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Performance Evaluation of intelligent computing Platform for Air-Combat Decision Algorithm 24

Performance Evaluation of Intelligent Computing Platform for...

引用

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： Xu, Kangfa Bai, Linting Wen, Pengcheng Niu, Wensheng Xi'an Aeronautics Computing Technique Research Institute Avic Aviation Key Laboratory of Science and Technology on Airborne and Missle-borne Computer Xi'an China

ISBN: (纸本)9798350319934

At present, some performance evaluation methods of intelligent computing platform oriented to air combat decision algorithm have problems such as complex evaluation index system construction, poor evaluation accuracy, difficult to verify the effectiveness of evaluation conclusions and lack of real-time performance. Based on this, this paper establishes the intelligent computing platform performance evaluation index set according to the intelligent decision class algorithm structure, platform compatibility and platform hardware characteristics. Cloud center of gravity method and consistent weighting method are selected as the evaluation algorithm and weighting algorithm respectively to carry out real-time evaluation and form the initial evaluation conclusion. Besides, the 'evaluation confidence' is used to judge the validity of the evaluation conclusion and whether a second evaluation is needed to form the final conclusion and the simulation environment of air combat is used to verify the accuracy of the evaluation results. This method avoids the randomness and uncertainty of the traditional evaluation methods, ensures the real-time and effectiveness of the evaluation results, significantly improves the accuracy, and can truly and effectively reflect the operational performance of the computing platform equipped with the air-combat decision algorithm. © 2022 ieee.

关键词： Cloud computing

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Comprehensive Review of Smart Healthcare Recommendation systems Using Deep Learning 1

Comprehensive Review of Smart Healthcare Recommendation Syst...

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1st international conference on Innovative and intelligent Information Technologies, IC3IT 2024

作者： Bouslah, Soumeya Benharzallah, Saber Hamouma, Moumen Kahloul, Laid University of Batna 2 Lamie Laboratory Departement of Computer Science Batna Algeria University of Biskra Linfi Laboratory Departement of Computer Science Biskra Algeria

ISBN: (纸本)9798331541064

As smart cities advance and increasingly use data from Internet of Things (IoT) sources to enhance urban environments, smart healthcare has become a key focus area. This paper investigates the integration of Deep Learning (DL) techniques in Smart Healthcare Recommendation systems (SHRSs), presenting a foundational taxonomy, that categorizes these systems into four distinct types: Content-Based Filtering (CBF), Collaborative Filtering (CF), Context-Aware Filtering (CAF), and Hybrid Filtering (HF). These approaches, implemented through DL, enable advanced data processing, pattern recognition, and personalization. Additionally, the paper introduces a new classification based on the nature of intervention, dividing SHRSs into preventive, diagnostic, treatment-focused, and hybrid categories. This dual classification fills a critical gap in the comparative analysis of DL-driven healthcare, which demonstrates the efficacy of these systems in providing personalized health advice, leveraging real-time sensor data and optimizing the handling of complex health datasets. Furthermore, this research outlines future work and potential directions for advancing SHRSs, offering insights into the application and impact of sophisticated recommendation techniques within the context of urban health management. © 2024 ieee.

关键词： Electronic health record

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Vehicle Pseudonym Change Mechanism Based on Dynamic Game

Vehicle Pseudonym Change Mechanism Based on Dynamic Game

引用

2024 international conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Zhao, Zheng Wang, Junren Mao, Qian Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Liaoning University Shenyang China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

intelligent Transportation systems (ITS), particularly vehicular ad-hoc networks, play a crucial role in improving road safety and traffic efficiency. However, transmitting vehicle location and identity data poses significant privacy risks, potentially allowing attackers to exploit this information. In this study, we developed a user-centric privacy model based on information entropy, enabling vehicles to monitor real-time location privacy levels. We also proposed a decision algorithm for pseudonym changes, dynamically identifying a cooperative set of vehicles for pseudonym alteration. Comparative experiments using SUMO and NS-3 simulations show that our scheme enhances location privacy while reducing pseudonym change frequency. This research provides valuable theoretical and technical foundations for ITS. © 2025 SPIE.

关键词： Vehicular ad hoc networks

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Research on the Control System and Method of Cutting Arms for Digital Twin Driven Excavation Equipment 9

Research on the Control System and Method of Cutting Arms fo...

