gene selection and genetic algorithms. Despite the extensive study of MA, there remains a significant research gap in non-English literature, particularly in Bahasa, limiting accessibility for Indonesian researchers. This survey aims to bridge this gap by providing valuable insights and encouraging further exploration and application of MA to solve increasingly complex problems. It offers a comprehensive overview that underscores the importance of MA and its potential for future research and innovation. © 2024 IEEE.

关键词： Genetic algorithms

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O(N) distributed direct factorization of structured dense matrices using runtime systems 23

O(N) distributed direct factorization of structured dense ma...

引用

52nd international conference on parallel Processing (ICPP)

作者： Deshmukh, Sameer Ma, Qinxiang Yokota, Rio Bosilca, George Tokyo Inst Technol Sch Comp Tokyo Japan Tokyo Inst Technol Global Sci Informat & Comp Ctr Tokyo Japan Univ Tennessee Innovat Comp Lab Knoxville TN USA

ISBN: (纸本)9798400708435

Structured dense matrices result from boundary integral problems in electrostatics and geostatistics, and also Schur complements in sparse preconditioners such as multi-frontal methods. Exploiting the structure of such matrices can reduce the time for dense direct factorization from O(N-3) to O(N). The Hierarchically Semi-Separable (HSS) matrix is one such low rank matrix format that can be factorized using a Cholesky-like algorithm called ULV factorization. The HSS-ULV algorithm is highly parallel because it removes the dependency on trailing sub-matrices at each HSS level. However, a key merge step that links two successive HSS levels remains a challenge for efficient parallelization. In this paper, we use an asynchronous runtime system PaRSEC with the HSS-ULV algorithm. We compare our work with STRUMPACK and LORAPO, both state-of-the-art implementations of dense direct low rank factorization, and achieve up to 2x better factorization time for matrices arising from a diverse set of applications on up to 128 nodes of Fugaku for similar or better accuracy for all the problems that we survey.

关键词： low rank approximation runtime systems HSS matrix distributed

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Research and Application of Three-Dimensional Point Cloud Data Analysis Technology for Smart Grid Transmission Data Based on Cloud Computing 3rd

Research and Application of Three-Dimensional Point Cloud Da...

引用

3rd international Symposium on New Energy and Electrical Technology (ISNEET)

作者： Guo, Jinchao Rao, Chengcheng Chen, Yun Guangdong Power Grid Co Ltd Machine Patrol Management Ctr Guangzhou 521000 Peoples R China

ISBN: (纸本)9789819905553;9789819905539;9789819905522

Big data is an important product of the information age. Integrating big data into smart grid applications and correctly grasping the key technologies of big data can effectively promote the sustainable development of power industry and the construction of strong smart grid. As far as modern smart grid is concerned, this is both an opportunity and a challenge. 3D point cloud data processing is the core content of reverse engineering technology. As an important data processing step in the preprocessing stage of 3D point cloud, point cloud registration plays an extremely important role in obtaining the complete 3Dcoordinates of the measured target surface. However, at present, the registration speed, accuracy and reliability of various registration algorithms still need to be improved. Cloud computing technology integrates several cheap ordinary PCs into a cloud computing cluster, which realizes the safe storage and efficient processing of massive data. Therefore, consider combining cloud computing with data mining algorithm to solve the problem of massive data conversion in smart grid. In this paper, cloud computing technology is introduced into the smart grid condition monitoring field. By introducing distributed file system, improving traditional density clustering algorithm and parallel design, the storage and clustering division of big data in condition monitoring are effectively solved, which provides a feasible method for the application of cloud computing in condition monitoring field.

关键词： Cloud computing Smart grid Transmission data 3D point cloud data analysis technology

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Battery Optimization Using Machine Learning 3

Battery Optimization Using Machine Learning

引用

3rd IEEE international conference on Blockchain and distributed systems Security, ICBDS 2024

作者： Patil, Aditya Lodha, Sanket Deshmukh, Sonal Joshi, Rupali S. Patil, Vaishali Chitnis, Sudhir Vishwakarma Institute of Information Technology Pune India Mgm University-Institute Of Management and Research Chh. Sambhajinagar India Mgm University-JavaharlalNehru Engineering College Chh. Sambhajinagar India Pvg College of Science and Commerce Pune India Vishwakarma Institute of Information Technology Pune India Vishwakarma College of Arts Commerce and Science Dept. of Computer Science Pune India

