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检索条件"任意字段=International Conference on Advances in Intelligent Control and Computer Engineering"

共 46884 条记录，以下是4981-4990 订阅

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computer Simulation Study on The Relationship Between the Tensile Fracture Behavior of Aircraft Composites and The Fiber Strength Distribution 6

Computer Simulation Study on The Relationship Between the Te...

引用

6th international conference on intelligent Computing and control Systems, ICICCS 2022

作者： Kong, Lei Guangzhou Civil Aviation College School of Aircraft Maintenance Engineering Guangzhou510470 China

ISBN: (纸本)9781665410359

Composite materials have excellent characteristics such as high specific strength and high specific stiffness, but the whole life cost issue is still the core issue of composite materials applied to aircraft structures on a large scale. Although domestic and foreign researchers have conducted corresponding studies on the cost of each stage of aircraft composite material structure, the cost of each stage is still studied separately. This article first conducts tensile failure experiments on aircraft reinforced composite materials, and uses scanning electron microscope testing method technology to Observe the microstructure morphology of the transverse and longitudinal cross-sections of the composite material. © 2022 IEEE.

关键词： Aircraft manufacture

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Design and analysis of electrical automation control system under the application of computer technology

Design and analysis of electrical automation control system ...

引用

2022 international conference on Mechanisms and Robotics, ICMAR 2022

作者： Wu, Jie Fuzhou Preschool Education College Jiangxi Fuzhou344000 China

ISBN: (纸本)9781510657328

At present, the development and growth of electrical automation control industry constantly promotes the optimization design of electrical automation control system by computer technology. The software design of electrical automation control system by computer technology mainly includes two main contents: control algorithm and control system. Therefore, this paper puts forward the practical role of electrical automation control algorithm under dual-mode integral steady-state control of computer technology. At the same time, the data information processing is used for automatic data collection, and the fuzzy parameter identification model is used to establish the electrical automation control unit. Use computer technology to remotely operate automation, improve the stability of electrical automation, and maximize the gain of electrical automation control system, so as to promote the intelligent development of electrical automation control system. © 2022 SPIE.

关键词： Software design

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Enhancing Strategic Marketing with AI-Driven Insights into Dynamic Preferences and Decision Patterns

Enhancing Strategic Marketing with AI-Driven Insights into D...

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2025 international conference on intelligent control, Computing and Communications, IC3 2025

作者： Raj, Vijilius Helena Shubhra Al-Rubaye, Taqi Mohammed Khattab Siri, Dharmapuri Sirisha, N. Dutt, Amit New Horizon College of Engineering Department of Applied Sciences Bangalore India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India College of Medical Technologies The Islamic University Department of Medical Laboratory Technology Najaf Iraq Griet Department of Cse Bachupally Telangana Hyderabad India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India

ISBN: (纸本)9798331527495

Once AI begins gathering client data, the marketing sector will alter drastically. This research uses sophisticated AI technologies to better understand how complex client behaviors might be. We examine pricing solutions, including social media mood monitoring, joint filtering algorithms for targeted marketing, and reinforcement learning-based dynamic pricing. Neural networks are being investigated for application in e-commerce predictive analytics and predicting subscription cancellations. This research examines clustering algorithms' performance to see whether they may be utilized for cross-channel marketing activities, including consumer segmentation and credit modeling. The article concludes by examining how virtual reality is affecting shop advertising and marketing. The study's findings encompass AI-powered marketing strategies' applications, advantages, and drawbacks. AI helps marketing, according to the findings. Businesses may improve their strategy, communicate with consumers, and meet client needs using this information. © 2025 IEEE.

关键词： Marketplaces

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Automated Traffic Management Handling Traffic Congestions 5

Automated Traffic Management Handling Traffic Congestions

引用

5th IEEE international conference on advances in Science and Technology, ICAST 2022

作者： Roy, Reema Anne Patil, Sunita R K J Somaiya Institute of Engineering and Information Technology Sion Mumbai Department of Computer Engineering Mumbai India

ISBN: (纸本)9781665492638

Today, the number of vehicles on the road is drastically growing and thus, the existing traffic arrangement method is unable to adequately address traffic congestion issues, particularly at intersections and four-way intersections. High Priority Vehicles (HPV) get caught in traffic as a result of traffic congestion, causing delays in their emergency services. This paper provides a solution addressing the challenge of traffic congestion to supply priority vehicles with fast movement to provide timely transportation and reaction with an automated intelligent traffic management system that can modify paths and decisions itself based on vehicle density and emergency priority with the use of deep learning algorithms. © 2022 IEEE.

关键词： Traffic congestion

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Lightweight computer vision based asphalt pavement crack visualization detection 8

Lightweight computer vision based asphalt pavement crack vis...