引用

9th international conference on intelligent computing and Signal Processing, ICSP 2024

作者： Hu, Shouxin Yang, Yong Bao, Wenliang Nie, Yukun Taiyuan Institute Co. Ltd China Coal Technology & Engineering Group Shanxi Taiyuan030006 China Shanxi Tiandi Coal Mining Machinery Co. Ltd. Shanxi Taiyuan030006 China China National Engineering Laboratory for Coal Mining Machinery Shanxi Taiyuan030006 China

ISBN: (纸本)9798350376548

A digital twin driven cutting arm control system for excavation equipment is proposed to address issues such as low intelligence level, low excavation efficiency, and mismatch between equipment performance parameters and actual mine conditions. Firstly, the overall scheme of the digital control system for the cutting arm of excavation equipment was proposed using digital intelligent technology;Secondly, based on the feedback of physical information from sensors and servo hydraulic cylinders, a dual closed-loop control structure is designed, taking into account external disturbances and input saturation uncertainties. Using backstepping control theory and adaptive technology, a controller is derived to control the displacement and speed of the cutting arm. Finally, the on-site working face and virtual device twin models are restored using the Unity3D platform. Through intelligent perception of the environment and backend data analysis and processing, functions such as state detection, collision detection, and fault diagnosis are achieved. © 2024 ieee.

关键词： Digital control systems

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AI for Finance (AIFF): from Abnormal data Recognition to Information System Intrusion Detection 2

AI for Finance (AIFF): from Abnormal Data Recognition to Inf...

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2nd international conference on Edge computing and Applications, ICECAA 2023

作者： Zhang, Xiaoyuan Shandong Youth University of Political Science Accounting School Jinan250103 China

ISBN: (纸本)9798350347579

With the development of the data mining and the intelligent information technology, the complex information processing paradigm based on artificial intelligence has become a mainstream trend. In this paper, starting from the discussions of abnormal data detection, the novel information system intrusion detection is designed for the construction of the AIFF model. The model starts with the recognition accuracy improvement, in the designed scheme, the weighted Naive Bayes algorithm and the intelligent clustering model are combined to effectively detection the abnormal information. Then, by adopting the rule that modification of the firewall rules on the proxy server makes it possible to directly filter out the next intrusion address from the firewall, the pre-processing will be achieved. Furthermore, this study proposes a scheduling strategy based on resource availability to finalize the detection system. Through the experiment under different scenarios of the self and also comparison testing, the performance is validated. © 2023 ieee.

关键词： Information systems

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A Meticulous Analysis of Diverse Human Traits in Avid Readers and Non-Readers Through advanced data Analytics and Machine Learning Approach

A Meticulous Analysis of Diverse Human Traits in Avid Reader...

引用

2024 ieee international conference on Information Technology, Electronics and intelligent Communication systems, ICITEICS 2024

作者： Aziz, Farook Abdul Sowmya, V.J. Hindustan Institute of Technology and Science Department of Computer Applications Chennai India

ISBN: (纸本)9798350382693

In the contemporary digital landscape, the enduring practice of reading books encounters formidable challenges amidst the pervasive allure of instant digital gratification. This paper embarks on a nuanced exploration, dissecting the intricate interplay between digital culture and the enduring significance of reading. While past research has predominantly scrutinized the dwindling popularity of reading and its repercussions on empathy and academic performance, our study takes a deeper dive. We focus on scrutinizing the ramifications of reading, or its absence, on pivotal aspects including stress levels, sleep quality, memory, and cognitive functions. Through rigorous comparative analysis between avid readers and non-readers, our aim is to elucidate the comprehensive impact of reading on human well-being. Furthermore, as part of our research endeavor, we intend to employ sophisticated machine learning models to predict an individual's psychological profile, particularly focusing on their position within the psychology spectrum. Leveraging cutting-edge sophisticated machine learning techniques and data visualization techniques, this research endeavors to unravel the subtle connections between reading habits and diverse dimensions of well-being, underscoring the paramount importance of nurturing a steadfast reading habit. © 2024 ieee.

关键词： Emotional intelligence

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Research on Demand Response data Compression Based on Neural Network under 5G Environment 5

Research on Demand Response Data Compression Based on Neural...

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5th ieee international conference on Power, intelligent computing and systems, ICPICS 2023

作者： Pan, Yuqing Qi, Bing Li, Bin Zhu, Enguo Liu, Yan Lu, Chunguang Wang, Chaoliang School of Electrical and Electronic Engineering North China Electric Power University Beijing China China Electric Power Research Institute Beijing China State Grid Zhejiang Electric Power Co. Ltd. Hangzhou China

ISBN: (纸本)9798350333442

In the context of 5G, data volume is exploding, and data transmission and processing are facing challenges. In this paper, a data compression algorithm based on neural network is proposed to solve the problem of large scale and high dimension of demand response data in the process of transmission and storage. By mapping demand response data to low dimensional space for representation, the algorithm effectively reduces the amount of data and improves the efficiency of data transmission and storage. The algorithm uses Long Short Term Memory network for data compression and restoration. The experimental results show that the data compression algorithm based on neural network has good compression effect and accuracy. At the same time, the algorithm has good versatility and adaptability, and can be applied to the compression and restoration of data sets of different types and sizes, providing an effective solution for efficient demand response data processing. © 2023 ieee.

