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Artificial Intelligence: Trends and Challenges 7

Artificial Intelligence: Trends and Challenges

引用

7th international conference on Parallel, distributed and grid computing, PDGC 2022

作者： Karthick, A.V. Gopalsamy, S. Alagappa University Department of Computational Logistics Karaikudi India Alagappa University Department of International Business Karaikudi India

ISBN: (纸本)9781665454018

Artificial Intelligence is an interdisciplinary field that combines Machine Learning, Big Data, Cloud computing, and Information Theory. The major advantage of machine learning is that it builds on prior experience, so machines are self-learning and can predict the future without error. It is a kind of decision-making approach that is applied in various domains like social media, health care, finance, etc. In Big Data and Cloud computing, the volume of data is sustainable and increasing, which is processed with low power consumption with the help of machine learning. It is possible to support the next generation of smart grid by providing the platform that integrates, in addition to the communication infrastructure, the AI and IoT support, providing a multitenant system, thanks to the future Massive Internet of Things (MIoT), one of the pillars of the 5G/6G network factory. Rapid development in Deep Learning, Artificial Intelligence (AI) and Machine Learning (ML) will give better results for future applications. This paper focuses on the trends and challenges related to AI is discussed. © 2022 IEEE.

关键词： Decision making

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Human Activity Recognition based on MEMS Sensors Using Convolutional Neural Network 16

Human Activity Recognition based on MEMS Sensors Using Convo...

引用

16th international conference on Cyber-Enabled distributed computing and Knowledge Discover, CyberC 2024

作者： He, Zhenyu Lin, Junjie He, Zhenfeng Sun, Yulin Jinan University College of Information Science and Technology Guangzhou China Jinan University Guangdong Institution of Smart Education Guangzhou China Jinan University International School Guangzhou China Guangdong Tobacco Huizhou City Co. Ltd Huizhou China

ISBN: (纸本)9798331506896

Human Activity Recognition was a key part of medical and mobile applications in today's world, with important applications in old-age homes and monitoring daily activities. In this paper, we proposed an automated Human Activity Recognition model using a 1-Dimensional Convolutional Neural Network (CNN). To select the optimal parameters for the CNN model, we used the grid Search Cross Validation method. On one hand, we used a manual feature extraction and CNN method. Starting from the physical significance of accelerometer and gyroscope signals, we extracted a new set of features. Experimental results show that the new features we extracted perform well in common human activity recognition tasks using SVM, MLP, and CNN. On the other hand, we used a method where CNN automatically extracts features and performs recognition. Experimental results indicate that CNN's automatic feature extraction is more effective than manual extraction. The model proposed in this paper achieved a recognition rate of up to 98.53%, which is 2% higher than the current accuracy. © 2024 IEEE.

关键词： Gyroscopes

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Research on Key Technologies of Emergency Communication Device in distributed Power grid based on 5G Communication 4

Research on Key Technologies of Emergency Communication Devi...

引用

4th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2022

作者： Kangping, Yang Ziqi, Zhou Xinhui, Zhong Jiaming, Liu Xi, Han Digital Grid Research Institute China Southern Power Grid Guangdong Province Guangzhou City510670 China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

Taking distributed power grid emergency communication device as the research object, combined with 5G communication technology, the key technologies of distributed power grid emergency communication device based on 5G communication are studied. The 5G power emergency communication device adopts wireless broadband multi-network convergence technology, interference suppression method, service QoS guarantee method and security technology. In terms of communication mechanism, it can not only achieve compatibility between 5G and 4G, support network optimization, but also achieve the convergence between the operator's public network and 4G power wireless private network. The scheme ensures the quality of transmission service and realizes the secure transmission of data. © 2022 IEEE.

关键词： Electric power transmission networks

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GIRAFF: Reverse Auction-based Placement for Fog Functions 9

GIRAFF: Reverse Auction-based Placement for Fog Functions

引用

9th international Workshop on Serverless computing (WoSC) Part of Middleware conference

作者： Parol-Guarino, Volodia Parlavantzas, Nikos Univ Rennes Inria Rennes France INSA Rennes IRISA Rennes France

ISBN: (纸本)9798400704550

Function-as-a-Service (FaaS) is a compelling new programming model for developing applications running on fog infrastructures. FaaS applications are composed of short-lived, event-triggered units, called functions. Functions can be flexibly deployed on demand along the cloud-to-thing continuum. However, deciding how to place those functions in the fog presents multiple challenges. The fog contains diverse, geo-distributed, and potentially resource-constrained nodes that should be efficiently shared between applications with latency requirements. Importantly, fog nodes are owned by different entities that should be incentivized to share their resources. Most function placement approaches ignore latency requirements or the presence of multiple owners in fog infrastructures. To address these challenges, this article proposes a market-based approach to place FaaS applications in the fog. Clients submit function placement requests associated with SLAs that specify expected guarantees over network latency and allocated resources. The approach then organizes an auction among fog node providers to determine the nodes that host each function and the revenue of the provider. The article presents an open-source implementation of the approach evaluated on the grid'5000 testbed. Experiments demonstrate that our approach can reduce client spending by up to three times while delivering service quality that matches or exceeds that of baseline methods.