引用

8th international conference on intelligent Computing and Signal Processing, ICSP 2023

作者： Yun, Zehui Lv, Jingguo Liu, Yiting Zhang, Jiyong Beijing University of Civil Engineering and Architecture School of Geomatics and Urban Spatial Informatics Beijing China State Power Economic Research Institute Co. Ltd. Beijing China

ISBN: (纸本)9798350302455

Cracks are the most common damage on urban asphalt roads, and it is important to detect cracks, which can effectively improve the safety performance of asphalt roads to extend their service life. The current detection of cracks mostly uses deep learning methods based on computer vision, and deep learning algorithms generally have the incompatibility problem of high accuracy and poor speed or fast speed and poor accuracy, and crack detection is limited by the demand of equipment can not be easily applied in the mobile terminal. Therefore, this paper proposes a lightweight road detection method based on computer vision. The method uses YOLOv5 as Baseline, and experiments are conducted by two different lightweight methods to explore the impact of pruning-based lightweight methods on network model size and detection speed and accuracy. The first method is based on weight pruning of BN layer, and the second method is based on pruning of Backbone's network structure. By comparing the evaluation with Baseline on the homemade dataset, the results show that the Backbone based network structure pruning only decreases the accuracy by 7.3% under the condition of pruning the Params by 55.2%, and the method achieves better results, which is beneficial to the fast and easy deployment of computer vision based deep learning networks in mobile. © 2023 IEEE.

关键词： computer vision

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Kidney Tumor Detection Using MLflow, DVC and Deep Learning 2

Kidney Tumor Detection Using MLflow, DVC and Deep Learning

引用

2nd IEEE international conference on advances in Information Technology, ICAIT 2024

作者： Usha, M.G. Shreya, M.S. Supreeth, S. Shruthi, G. Pruthviraja, Dayananda Chavan, Pundalik School of Computer Science Engineering REVA University Bangalore India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Karnataka Manipal576104 India

ISBN: (纸本)9798350383867

Kidney tumors are a global health concern, necessitating precise detection for effective treatment and better patient outcomes. This paper presents a novel approach that combines deep learning with Data Version control (DVC) and MLflow frameworks to revolutionize kidney cancer detection. Deep learning, a subset of artificial intelligence, shows great promise in interpreting complex patterns in medical imaging data. Utilizing convolutional neural networks (CNNs), our model analyzes radiographic images to identify subtle indicators of renal malignancies with unprecedented accuracy and efficiency. Incorporating DVC ensures seamless management of large imaging datasets, promoting collaboration and reproducibility across research endeavors. Additionally, MLflow streamlines the experimentation process, enabling systematic evaluation of model performance metrics and hyperparameters. Through meticulous logging and visualization of experimentation results, our framework facilitates informed decision-making, leading to the selection of optimal models for kidney cancer detection. This comprehensive approach signifies a significant advancement in oncological diagnostics, offering a holistic solution to the challenges posed by kidney cancer. By merging deep learning with DVC and MLflow, our methodology heralds a transformative paradigm shift in cancer detection, poised to enhance clinical outcomes and elevate patient care globally. ©2024 IEEE.

关键词： Convolutional neural networks

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An Interactive Game based Learning Model for Autistic Children 7

An Interactive Game based Learning Model for Autistic Childr...

引用

7th international conference on intelligent Computing and control Systems, ICICCS 2023

作者： Ravale, Ujwala Gnanasekar, Divhya Kulkarni, Sanket Suryanarayan, Lakshmi SIES Graduate School of Technology Department of Computer Engineering Navi Mumbai Nerul400706 India

ISBN: (纸本)9798350397253

In the world one of the most prevalent developmental diseases is autism. It is a chronic illness for which there is now no known treatment. In general manner it is the result of a neurological disorder that shows how the brain functions. Children with autism are typically self-absorbed and seem to live in their own worlds, making it difficult for them to interact and connect with others. Sometimes, they struggle to understand what people are saying to them and to learn how to interact with others. The use of visual aid is one of the most strongly suggested ways of teaching autistic youngsters. Games, by their very nature, provide flexibility, the ability to learn from failures, and the ability to adapt to new difficulties and expectations. They have been demonstrated to be one of the most successful tools for autistic people. The proposed system is designed to tackle Autism Spectrum Disorder (ASD) using the gaming approach. The aim is to provide age-targeted gameplay, which includes targeting specific skills for certain, age groups with levels in each game. Also providing a reward system, with tokens or a visual mark of achievement, makes the game more interesting and engaging to play, hence children perform better. © 2023 IEEE.

