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共 12917 条记录，以下是71-80 订阅

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Application of image classification in forest fire detection using UAV 3

Application of image classification in forest fire detection...

引用

3rd international conference on Robotics, Artificial Intelligence and Intelligent control (RAIIC)

作者： Geng, Bowen Beijing Univ Posts & Telecommun Beijing Peoples R China

ISBN: (纸本)9798350352634;9798350352627

This paper focuses on the application of image classification in forest fire detection using unmanned aerial vehicles (UAVs), discussing the development history of UAV image classification and the significance of machine vision in fire monitoring. Initially, the dataset used for fire detection and the data processing and enhancement techniques are introduced. Subsequently, the construction and architecture of the image classification model are detailed. The core of this study is to enhance the accuracy of model image recognition in complex forest environments by replacing optimizers, modifying the model architecture, and adding modules. Various models and optimizers are compared and analyzed, and the operations and significance of enhancement methods and attention mechanisms are explored. The aim is to improve training effectiveness through these strategies, thereby effectively supporting UAVs in forest fire detection.

关键词： UAV Forest fire detection Image classification Machine vision Model optimization

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Proceedings - 2024 3rd international conference on Computational Modelling, Simulation and optimization, ICCMSO 2024

Proceedings - 2024 3rd International Conference on Computati...

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3rd international conference on Computational Modelling, Simulation and optimization, ICCMSO 2024

ISBN: (纸本)9798350361391

The proceedings contain 77 papers. The topics discussed include: monitoring and prediction of household power consumption using Internet of Things and ARIMA;social media marketing: does it create impact on women entrepreneurs;transforming dentistry using artificial intelligence based innovations for advanced diagnostics and sustainable healthcare;cyber physical system for physical chessboard game on computer screen in a real time;multichannel image encoding for short time-series feature representation applied to system peak demand forecasting model;GSM based vehicle security theft control system;finite element simulation of T-shape branch using tube- hydroforming process;and optimizing air quality forecasts: integrating ARIMA with deep learning approaches.

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2024 3rd international conference on Sustainable Mobility applications, Renewables and Technology, SMART 2024

2024 3rd International Conference on Sustainable Mobility Ap...

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3rd international conference on Sustainable Mobility applications, Renewables and Technology, SMART 2024

ISBN: (纸本)9798331532925

The proceedings contain 77 papers. The topics discussed include: a novel asymmetric split-spoke-type variable flux memory machine;a novel asymmetric variable flux memory machine with hybrid-layer permanent magnets;a novel stator surface-mounted permanent magnet machine with asymmetric stator pole configuration;achieving sustainable software systems by reducing bloat and by promoting green practices in software engineering education;an efficient design optimization method for consequent-pole asymmetric rotor hybrid interior permanent magnet synchronous machine;design of gravity energy storage switched reluctance linear motor;newton-Raphson method using HHL algorithm for power flow quantum computing;and a new non-recursive analytical calibration approach for Li-ion ECMs based on voltage gradient and sigmoid function.

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Intelligent Decision-Making for Maintenance Assurance throughout the Lifetime of Helicopter Swarms 3

Intelligent Decision-Making for Maintenance Assurance throug...

引用

3rd conference on Fully Actuated System Theory and applications (FASTA)

作者： Wang, Yanan Zhang, Ke Jiang, Bin Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Peoples R China Natl Key Lab Helicopter Aeromech Nanjing 211106 Peoples R China

ISBN: (纸本)9798350373707;9798350373691

The utilization of intelligent algorithms for decision-making and optimization in the collaborative maintenance of helicopter swarm addresses the challenge of maximizing the reliability of swarm task execution under limited maintenance resources. Consequently, optimization of maintenance decisions has become a focal point of research both domestically and internationally. The problem of allocating maintenance resources under resource constraints, known as selective maintenance, can naturally be modeled as a Markov decision process. For solving this problem, employing multi-objective optimization algorithms is a logical choice. However, due to the large number of optimization decision variables involved in this practical problem, traditional algorithms may encounter difficulties. Reducing the search space of decision variables can alleviate this challenge. With this in mind, this study proposes a multi-objective optimization algorithm based on fuzzy theory. Finally, we validate the feasibility of the model and intelligent decision-making solutions through an illustrative example.