ISBN: (纸本)9798350354348

The ever-growing mountain of e-waste, fueled by short-lived batteries, threatens our planet's security. Discarded batteries leach toxic materials, jeopardizing environmental health and safety. This escalating crisis demands a paradigm shift. This research proposes a groundbreaking solution: leveraging Machine Learning to optimize battery lifecycles, dramatically reducing waste and its associated environmental security *** work integrates advancements in solid-state electrolytes with data-driven ML techniques to enhance battery management, contributing to sustainable security solutions. We employ clustering algorithms to categorize batteries for targeted optimization and implement regression models to predict and mitigate battery degradation. Our approach goes beyond traditional capacity and voltage metrics, incorporating crucial factors like temperature and depth of discharge for a holistic E-waste security *** research paves the way for a secure and sustainable future by establishing a critical link between AI and responsible e-waste management. By promoting collaboration between researchers, policymakers, and consumers, we can leverage technology to decouple our reliance on electronics from the environmental burden of battery waste. This work presents a powerful solution with immense potential to secure a cleaner and more sustainable future. © 2024 IEEE.

关键词： Waste management

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Multivariate Time Series Missing Value Filling Based on Trans-GAN Model 3

Multivariate Time Series Missing Value Filling Based on Tran...

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3rd international conference on Intelligent Communications and Computing, ICC 2023

作者： He, Pengfei Dang, Jianwu Yang, Jingyu Yue, Biao School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou China

ISBN: (纸本)9798350308327

To address challenges in handling missing values in multivariate time series data, such as low efficiency, insufficient utilization of temporal features, and inadequate reasoning capability under high missing rates, this study proposes the Trans-GAN network model. The model is a fusion of the Transformer and Generative Adversarial Network, incorporating the QS sparse attention module to replace the self-attention matrix in the Transformer. This replacement reduces algorithmic complexity and enhances inference performance. Additionally, to improve training stability, Trans-GAN introduces the W-GAN loss function, overcoming the issue of mode collapse observed in traditional GAN networks. Experimental results demonstrate that Trans-GAN achieves outstanding imputation performance on multiple datasets, showcasing robust generalization capabilities and offering a promising solution for imputing missing values in multivariate time series data. © 2023 IEEE.

关键词： parallel processing systems

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Real-time Strategy for Voltage Regulation of Distribution Networks Considering the Incomplete Response of distributed Resources 3

Real-time Strategy for Voltage Regulation of Distribution Ne...

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2023 3rd international conference on Smart Grid and Energy Internet, SGEI 2023

作者： Tan, Wenzhuo Yi, Xingyu College of Electrical and Information Engineering Hunan University Changsha410082 China

To solve the problem of nodes whose voltage exceeds the security constraint in the scenario of massive distributed generation access, a real-time strategy for voltage regulation of the distribution network considering the incomplete response of distributed resources is proposed. The strategy includes two parts: a real-time strategy for voltage regulation of the distribution network and the improvement of the strategy to deal with the incomplete response of distributed resources. Firstly, the real-time voltage autonomy of the distribution network is realized through the distributed resource strategy for voltage regulation;Then, aiming at the incomplete response of distributed resources, the strategy for voltage regulation is improved, and the margin iteration and feedback regulation are added;Finally, based on the IEEE33 node model, we verify the strategy for voltage regulation which is proposed in this paper. The results of the experiment show that the strategy for voltage regulation can effectively solve the problem of distribution network voltage out of limit, and has good anti-interference ability for the incomplete response of distributed resources. © Published under licence by IOP Publishing Ltd.

关键词： Real time systems

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Range-Aware Hand Gesture Recognition Using FMCW Radar and Deep Learning 29

Range-Aware Hand Gesture Recognition Using FMCW Radar and De...