关键词： fog FaaS function-as-a-service serverless auction SLA service-level agreement QoS quality of service testbed grid'5000

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2nd international conference on Algorithms, Network and Computer Technology

2nd International Conference on Algorithms, Network and Comp...

引用

2nd international conference on Algorithms, Network and Computer Technology, ICANCT 2023

The proceedings contain 16 papers. The topics discussed include: a design pattern of IAPVS platform based on distributed edge computing;side-channel attack security risk assessment model based on mutual information game;research and application of power grid data anomaly tracing method based on time series correlation;military unmanned equipment image target recognition method based on improved deep learning;analysis of the influence of adjacent new pile foundation construction on the structural deformation of the in-service subway tunnels;a numerical study on smoke propagation in metro tunnel fires with different door opening scenarios;effect of door openings on train fire scenarios within a subway depot;numerical simulation study on the embedding depth of anti-slip piles in fully weathered granite landslides;analysis and optimization of brace system in scaffold;and an intelligent fault diagnosis method that combines operating condition attribute encoding and multi-scale cascading concept.

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Fault Location of Distribution Network with distributed Generation Based on BAS-PSO 8th

Fault Location of Distribution Network with Distributed Gene...

引用

8th international conference on computing, Control and Industrial Engineering, CCIE 2024

作者： Wang, Jing Peng, Yuefeng Zuo, Zhengqin Ren, Haige Wu, Xingxiu Liang, Yujie Tongren Power Supply Bureau of Guizhou Power Grid Co. Ltd Tongren554300 China

ISBN: (纸本)9789819769339

A Particle Swarm Optimization algorithm (BAS-PSO) based on the Tencent Bull whisker search algorithm is proposed to address the drawbacks of long localization time and easy falling into local optima when using particle swarm optimization to locate faults in distribution networks with distributed power sources. The algorithm first utilizes the Longhorn whisker search algorithm to optimize the initial population of the particle swarm optimization algorithm, producing a high-quality initial population;Secondly, establish a mathematical model for fault location in distribution networks with distributed power sources, and use an improved particle swarm optimization algorithm to iteratively generate the optimal solution, achieving the goal of accurately locating the fault section. Using the IEEE33 node distribution network model as a carrier, simulation experiments were conducted for single point, multi-point faults, and incorrect information uploaded by FTUs. The experimental results show that the BAS-PSO algorithm can quickly and accurately locate faults in distribution networks containing distributed power sources. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Power distribution faults

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Demand Response Scheme: Achieving Sustainability in distributed Data Processing 9

Demand Response Scheme: Achieving Sustainability in Distribu...

引用

9th IEEE international conference on Data Science in Cyberspace, DSC 2024

作者： Zhai, Xueying Peng, Yunfeng Guo, Xiuping Zhang, Liang Zhang, Wei University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China Beijing University of Posts and Telecommunications School of Economics and Management Beijing China Guizhou Institute of Technology Guizhou Key Laboratory of Electric Power Big Data Guizhou China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan Jinan China

ISBN: (纸本)9798350391367

The rapid development of Internet of Things (IoT) technology has driven the intelligent transformation of various industries, including manufacturing, agriculture, and healthcare, etc., significantly enhancing their management capabilities and decision-making efficiency. Data analysis is crucial, serving as both the core technology of this transformation and a major driving force for advancing industry intelligence. However, the increasing volume of data has led to high energy consumption during data analysis, posing significant challenges to environmental and economic sustainability. Integrating renewable energy sources (RESs) is an effective way to reduce greenhouse gas emissions due to their low-carbon and renewable nature. Additionally, the spatiotemporal variability and complementarity of RES generation and grid electricity prices provide favorable conditions for distributed data processing. Therefore, a two-stage demand response scheme is proposed to reduce carbon emissions and electricity costs by prioritizing data processing in data centers (DCs) where RES is abundant or electricity prices are low, based on RES generation and electricity price signals. Simulation results show that the proposed scheme reduces 36.37% carbon emissions and 20.49% electricity costs compared to the benchmark algorithm, indicating its potential for both environmental and economic optimization. © 2024 IEEE.

