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检索条件"任意字段=3rd Conference on Learning and Intelligent Optimization"

共 11827 条记录，以下是181-190 订阅

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Study of Stochastic Analysis optimization Algorithm in Information Retrieval 3

Study of Stochastic Analysis Optimization Algorithm in Infor...

引用

3rd IEEE International conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Xiao, Xiaonan Xiamen University Tan Kah Kee College Zhangzhou36310 China

ISBN: (纸本)9798350333862

The stochastic optimization algorithm and the random signal nonlinear optimal filtering algorithm are typical representatives of intelligent optimization algorithms in the rapidly developing scientific research and engineering application technology fields. They are the two computing cores of high-performance intelligent calculation in intelligent control. In order to effectively improve the efficiency of information filtering and optimal quantization modeling of a class of partially observable random signals with massive characteristics in intelligent control, stochastic optimal control theory and methods are used to discuss in depth the mathematical construction of this type of random signal transmission system. Two optimal control mathematical models are obtained via the optimal calculation and random optimization analysis of the allowable coding function and decoding function under this type of signal. It provides an ideal mathematical processing method for improving the intelligent control and information management efficiency of the signal transmission system. © 2023 IEEE.

关键词： Information filtering

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Research on Human Activity Recognition Algorithm Based on Metric learning 3

Research on Human Activity Recognition Algorithm Based on Me...

引用

3rd International conference for Innovation in Technology, INOCON 2024

作者： Hu, Yuncong Hangzhou Yuncong Intellectual Property Co. Ltd Zhejiang Hangzhou474177 China

ISBN: (纸本)9798350381931

In the context of the rapid development of computer technology, people's lives have been inseparable from high-tech technology, which can bring convenience to people. In the field of computer vision, human activity recognition is a very hot topic, basketball technology recognition, intelligent monitoring, intelligent security systems, etc. all need to use human activity recognition. Traditional recognition methods cannot solve the problem of accurate recognition of human activities in computer vision. Therefore, this paper proposes a measure learning for human activity recognition analysis. In the intelligent era, Human Activity Recognition (HAR) technology is like a beautiful landscape, spanning many research fields such as computer vision, pattern recognition and machine learning. With its unique charm, it attracts countless researchers to dig deep. © 2024 IEEE.

关键词： Computer vision

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Position Estimation for Mobile Robots using Machine learning 3

Position Estimation for Mobile Robots using Machine Learning

引用

3rd International conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Varma, Kallepalli Rahul Sreenivasan, Medha Srivani, N. Bhattacharya, Shourjyo Glace Varghese, T. Kochuvila, Sreeja Dept. of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Robot localization is a critical challenge present in autonomous robots to estimate their position within the environment, ensuring accurate navigation and task execution. This research project compares the position estimation capabilities of advanced machine learning methods Gradient Boosting and K-Nearest Neighbors. In this work Machine learning (ML) models are built using a dataset from *** that tracked Received Signal Strength Indicator (RSSI) readings and tested them against strong performance measurements. This work findings show GB provides better results than KNN because it reaches an R2 score of 0.9341. These insights are applicable in various fields, including autonomous vehicles, industrial automation, service robotics, and multi-robot coordination, guiding the selection of appropriate algorithms for specific localization challenges. © 2025 IEEE.

关键词： Gradient Boosting K-Nearest Neighbors Machine learning Navigation Robot localization

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Deep learning-Based Transfer learning with MobileNetV2 for Crop Disease Detection 3

Deep Learning-Based Transfer Learning with MobileNetV2 for C...

引用

3rd International conference on intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Jesupriya, J. Mageswari, P. Uma Alli, A. Bengaluru India Bengaluru India Bengaluru India

ISBN: (纸本)9798331515911

Early diagnosis of such maladies can avoid crop diseases and increase agricultural yield. We attempt to propose deep learning-based approach for the classification of diseases in an apple crop using the New Plant illnesses Dataset sourced from Kaggle. A pre-trained feature extractor called Mobile NetV2,with global average pooling and denser layers and dropout is included for achieving better regularization in the proposed model along with transfer learning. The increase in augmented image data increases generalization and robustness at training. Our approach is distinctive in terms of achieving excellent accuracy based on 97% training accuracy with a validation accuracy of 97% over20 epochs. In its pursuit to precision agriculture, this research allows quick interventions for crop health management through early disease detection-an efficient and lightweight choice. © 2025 IEEE.