关键词： Selective Maintenance Maintenance optimization Reliability Helicopter Swarm Fuzzy Evolution Multi-objective optimization

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optimization of Visual SLAM for Mobile Robots in Complex Environments: Tight Coupling of Visual-Inertial Fusion and Efficient Loop Closure Detection Strategies 3

Optimization of Visual SLAM for Mobile Robots in Complex Env...

引用

3rd international conference on Robotics, Artificial Intelligence and Intelligent control (RAIIC)

作者： Fu, Bo Wei, Wei Guo, Zhiyuan Ren, Yuhan Dept Xian Univ Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9798350352634;9798350352627

This study tackles mobile robots' environmental perception challenges in complexity, presenting an advanced Visual-Inertial SLAM (VSLAM) technique that enhances accuracy, robustness, and real-time functionality. It bolsters visual odometry with ORB features for meticulous matching and selects keyframes, integrating IMU data for robust motion handling in low-textured scenes. Rear-end operations employ graph optimization and a bag-of-words-based loop closure, utilizing sliding window optimization and marginalization to curb accumulative errors, ensuring trajectory and map consistency. Experiments on KITTI, EuRoC, and TUM datasets surpass conventional methods like ORB-SLAM2 and VINS-Mono, trimming trajectory and mapping inaccuracies by 23.8% and 41.7%, respectively, with robust adaptability across motion modes and environments. System module timing analysis paves the way for real-time deployment on less powerful hardware. Future research directions include direct visual odometry, dynamic environment adaptation, multi-sensor fusion, and large-scale scene comprehension, pushing SLAM's frontier in intricate dynamics and empowering autonomous robot navigation.

关键词： Mobile Robots Visual SLAM Graph optimization Environmental Perception

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PID Parameter Tuning for Maglev Systems: Leveraging Genetic Algorithm and Grey Wolf optimization 3

PID Parameter Tuning for Maglev Systems: Leveraging Genetic ...

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3rd IEEE international conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Singh, Amandeep Singh, Aditya Ahlawat, Anshul Bhushan, Bharat Delhi Technological University Dept. of Electrical Engineering Delhi India

ISBN: (纸本)9798350387193

This work introduces a novel method for optimizing PID (proportional-integral-derivative) controllers in Maglev systems using two well-known optimization algorithms: Grey Wolf optimization (GWO) and Genetic Algorithm (GA). The importance of PID controllers in controlling the performance and stability of Maglev systems is described at the outset of the study. The process of using GA and GWO algorithms for parameter tuning is then presented, along with the effectiveness of these algorithms in optimizing PID controller parameters. The main tool used to implement these algorithms and simulate their use in a traditional PID model is MATLAB programming. Additionally, the mean-square error (MSE) performance criterion is used to evaluate the performance index, offering a thorough evaluation of control effectiveness through a variety of optimization methods. Through simulation studies, the effectiveness of the tuned PID controllers is thoroughly assessed, determining how well they can improve the robustness and dynamic response of the Maglev system. © 2024 IEEE.

关键词： Mean square error

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Improved Mountain Gazelle optimization for PID Tuning of MPPT Based Solar PV System 3

Improved Mountain Gazelle Optimization for PID Tuning of MPP...

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3rd IEEE international conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Veerasamy, Hemachandran Mouttou, Arounassalame Rathidevi, U. Puducherry Technological University Department of Electrical and Electronics Engineering Puducherry India

ISBN: (纸本)9798350387193

Recent advancements in the field of solar energy has made a huge revolution in power generation. Due to the erratic nature of the system, there is a need to extract the maximum available power from the solar photovoltaic system at a given time. To extract the maximum power, we use power electronic converters. This paper uses a dc-dc boost converter for maximum power point tracking (MPPT) of the solar photovoltaic (PV) system using a proportional-integral-derivative (PID) controller. The PID controller is tuned using the improved Mountain Gazelle optimization (MGO) algorithm. The performance of the controller is compared with other controllers tuned by optimization methods such as Genetic Algorithm (GA) and Grey Wolf optimization (GWO) algorithm. The simulation studies were carried out using MATLAB and the results are presented. © 2024 IEEE.

