the use of machine learning methods in fiberoptic information transmission systems (FOITS) is considered. the article discusses the basic operating principles of fiber optic systems and the problems they face, such as...
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Deep learning techniques have been widely applied to remote sensing image detection tasks. this paper proposes an improved method based on YOLOv5, named CI-YOLOv5 (Class Increment YOLOv5), which aims to achieve increm...
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Voltage control in low-observable distribution networks faces significant uncertainty challenges. In this paper, an uncertainty-aware voltage control method based on the fusion of Bayesian deep learning and probabilis...
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Withthe construction of new-type power systems, the proportion of renewable energy access continues to increase, and the uncertainty of the power grid increases. the current power grid dispatch plan based on physical...
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How to plan the vehicle path efficiently and accurately is a key problem in route planning. To solve this problem, in this paper, an Algorithm combining Ant Colony Algorithm (ACA) and Proximal Policy optimization (Pro...
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this study proposes an AI-based optimization approach for civil aviation passenger and cargo cabin design, focusing on maximizing space utilization, structural integrity, comfort, and energy *** combining deep learnin...
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Edge detection is one of the core technologies in digital image processing and computer vision, and has been widely applied in fields such as image recognition and remote sensing image processing. this article propose...
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ISBN:
(纸本)9798331530372;9798331530365
Edge detection is one of the core technologies in digital image processing and computer vision, and has been widely applied in fields such as image recognition and remote sensing image processing. this article proposes an optimization scheme for edge detection algorithm, which collects image information through binocular cameras and caches it in memory. After grayscale transformation preprocessing, the classic SOBEL algorithm and optimized SOBEL algorithm are used to extract edge information, obtain binary images, and display them on the LCD screen in real time. through practical testing, the optimized algorithm can effectively solve the problem of detecting edges that are too coarse in the original algorithm, and improve the accuracy of detection and positioning. this system can be widely applied in fields such as medical imaging and autonomous driving.
the industrial production process is becoming increasingly complex, and the requirements for quality assurance are becoming higher. Building a fault identification model is the focus of this study. this paper attempts...
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ISBN:
(纸本)9798350375084;9798350375077
the industrial production process is becoming increasingly complex, and the requirements for quality assurance are becoming higher. Building a fault identification model is the focus of this study. this paper attempts to propose a model incorporating mixed sampling and machine learning techniques, compare to select the optimal model to achieve production line fault alarm. In addition, We use simulated annealing algorithm to find the optimal solution for personnel allocation based on the relationship between factors such as length of years of service, production line, and output, helping factories achieve efficient allocation of workers.
In order to improve the intelligence of modern hospital logistics transmission system, a medical track logistics control system based on digital twins was designed to improve the efficiency of logistics transmission a...
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ISBN:
(纸本)9798350375084;9798350375077
In order to improve the intelligence of modern hospital logistics transmission system, a medical track logistics control system based on digital twins was designed to improve the efficiency of logistics transmission and provide a supporting application platform for the track logistics system. Platform from mechanical structure, to hardware control system, and then to digital twin system, a full range of independent research and development;the proposed twin model construction method extends the application of digital twin technology in the field of intelligent manufacturing. Finally, the test shows that the system can effectively complete the logistics and transportation tasks, and can achieve the virtual-real contrast, improve the system operation and maintenance efficiency.
Accurately predicting web traffic is crucial for optimizing website performance and understanding user behavior. this study investigates various machine learning and statistical models to forecast web traffic trends. ...
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ISBN:
(纸本)9798350367782;9798350367775
Accurately predicting web traffic is crucial for optimizing website performance and understanding user behavior. this study investigates various machine learning and statistical models to forecast web traffic trends. We apply a range of algorithms, including XGBoost, Random Forest, SARIMA, ARIMA, Prophet, and Moving Average with Seasonal Index, to two distinct datasets: "Daily Website Visitors" and "Future Traffic to Wikipedia Pages." the datasets are preprocessed and analyzed to uncover underlying trends and seasonal patterns, with models evaluated using key performance metrics such as MSE, RMSE, and MAPE. Our results demonstrate that the Moving Average model with Seasonal Index outperforms other models in terms of accuracy, achieving 95.87% accuracy on the "Daily Website Visitors" dataset and 98.23% accuracy on the "Future Traffic to Wikipedia Pages" dataset. these findings highlight the importance of leveraging advanced machine learning techniques alongside traditional statistical methods to improve web traffic forecasting, providing valuable insights for website optimization and digital marketing strategies.
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