关键词： Fruits

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A Multiclass Deep learning Approach using CRelu - To Enhance Brain Tumor Identification 3

A Multiclass Deep Learning Approach using CRelu - To Enhance...

引用

3rd International conference on intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Kusuma, P. Selvam, Sheba Ronihal, Shreedevi S. Bnm Institute of Technology Bangalore India Bnm Institute of Technology Bangalore India Bnm Institute of Technology Bangalore India

ISBN: (纸本)9798331515911

Research analyses the deployment of Convolutional-Neural-Networks (CNN) equipped with the CReLU (Concatenated Rectified Linear Units) activation function for identifying brain tumors MRI scan images. The CNN model is designed to be trained to classify various types of tumors, including glioma, meningiomas, pituitary tumors, and cases with no tumor present. By leveraging MRI images, the study evaluates how the CReLU activation function can enhance the model's capability to reliably distinguish between these tumor types, aiming to improve diagnostic accuracy and facilitate early detection through advanced image analysis techniques using deep learning. © 2025 IEEE.

关键词： Convolutional neural networks

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The Rise of Intelligence: A Comprehensive Review on AI and AI Automation 3

The Rise of Intelligence: A Comprehensive Review on AI and A...

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3rd International conference on Communication, Control, and intelligent Systems, CCIS 2024

作者： Bhardwaj, Cheshtaa Gla University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798331528201

This paper presents a comprehensive review of Artificial Intelligence (AI), Machine learning (ML), and Deep learning (DL) technologies, focusing on their impact in driving AI automation across diverse sectors with a special emphasis on robotics. As AI continues to evolve, its integration into automation systems has revolutionized industries, enhancing efficiency, precision, and decision-making. The role of AI automation in robotics is critically examined, covering key architectural frameworks that enable autonomous operation and intelligent decision-making. Furthermore, the security aspects associated with AI in robotics, identifying attack surfaces and potential vulnerabilities has been analysed. This review highlights the transformative potential of AI automation while addressing the challenges and security concerns that accompany its deployment in modern systems, particularly in robotics. © 2024 IEEE.

关键词： Adversarial machine learning

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optimization of Transmission Network Structure Based on Deep Neural Networks 3

Optimization of Transmission Network Structure Based on Deep...

引用

3rd International conference on Energy and Electrical Power Systems (ICEEPS)

作者： Zhang, Weiqi Li, Lixin Yu, Yijun China Elect Power Res Inst Power Automat Dept Beijing Peoples R China

ISBN: (纸本)9798350375145;9798350375138

Real-time transmission line switching control is a cost-effective and efficient measure to alleviate line overload. However, due to the nonlinear characteristics of the transmission network structure optimization problem, conventional optimization methods often struggle to find solutions quickly. In recent years, data-driven methods have been widely applied in fields such as power system dispatch optimization. This paper proposes a method based on deep neural networks. By using historical and simulation data of the power system, the neural network is trained to perform exploratory learning and find optimal topology control strategies when line overload occurs. This method is trained and tested on the IEEE 14-bus open-source dataset, and the test results verify its effectiveness.

关键词： deep learning data-driven deep neural networks topology optimization line overload mitigation

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Design and Implementation of intelligent Control Algorithm for Energy Power System Combined with Reinforcement learning 3

Design and Implementation of Intelligent Control Algorithm f...