关键词： Three term control systems

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optimization of Three-Ring Concentric Circular Antenna Arrays for Maximum Side Lobe Level Reduction 3

Optimization of Three-Ring Concentric Circular Antenna Array...

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3rd IEEE international conference on Intelligent Techniques in control, optimization and Signal Processing, INCOS 2024

作者： Waly, Mohamed Ibrahm Majmaah University College of Applied Medical Scince Medical Equipment Technology Department Riyadh11952 Saudi Arabia

ISBN: (纸本)9798350361186

This study focuses on the perfect creation of concentric circular antenna arrays (CCAAs) regardless of the presence of a central feeding element. The main goal is to find the current excitation weights and ring radius that minimize side lobe level (SLL) as much as possible. These concentric circular antenna arrays can be utilized in various applications, including mobile cognitive radio ad hoc networks and smart grids. The Taguchi method was employed as the optimization strategy. Detailed numerical results indicate that the CCAA, when fed by a yield element, significantly lowers the SLL compared to a similar array without a central feeding element. Moreover, a specific CCAA configuration, consisting of 4, 6, and 8 components in three succeeding loops and a central feeding component, achieves the lowest SLL of -35.70 dB. © 2024 IEEE.

关键词： Feeding

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Construction Quality optimization and Adaptive control Algorithm Design of Intelligent Water Conservancy Project Based on Reinforcement Learning 3

Construction Quality Optimization and Adaptive Control Algor...

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

作者： Wang, Xiaoyong Chu, Dongdong Jiangsu Hydraulic Research Institute Yangzhou Jiangsu210000 China

ISBN: (纸本)9798350376173

In this paper, an intelligent optimization and adaptive control method based on RL (Reinforcement learning) is proposed to solve the key problems of construction quality optimization and control of water conservancy projects. Firstly, this paper analyzes the factors affecting the construction quality of water conservancy projects, points out the limitations of traditional control methods, and expounds the necessity and significance of introducing RL technology. On this basis, the construction quality optimization model based on RL is constructed, and the adaptive control algorithm is designed, and the effectiveness of the proposed method is verified by simulation experiments. The experimental results show that the RL model can learn independently and find the optimal construction strategy in different construction environments, and realize the adaptive optimization of construction quality. Compared with other methods, this method shows obvious advantages in improving construction quality and effectively reduces the occurrence of construction quality problems. At the same time, the adaptive control algorithm shows strong robustness and expansibility, and is suitable for water conservancy construction projects with different scales and complexity. This achievement not only improves the stability and reliability of construction quality, but also provides new technical support for the high-quality development of water conservancy projects. © 2024 IEEE.

关键词： Adaptive control algorithm Intelligent water conservancy project optimization of construction quality Reinforcement learning

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Research on the Application of Object Detection Algorithm Based on Neural Network in the Regulation and control of Intelligent Building Energy-saving Equipment 24

Research on the Application of Object Detection Algorithm Ba...

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3rd international conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML)

作者： Wang, Xinjun Chengdu Polytech Sch Urban Construct Chengdu Sichuan Peoples R China

ISBN: (纸本)9798400709777

To improve the regulation effect of intelligent building energy-saving equipment, an optimization regulation method for air conditioning system based on improved YOLOv5 personnel detection is proposed. Firstly, CBAM attention mechanism and EIOU loss function are introduced to improve YOLOv5 network. Then, based on personnel detection results of the improved YOLOv5, control optimization for air conditioning system is carried out from two aspects: variable refrigerant volume system and fresh air system. The experimental results show that the average precision and F1 score of the improved YOLOv5 algorithm for indoor personnel detection reach 98.62% and 0.95 respectively, which are significantly improved compared with Fast R-CNN and the original YOLOv5 algorithm. The improved YOLOv5 algorithm has a high reliability when applied to calculate personnel occupancy rate and personnel uniformity. The simulation results show that compared to the total power consumption under traditional control strategy, the energy-saving rates reach 64.39% and 8.13%, respectively, which indicates that the proposed method has certain practical value and is worth further research and promotion.

关键词： Object detection Air conditioning system Occupancy rate Regulation optimization

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