关键词： Restoration

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Recurrent Neural Network Analysis of Optometry data

Recurrent Neural Network Analysis of Optometry Data

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2024 ieee international conference on intelligent computing and Emerging Communication Technologies, ICEC 2024

作者： Sharma, Avinash Barua, Tarkeshwar Saxena, Rini Goswami, Manish Goyel, Parul Chandigarh Group of Colleges Chandigarh Engineering Department of Computer Science and Engineering 140307 India Roorkeee Institute of Technology Department of Computer Science and Engineering Roorkee India Chandigarh Pharmacy College Chandigarh Group of Colleges 140307 India M. M. Engineering College Maharishi Markandeshwar Mullana Computer Science & Engineering Haryana Ambala1307 India

ISBN: (纸本)9798331508432

This survey explores the potential of recurrent neural networks (RNNs) for analyse eye-trailling data, generally data obtained from Optometry systems. RNNs stand out at distinguishing patterns in consecutive data, making them appropriate for tasks like foretell future gaze, distinguishing areas of interest, and detecting anomalousness in gaze patterns. The abstract synopsis the process of probing Optometry data using RNNs. It highlights data pre-processing steps like cleaning, formatting, and normalization. The assortment of an LSTM network edifice and hyperparameter tuning for optimal execution are discussed. breeding and evaluation operation are explained[12], including using separate breeding, validation, and testing sets. Finally, the abstract mentions potential computer applications of the analysis, including human-computer interaction(HCI) (HCI) optimization and individual behavior understanding. © 2024 ieee.

关键词： Recurrent neural networks

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Empowering Anomaly Detection for Industrial Internet of Things with intelligent Edge computing and Decentralized Machine Learning

Empowering Anomaly Detection for Industrial Internet of Thin...

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2024 international conference on advanced Technologies for Communications, ATC 2024

作者： Pham-Nguyen-Hai, Anh Van-Thien, Luan Nguyen-Khanh, Thuat Le-Trung, Quan University of Information Technology Faculty of Computer Networks and Communications Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350353983

The Industrial Internet of Things (IIoT) aims to connect machinery, equipment, human resources, and all other relevant components in an industrial environment to achieve op-erational and management efficiency. Alongside the potential benefits of IIoT, this field also has many exploitable vulnerabilities. IIoT devices are often limited in resources, making implementing security solutions directly on these devices difficult. Instead, N et-work Intrusion Detection systems (NIDS) are typically deployed at edge nodes in IIoT systems. In this study, we build a NIDS on cloud infrastructure to simulate edge devices within the Swarm Learning architecture. In this system, we train two models, CNN and RNN, on the Edge-IIoTset dataset. The results show that the CNN and RNN models in the Swarm Learning architecture achieve good performance compared to Centralized Learning models and Federated Learning approaches. Specifically, our system achieves accuracy close to centralized machine learning models and outperforms Federated Learning approaches in binary and multi-label attack detection. Additionally, we evaluate the aggregators in Swarm Learning. The mean aggregator is stable, while the coord and geo aggregators achieve high accuracy in classes with few data points. © 2024 ieee.

关键词： Edge computing Edge-IIoTset dataset IIoT NIDS Swarm Learning

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13th international conference on Frontier computing, FC 2023

13th International Conference on Frontier Computing, FC 2023

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13th international conference on Frontier computing, FC 2023

ISBN: (纸本)9789819992980

The proceedings contain 180 papers. The special focus in this conference is on Frontier computing. The topics include: Optimization of English Machine Translation Model Based on Neural Network;exploration on Text Detection Optimization Algorithm Based on Neural Network Technology;CO2 Emission Prediction of Vehicle Fuel Consumption Based on EMD-LSTM;application of data Fusion Algorithms in the data Processing of intelligent Greenhouses;intelligent Film and Television Communication Optical Technology Based on Network New Media;design of Heterogeneous database Encryption and Decryption System Based on data Mining;research and Implementation of Music Recommendation System Based on Particle Swarm Algorithm;design of High-Speed Multi-channel data Transmission System Based on Single-Chip Microcomputer;application of Distributed database System in Financial Management;Research on the Development of Japanese MOOC System Based on BP Neural Algorithm;research on Default Risk Prediction of Listed Companies’ Green Credit Based on Deep Learning Algorithm;improvement of Cloud Platform Utilization Based on Evaluation and Optimization of computing Resource Runtime Surplus Capacity;design and Implementation of Operation and Maintenance Monitoring Platform Based on data Mining Algorithm;civil Aviation Logistics Transportation Route Optimization Algorithm Based on A+ Algorithm;design of Interactive Japanese Translation System Based on Feature Extraction Algorithm;a Preliminary Study on Low-Carbon City Planning Methods Supported by the Cluster Optimization Algorithm;object Detection Algorithms in Embedded systems and their Applications;Application of Computer VR Technology in Digital Media System Design;discuss the Technical Application of Cloud data Center and Cloud Management Platform;Design of ARM-Based Program Automatic Shelling data acquisition System.

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