关键词： Low emission

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Anomaly Detection by Using Multimodal Deep Learning

Anomaly Detection by Using Multimodal Deep Learning

引用

2023 international conference on Algorithms, High Performance computing, and Artificial Intelligence, AHPCAI 2023

作者： Jiang, Guangxin Wang, Zhenyu Wang, Kunhan Han, Jinsi Wu, Shengli Tong, Min State Grid Inner Mongolia Eastern Power Co. Ltd. 010000 China State Grid Inner Mongolia Eastern Power Co. LTD. Inner Mongolia ultra high voltage branch 026000 China State Grid Inner Mongolia Eastern Power Co. Ltd. Electric power Research Institute 010000 China

ISBN: (纸本)9781510671881

In the field of power systems, the detection of multidimensional fault data is essential. Introducing the concept of IT Operations Artificial Intelligence (AIOps), combined with big data and machine learning techniques, aims to take place extensive IT operational tasks, including service availability and performance monitoring. Multiple models are utilized to process monitoring data patterns, such as text attributes and real-value response times extracted from logs and traces, enabling the detection of faults and potential anomalies in cloud services. To detect anomalies in the execution of system components, a dual-mode distributed tracing data from large-scale cloud infrastructure is employed, and a novel method for anomaly detection is proposed. The application of LSTM (Long Short-Term Memory) multimodal neural networks is demonstrated to learn the sequential characteristics of the two modes of data in traces. The capability to detect dependencies and concurrent events is showcased through a method that reconstructs execution paths using the proposed models. In experimental evaluations using large-scale production cloud data, the new approach outperforms traditional architectures and other deep learning methods. © 2023 SPIE. All rights reserved.

关键词： Long short-term memory

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A Study on the Random Evolution Dynamic Model of Compliance Behavior of Bid Evaluation Experts 24

A Study on the Random Evolution Dynamic Model of Compliance ...

引用

2024 international Academic conference on Edge computing, Parallel and distributed computing, ECPDC 2024

作者： Wu, Zhiwei He, Ping Dong, Bing Yang, Guang-Yu Zhang, Yifei State Grid Jilin Electric Power Co. Ltd. Tendering Company Jilin Changchun China

ISBN: (纸本)9798400718168

Tendering and bidding is one of the most important resource allocation methods in the market economy system with Chinese characteristics. Evaluation experts hold the leading position in the evaluation work, and their performance will have the most direct and fundamental impact on the evaluation results. In recent years, with the increase in the size of the bidding market, the team of evaluation experts has developed and grown. However, the number and quality of evaluation experts are not proportional. Cases of hidden ethical behaviors such as rent-seeking and non cooperation among evaluation experts causing the loss of excellent bids and significant losses to projects are common. Therefore, in order to improve the management level of evaluation experts, this article, based on game theory and other relevant theories, derives a mathematical analytical formula for the rooting probability, strategy rooting conditions, and rooting time of the Wright Fisher process stochastic evolutionary game model with selection differences. A dynamic model for the random evolution of compliance behavior of evaluation experts is established, and this model is applied to the management of evaluation experts. The rooting probability, strategy rooting time of compliance strategies of evaluation experts are solved, and the model is applied to the management of evaluation experts. Finally, numerical simulation was conducted using MATLAB to analyze the impact of parameter changes and incentive constraint conditions on the compliance behavior of evaluation experts. © 2024 ACM.

关键词： Resource allocation

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Smart grid Optimization Dimensioning Methods for Residential Solar Cell Dimensioning 2

Smart Grid Optimization Dimensioning Methods for Residential...

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2nd IEEE international conference on Device Intelligence, computing and Communication Technologies, DICCT 2024

作者： Mange, Purva Savant, Rohini Singh, Kriti Lule, Aditi Nagpur Campus Pune India

ISBN: (纸本)9798350372847

Power now comes from a variety of diverse sources. Electricity demand from homes accounts for a significant portion of the total, and fossil fuels are the primary source of energy. distributed generation (DG), clean energy technology (CET), and a demand side management (DSM) approach that employs energy efficiency (EE) measures have been actively promoted on a worldwide scale for technical, economic, and environmental reasons. This study introduces the idea of client creation as a method of load management. The solar generator's cheap upkeep and simple operation are major benefits of using it. Several factors, including orientation, tilt angle, and module technology, affect how much it costs every supplied solar Watt, making it crucial to get the sizing of a planned photovoltaic system just right. Significant effects on PV system performance may be attributed to changes in tilt angle and module technology. This research simulates the effects of installing PV generators of varying capacities (Si-mono, Si-poly, and Si-amorph) in the Indian city of Alger. Mounted PV generators have been tilted at several degrees, from 0 degrees to 90 degrees, to determine the optimal installation angle for PV generators on the roofs of homes. Savings in energy and money on energy bills have been calculated as a final step. © 2024 IEEE.

关键词： Energy efficiency

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