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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

共 1401 条记录，以下是271-280 订阅

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cloud computing in Enhancing the Efficiency and Integration of Alternative Energy Systems

Cloud Computing in Enhancing the Efficiency and Integration ...

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Computational Intelligence, Communication Technology and Networking (CICTN), international conference on

作者： Amiya Kumar Sahoo Sucharita Prusty Suvendra Kumar Jayasingh Asish Kumar Swain Hemanta Kumar Mohanta Aryan Institute of Engineering and Technology Bhubaneswar Odisha India Institute of Management and Information Technology BPUT Cuttack Odisha India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

In response to growing environmental concerns and the need for sustainable development, alternative energy systems have emerged as crucial solutions to the problems associated with fossil fuels. This research focuses on the significant role cloud computing plays in improving the efficiency and integration of various alternative energy systems such as solar, wind, hydropower, biomass, geothermal, and tidal/wave energy. The study explores how cloud computing technologies enable real-time data processing, storage, and analysis of the large datasets generated by these renewable energy sources, thus optimizing their performance and integration into the energy grid. cloud computing provides advanced data management tools that are vital for managing the variable and intermittent nature of renewable energy production. By utilizing cloud-based platforms, energy producers can achieve improved forecasting, load balancing, and energy distribution, which are essential for enhancing efficiency and reliability. Additionally, this research highlights how cloud computing fosters collaboration and innovation by offering a scalable and flexible infrastructure. This infrastructure supports the development of new technologies and applications within the renewable energy sector, promoting continuous advancements and breakthroughs. This research underscores the crucial role of cloud computing in advancing a sustainable energy future.

关键词： cloud computing Renewable energy sources Technological innovation Collaboration Production Data processing Real-time systems Security Reliability Sustainable development

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An industrial equipment maintenance support system for networked collaborative evolution in the smart product service ecosystem 2

An industrial equipment maintenance support system for netwo...

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2nd IEEE international conference on Digital Twins and parallel Intelligence, DTPI 2022

作者： Bao, Yu-Guang Sun, Zhao-Hui Liao, Xiao-Qiang Chang, Yuan Qiu, Siqi Ming, Xinguo School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665492270

The traditional model of industrial equipment operation and maintenance has changed with the development of industrial internet technologies such as edge computing, cloud-edge collaboration, big data, artificial intelligence, digital twins, etc. Meanwhile, researchers are beginning to focus on the range of influence of equipment asset reliability, which is shifting from local performance to organizational goals. The networked collaborative evolution of equipment assets and value chain management is becoming the core value proposition of industrial internet platforms. From the perspective of system architecture, this paper discusses a novel industrial equipment maintenance support system based on the industrial internet platform, detailing the design of the resource and edge layer, cloud platform layer, big data governance and service layer, modeling and simulation layer, information model and collaboration layer, and organization, business, and service layer. The proposed system architecture and solution are expected to provide possible guidance for group-type enterprises and cross-industry service providers to help them innovate equipment asset management solutions based on the industrial internet platform. © 2022 IEEE.

关键词： Simulation platform

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Optimizing Search and Sort Algorithms: Harnessing parallel Programming for Efficient Processing of Large Datasets

Optimizing Search and Sort Algorithms: Harnessing Parallel P...

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Automation, computing and Renewable Systems (ICACRS), international conference on

作者： Ipsit Maurya Subhratha Sinha M Suguna School of Computer Science and Engineering Vellore Institute of Technology Chennai

This research study investigates the impact of parallel programming techniques on the performance of searching and sorting algorithms. Traditional sequential algorithms have been the foundation of data processing for decades, but the increasing availability of parallel computing resources opens new possibilities for improving efficiency and reducing execution times. By leveraging parallel programming models, such as shared memory and distributed memory systems, this study explores how the parallelization of search and sort algorithms can enhance their speed and scalability. Through comprehensive experimentation and analysis, this study aims to provide valuable insights into the benefits and challenges of parallel programming in the context of searching and sorting algorithms.

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2nd international conference on Emerging Technologies for computing, Communications, and Smart Cities, ETCCS 2021

2nd International Conference on Emerging Technologies for Co...