关键词： Serious games

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Power Resilience Planning under the Threat of Artificial Intelligence

Power Resilience Planning under the Threat of Artificial Int...

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2024 Portland international conference on Management of engineering and Technology, PICMET 2024

作者： Corbett, Chip Nguyen, Cuong Hongchai, Dahm M. Thorat, Prajakta Prasad, Pavithra Von Schimmelmann, Sarah Weber, Charles Anderson, Tim Portland State University Engineering and Technology Management Department PortlandOR United States Product Development Department Allbirds PortlandOR United States Process Engineering Department Intel PortlandOR United States

ISBN: (纸本)9781890843458

The earth is an unstable planet. Change is constant and frequently chaotic. It is very important to plan carefully to manage changes that can be anticipated now, and to cover potential issues that might not yet have been discovered. The dawn of artificial intelligence (AI) presents a host of new concerns and opportunities. The criteria for evaluation are diverse and complex. Cybersecurity is absolutely essential, yet advances in technology have created an internet of things (IoT) where threat vectors might gain access to critical command and control elements through trillions of connected IoT devices. Whereas elegant zero trust cybersecurity models can be constructed and deployed, the vast majority of successful attacks involve a human element. Disruptive change makes decisions on any future course of action very difficult to evaluate. Distributed energy resources (DERs) can be designed to benefit individuals and improve the resilience of the power grid. We propose to direct the deployment of limited resources in an efficient fashion by evaluating the multi-discipline criteria using a hierarchical decision model (HDM), evaluated by human subject matter experts (SMEs) and generative artificial intelligence (GenAI). © 2024 PICMET.

关键词： Artificial intelligence

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Parameters Extraction of Photovoltaic Cell Using Particle Swarm Optimization 4th

Parameters Extraction of Photovoltaic Cell Using Particle Sw...

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4th international conference on Electronic engineering and Renewable Energy Systems, ICEERE 2024

作者： Chermite, Charaf Douiri, Moulay Rachid Elamri, Oumaymah Control and Computer Science for Intelligent Systems and Green Energy Department of Applied Physics Faculty of Science and Technology Cadi Ayyad University Marrakech Morocco LAMIGEP EMSI of Marrakech Systems and Applications Engineering Laboratory National School of Applied Sciences Cadi Ayyad University Marrakech Marrakesh Morocco

ISBN: (纸本)9789819799749

Extracting parameters accurately and effectively from solar photovoltaic (PV) models is crucial for detailed simulation, evaluation, and management of PV systems. Although there has been an increase in the development of analytical, numerical, and metaheuristic methods targeting this task, accurately determining these parameters continues to be a significant challenge. This study focuses on applying Particle Swarm Optimization (PSO) for the extraction of key parameters of RTC France solar cells, a critical step towards enhancing PV system efficiency and reliability. Additionally, the PSO's performance is evaluated against other metaheuristic algorithms including Enhanced Chaotic JAYA (CJAYA), Performance-Guided JAYA (PGJAYA), and Enhanced Gradient-Based Optimizer (EGBO), underscoring the effectiveness of the proposed PSO-based approach. Utilizing MATLAB-SIMULINK, comprehensive analysis and results are presented, shedding light on the efficacy of PSO in addressing the intricacies of parameter extraction in PV systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Particle swarm optimization (PSO)

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A Noval Event-IMU Odometry Based on Quadtree-Accelerated Asynchronous Event Corner and Graph Optimization 5

A Noval Event-IMU Odometry Based on Quadtree-Accelerated Asy...

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5th international conference on Robotics, intelligent control and Artificial Intelligence, RICAI 2023

作者： Lv, Xianwei Ma, Xiaoguang School of Information Science and Engineering Northeast University Shenyang China Foshan Graduate School Northeast University Foshan China

ISBN: (纸本)9798350357950

Event cameras, a type of neuromorphic vision sensor, capture pixel-level intensity changes to generate asynchronous event streams with precise timestamps. They offered several advantages, including a high dynamic range, high temporal resolution (low latency), and freedom from motion blur. Leveraging event information and corresponding visual algorithms holded significant promise for the development of robotic autonomous systems. In this paper, we proposed an event-inertial odometry method based on asynchronous event corner detection and tracking. We introduced a novel approach for fast event corner detection using a quadtree-based method, ensuring a spatiotemporally uniform distribution of corners. Additionally, we presented a high-precision state estimation framework that combines IMU measurements and event corner observations through graph optimization. To assess the performance of our method, we conducted experiments using a publicly available dataset and compared our results with state-of-the-art (SOTA) methods. Our findings demonstrated that our approach excels in terms of both accuracy and speed. © 2023 IEEE.

关键词： computer Vision Event Cameras Odometry

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