Aiming at the problems of complex fault diagnosis and slow processing speed of the current special vehicle electro-hydraulic system, this paper proposes an electro-hydraulic fault diagnosis system for special vehicle ...
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ISBN:
(纸本)9798400708305
Aiming at the problems of complex fault diagnosis and slow processing speed of the current special vehicle electro-hydraulic system, this paper proposes an electro-hydraulic fault diagnosis system for special vehicle based on RBF neural network. the improved convolutional neural network is used to extract the original data features of the special vehicle electro-hydraulic system, and then the extracted data features are sent to the RBF neural network for training, which can greatly reduce the training time, and the extracted features are in the underfitting state at this time, thereby reducing the risk of overfitting. the experimental results on the test samples show that the improved system can quickly and accurately locate the fault, and give the corresponding expert maintenance advice, which has certain reference value for the health management of special vehicles.
In this paper, we implement a hybrid combustion model which incorporates the fire simulation and solid burning together. To achieve real-time performance, GPU is used to solve the Navier-Stokes equations with CUDA pro...
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Multi controller deployment in Software-Defined Networking plays a pivotal role in maximizing network resource utilization. However, the existing deployment strategies cannot consider both latency and load, directly d...
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the FC-AE-ASM (Fibre Channel-Avionics Environment-Anonymous Subscriber Message) data acquisition and forwarding system collects and forwards FC link data. As it's core and foundation, the software provides a stron...
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this paper presents a system for real-time visualization of very large image data sets using ondemand loading and dynamic view prediction. We use a robust image representation scheme for efficient adaptive rendering a...
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ISBN:
(纸本)9780769529837
this paper presents a system for real-time visualization of very large image data sets using ondemand loading and dynamic view prediction. We use a robust image representation scheme for efficient adaptive rendering and a perspective view generation module to extend the applicability of the system to panoramic images. We demonstrate the effectiveness of the system by applying it both to imagery that does not require perspective correction and to very large panoramic data sets requiring perspective view generation. the system permits smooth, real-time interactive navigation of very large panoramic and non-panoramic image data sets on average personal computers without the use of specialized hardware.
Automatic and accurate segmentation of multi-object organs from magnetic resonance images (MRI) is a critical step in clinical diagnosis and treatment. this is still an open problem due to many difficulties, such as t...
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Anti-missile operation is an important military operation related to the survival of troops, and aerospace information plays a huge role in supporting anti-missile operations. this paper analyses the specific process ...
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Teaching quality has always been the focus in the field of education. computer vision is used to analyze the students' part of the classroom video, detect the students' heads, and provide data support for clas...
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this paper uses machine learning to predict the second-hand car trading cycle. In order to enhance the expressivity of the model, we processed the original data by merging data, dividing data into boxes, creating new ...
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this paper aims to connect the missing links with a web-based solution where-in a person, namely the Reporter can register their complaint in about 30-40 words describing the condition of the animal in concern. On fin...
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