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2nd international conference on Emerging Technologies for computing, Communications, and Smart Cities, ETCCS 2021

ISBN: (纸本)9789811902833

The proceedings contain 57 papers. The special focus in this conference is on Emerging Technologies for computing, Communications, and Smart Cities. The topics include: Spectral Analysis of DNA on 1-D Hydration Enthalpy-Based Numerical Mapping Using Optimal Filtering;a Novel Ensemble Model for Breast Cancer Diagnosis;a Novel Smart Aging Approach for Monitor the Lifestyle of Elderlies and Identifying Anomalies;spatial Analysis of Violent Crime Dataset Using Machine Learning;analysis of Violent Crime Dataset Using Support Vector Machine Model;nigeria Human Population Management Using Genetic Algorithm Double Optimized Fuzzy Analytics Engine Approach;flower Species Detection System Using Deep Convolutional Neural Networks;data Localization and Privacy-Preserving Healthcare for Big Data Applications: Architecture and Future Directions;design of Facial Recognition Based Touchless Biometric System;comparative Analysis of Semantic Similarity Word Embedding Techniques for Paraphrase Detection;seeker Optimization for Linear Phase Fir Filter Design;cloud Supported Secure e-Card College Management System;An Optimization of VM Allocation and Migration in cloud computing Systems for High Throughput and Low Tolerance;graDex—Graph-Based Data Analytics for Extractive Text Summarization;smart Traffic Monitoring with Fog and cloud computing;a Review of Precision Agriculture Methodologies, Challenges, and Applications;power Quality Enhancement and Low Voltage Ride Through Capability in Hybrid grid Interconnected System by Using D-Fact Devices;Optimal LFC Regulator for Frequency Regulation in Multi Area Power System;optimal Power Flow Using Firefly Algorithm with Solar Power;designing of Learning Environment of an Intelligent Tutoring System for Academic Learning Needs of Learning-Disabled Learners Based on Survey Report of Region-Specific Target Group.

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Path Planning of Mobile Robot Based on an Improved Genetic Algorithm 2

Path Planning of Mobile Robot Based on an Improved Genetic A...

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2nd IEEE international conference on Digital Twins and parallel Intelligence, DTPI 2022

作者： Chen, Zenghua Xiong, Gang Liu, Sheng Shen, Zhen Li, Yue Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Chang'an University School of Automobile Xi'an China

ISBN: (纸本)9781665492270

In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations;Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm;Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles;Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning. © 2022 IEEE.

关键词： Genetic algorithms

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Powering up the IT Equipment and Cooling Units of cloud Data Centers using Photovoltaic-fed Microgrid

Powering up the IT Equipment and Cooling Units of Cloud Data...

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Innovation in Technology (INOCON), IEEE international conference for

作者： Sankata Bhanjan Prusty Liza Rani Behera Pritha Singha Roy Subhransu Padhee School of Electronics and Communication Engineering Reva University Bangalore Department of Computer Science and Engineering Government College of Engineering Keonjhar Department of Computer Science & Engineering Chitkara University Punjab Department of Electrical and Electronics Engineering Sambalpur University Institute of Information Technology Burla Odisha

cloud computing infrastructure is designed to support seamless accessability and availability of different services to consumers over the internet. cloud data centers require a lot of power for powering up of the IT equipments and powering up of different air conditioning equipments. The high power consumption leads to higher energy bill as well as increased carbon foot print. To minimize the effect of carbon foot print, distributed energy resources are utilized. This paper provides a systematic analysis of the power model as well as air conditioning model of data centers. The architecture of solar microgrid and economic analysis of solar microgrid for data center has been highlighted in this paper.

关键词： Economics Data centers cloud computing Power demand Atmospheric modeling Microgrids Computer architecture

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Residential Short Term Load Forecasting Based on Federated Learning 2

Residential Short Term Load Forecasting Based on Federated L...

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2nd IEEE international conference on Digital Twins and parallel Intelligence, DTPI 2022

作者： Chen, Jiuxiang Gao, Tianlu Si, Ruiqi Dai, Yuxin Jiang, Yuqi Zhang, Jun School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (纸本)9781665492270

Load forecasting is an essential task in the power industry as an important means to assist the grid to balance supply demand. A large amount of user data monitored by smart grids can support deep learning models for load prediction, but accurate and fine-grained user data may reveal consumers' electricity consumption behaviors, which brings privacy and security issues. Federated Learning (FL) is a new type of high-efficiency machine learning between multiple participants or multiple computing nodes under the premise of ensuring information security during big data exchange and protecting the privacy of terminal data and personal data. Therefore, this paper explored a short-term residential energy demand forecasting method based on FL. The experimental data comes from the U.S. hourly residential base load. The federal forecast model was built on Pytorch, and we explored model behavior under different experimental conditions. © 2022 IEEE.