引用

29th IEEE international conference on parallel and distributed systems, ICPADS 2023

作者： Iida, Yosuke Fan, Mingyang Brahim, Walid Ma, Jianhua Ma, Muxin Qi, Alex Hosei University Graduate School of Computer and Information Sciences Tokyo184-8584 Japan Faculty of Computer and Information Sciences Hosei University Tokyo184-8584 Japan Pontosense Inc. 20 De Boers Dr Suite 514 Toronto Canada

ISBN: (纸本)9798350330717

This paper introduces a hand gesture classification implementation that combines FMCW radar and deep learning. Unlike previous work, we implement a Range-Aware methodology to automatically locate the hand range bin enabling more accurate classification. The inspiration behind our proposal is the observations made about the impact of the subject chest in the Range-Time (RT) information and the signature of the hand movement in the Range-Doppler (rd) space. Subsequently, we propose three distinct methods for hand range bin localization. Method I and II take advantage of the first observation by locating the chest and using it as a reference to select the hand bin. Method III, however, exploits the second observation about the Doppler signature of the hand movement to directly select the hand bin. The Doppler matrix resulting from each method is then fed to a CNN-based model for the hand gesture classification task. We perform subject-dependent and independent evaluations to classify six hand gestures and investigate the impact of several parameters including the type of input data, the use of an LSTM layer, and an increased range of up to 90 cm. The evaluation results show good performance even for subject-independent and from distance up to 90 cm achieving an average accuracy of 99.86% in subject-dependent evaluations and 94.23% in subject-independent scenarios. © 2023 IEEE.

关键词： deep learning FMCW radar hand gesture Range-Aware Time-Doppler

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Collaborative attack task assignment for distributed UAV swarm using competition cooperation mechanism 3

Collaborative attack task assignment for distributed UAV swa...

引用

3rd international conference on Advanced Algorithms and Signal Image Processing, AASIP 2023

作者： Su, Wenjia Gao, Min Gao, Xinbao Xuan, Zhaolong Army Engineering University of PLA Shijiazhuang050003 China

ISBN: (纸本)9781510668522

Unmanned aerial vehicle (UAV) swarm has sparked heated debate around the world in recent years. There are various stages to the battle of UAV swarm. This paper focuses on the attack task assignment after being cast or launched over the battlefield. In order to describe the process of task assignment for UAV swarm, a model introducing multiple constraints, such as limited detection range and imperfect communications, is established first. Then, inspired by contract network algorithm, we proposed a mechanism including competition for local revenue and cooperation for global revenue. And the premise of this mechanism is that UAV swarm is distributed, whose task is assigned by itself, not any other UAV. Finally, the advantages of our mechanism are illustrated by the contrast of different methods on the same issue. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Unmanned aerial vehicles (UAV)

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Research on Motion Control of Bipedal Wheeled-leg Robot Based on distributed Model 3

Research on Motion Control of Bipedal Wheeled-leg Robot Base...

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3rd international conference on Control and Intelligent Robotics, ICCIR 2023

作者： Yang, Yang Zhian, Zhang Nanjing University of Science and Technology School of Mechanical Engineering Nanjing210094 China

ISBN: (纸本)9781510671867

With the rapid development of mobile robot technology, bipedal wheeled-leg robots, which combine the efficient mobility of wheeled robots and the adaptability of legged robots to uneven terrain, are gradually attracting widespread attention. In complex terrains and unstructured environments, such as stairs, ramps, and narrow spaces, bipedal wheeled-leg robots have superior mobility and adaptability. This article introduces a motion control method for bipedal wheeled-leg robots with a five-bar leg configuration. This method decouples the robot system based on a distributed model, analyzes the body and wheeled leg system separately, and implements a controller for the robot's rapid movement on flat terrain, adaptation to unstructured terrain, and jumping movements through virtual model control and model predictive control. A series of experiments have verified the feasibility of the prototype system's movement in real-world scenarios. © 2023 SPIE.

关键词： Motion control

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A Scalable distributed Query Framework for Unstructured Big Clinical Data: A Case Study on Diabetic Records 3rd

A Scalable Distributed Query Framework for Unstructured Big...

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3rd international conference on Sustainable Expert systems, ICSES 2022

作者： Sayar, Ahmet Computer Engineering Department Kocaeli University İzmit41380 Turkey

ISBN: (纸本)9789811978739

Nearly 80% of the information in the healthcare sector is unstructured data, and this percentage is steadily rising. Traditional relational database solutions are not effective for the analysis and querying of that type of data. For the purpose of searching and analyzing unstructured clinical data, we provide a distributed and scalable big data system in this research. The framework was developed using the open source Hadoop and Hive libraries and is based on the MapReduce paradigm. The effectiveness of the suggested architecture is demonstrated by running various queries on actual records from diabetic clinics. In terms of response times, the framework is also contrasted with relational databases. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Search engines

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