引用

3rd International conference on Artificial Intelligence and Autonomous Robot Systems, AIARS 2024

作者： Zhang, Jiankai Xi'an University of Architecture and Technology Shaanxi Xi'an710000 China

ISBN: (纸本)9798350376173

Aiming at the requirement of intelligent control of energy power system (EPS), this paper proposes an intelligent control algorithm combined with reinforcement learning (RL), and designs and implements it in the microgrid system. Firstly, the state and control target of the microgrid system are determined by modeling it. Then, based on the RL algorithm, the agent is designed, and the appropriate state space, action space and reward function are defined, thus realizing the interactive learning between the agent and the environment. In the aspect of algorithm implementation, the depth RL algorithm (DQN) is used for training, and the algorithm is optimized and adjusted. Finally, the performance advantages of the proposed algorithm compared with the traditional PID control method are verified by comparative experiments, including clean energy utilization rate, load satisfaction rate, energy storage battery health status and system stability. The experimental results show that the proposed algorithm can effectively optimize the operation performance of microgrid system, and has good applicability and expansibility, which provides a new idea and method for EPS intelligent control. © 2024 IEEE.

关键词： clean energy DQN Efficient utilization of waste heat energy power system intelligent control Reinforcement learning

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A method for identifying illegal parking from unmanned aerial vehicles based on adaptive anchor boxes and multi-objective perception 24

A method for identifying illegal parking from unmanned aeria...

引用

3rd International conference on Algorithms, Data Mining, and Information Technology, ADMIT 2024

作者： Li, Yueyang Han, Xun Ai, Yi School of Transportation and Logistics Southwest Jiaotong University Sichuan Chengdu China Intelligent Policing Key Laboratory of Sichuan Province Sichuan Police College Sichuan Luzhou China School of Air Traffic Management Civil Aviation Flight University of China Sichuan Guanghan China

ISBN: (纸本)9798400718120

With the continuous increase in vehicle numbers, traffic violations have become prevalent. Traditional detection approaches are often labor-intensive and constrained by geographical and temporal limitations. This paper introduces an innovative method for analyzing unmanned aerial vehicle imagery of traffic violations, utilizing adaptive framing and multi-objective optimization techniques. We propose an adaptive anchor box algorithm based on SAMOPSO-Kmeans, which optimizes the number and dimensions of anchor boxes suitable for vehicle datasets. This optimization modifies weight coefficients and learning factors in a multi-objective particle swarm optimization algorithm, allowing for dynamic adjustments in response to iteration counts. Expanding on the SAMOPSO-Kmeans framework, we have developed a multi-objective detection algorithm, named SAMOPSO-EfficientDet-YOLOv7, for detecting traffic violations. This algorithm integrates the YOLOv7 detection network with the EfficientDet architecture, which employs a composite scaling strategy to adjust the network’s depth, width, and resolution simultaneously. The proposed framework significantly enhances performance compared to conventional methods, reducing the parameter count from 14.5 M to 9.1 M and improving mean average precision and accuracy by 1.48% and 10.52%, respectively. © 2024 Copyright held by the owner/author(s).

关键词： Particle swarm optimization (PSO)

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The Application of Dynamic Simulation and PID Control in the Kinematic Analysis of Suspended Crane 3

The Application of Dynamic Simulation and PID Control in the...

引用

3rd International conference on Energy and Power Engineering, Control Engineering (EPECE)

作者： Meng, Na Yang, Sen Sun, Wenzheng Chen, Longfa Shandong Univ Sci & Technol Coll Intelligent Equipment Tai An 271001 Shandong Peoples R China

ISBN: (纸本)9798350366105;9798350366099

With changes in speed, cranes inevitably experience swinging, making precise lifting difficult. Taking a suspended crane as an example, this study analyzes the mathematical characteristics of the crane. Through MATLAB/SIMULINK simulation analysis, it focuses on examining the operational performance of the crane under different working conditions. Conventional PID control parameter optimization is applied to the crane's load swing angle. Comparative analysis is conducted on experiments with and without an anti-swing control system. The results indicate that the PID controller can rapidly and effectively reduce swinging angles. This research provides valuable references for the dynamic optimization, system parameter selection, and swing control of suspended cranes.

关键词： Suspension crane Dynamic analysis Swing angle control PID control

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