关键词： Forecasting

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Point cloud semantic segmentation based on pillarpointnet 2

Point cloud semantic segmentation based on pillarpointnet

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2022 2nd international conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2022

作者： Gan, Xingli Shi, Hao Hu, Chunlei Deng, DianFu Yang, Shan School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou310023 China China Unicom Smart City Research Institute Beijing100048 China

Aiming at the problem that the deep neural network pointnet does not introduce local features, the segmentation accuracy is not high and the segmentation efficiency of pointnet++ is low. On the basis of pointnet, a two-way feature extraction method, pillarpointnet, is proposed. Our network is divided into upper and lower parallel paths. The upper path is a simplified version of pointnet, which is used to extract global features. In the lower path, we use pillars instead of voxels to reduce the problem of wasting computing power due to inconsistency in density. The features of each voxel are then assigned to the points within the grid to represent the domain features of the points. Finally, the local features, global features and the points are concatenated and put into the segmentation network. The final experimental results show that compared to some current state-of-the-art segmentation networks, pillarpointnet maintains a good balance between speed and accuracy. © Published under licence by IOP Publishing Ltd.

关键词： Deep neural networks

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Adaptive and Intelligent Edge computing Based Building Energy Management System 2nd

Adaptive and Intelligent Edge Computing Based Building Energ...

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2nd international conference on Sustainable Smart Cities and Territories, SSCT 2023

作者： Márquez-Sánchez, Sergio Alonso-Rollán, Sergio Pinto-Santos, Francisco Erbad, Aiman Ibrar, Muhammad Hanan Abdul Fernandez, Javier Hernandez Houchati, Mahdi Corchado, Juan Manuel BISITE Research Group University of Salamanca Calle Espejo s/n. Edificio Multiusos I+D+i Salamanca37007 Spain Salamanca37188 Spain Information & Computing Technology Division. College of Science and Engineering Hamad Bin Khalifa University A 036-F LAS Ar-Rayyan Qatar Iberdrola Innovation Middle East Doha Qatar

ISBN: (纸本)9783031369568

Most building and energy management system (BEMS) solutions follow a set of rules (supervised or unsupervised learning) to make energy-saving recommendations to inhabitants. However, these systems are normally solely trained on energy data meaning that they do not consider other key factors, such as the inhabitants’ comfort or preferences. The lack of adaption to inhabitants renders these energy-saving solutions largely ineffective. Moreover, BEMS solutions are cloud-based entailing greater cyberattack risks and a high data transmission load. To address these problems, this research proposes an edge computing architecture based on virtual organizations and distributed explainable artificial intelligence (XAI) algorithms for optimized energy use in buildings/homes and demand response. Thanks to virtual organizations’ energy efficiency (EE) measures, which consider the inhabitants’ comfort and dynamically learn from real-time inhabitant data, the consumption patterns of the inhabitants are effectively optimized. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Edge computing

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Smart Transportation Using Fog computing 2nd

Smart Transportation Using Fog Computing

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2nd international conference on Data Science, Machine Learning and Applications, ICDSMLA 2020

作者： Shaikh, Rizwana Modak, Masooda SIES Graduate School of Technolgy Navi Mumbai India

ISBN: (纸本)9789811636899

In the era of all smart applications with connected things, there is a need to tackle the issues of data preprocessing, increased latency in data and the overhead in traffic. Intelligent transportation systems (ITS) is one such application. Fog computing can be used as a support or replacement of cloud computing to solve the issue of data latency and traffic overhead. The paper proposes Fog computing based smart transportation application prototype that can be achieved by providing inter-fog communication. The communication over a distributed network is presented to cover a large geographical area. The inter-fog communication in the smart transportation could ensure the edge nodes managing the traffic lights and the street light control to be locally handled by the respective fog nodes with real time traffic reports. It can also provide suggestions for alternate routes at the time of congestion. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fog computing

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