Placements are of utmost significance to academic organizations and college students. A strong foundation for the professional field is built up for the student beforehand, and a positive placement report gives a scho...
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This article delves into an innovative radar working pattern recognition algorithm based on multi-layer perceptron (MLP). Through carefully designed optimization algorithms, we systematically searched and determined t...
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ISBN:
(纸本)9798400716959
This article delves into an innovative radar working pattern recognition algorithm based on multi-layer perceptron (MLP). Through carefully designed optimization algorithms, we systematically searched and determined the optimal MLP network structure to solve the radar operating pattern recognition problem. In a detailed simulation experiment, we carefully analyzed the effects of various network parameters, including the number of network layers, number of neurons, learning rate, and batch rate. The experimental results show that the MLP network can exhibit optimal performance when the number of layers is 5, the number of neurons is 512, the learning rate is 0.006, and the batch rate is 10. This discovery provides us with a highly promising solution to the problem of radar working pattern recognition.
The Class Imbalance Problem (CIP) is a critical challenge in machine learning, particularly in applications such as medical diagnosis and fraud detection, where minority classes are underrepresented but crucial. This ...
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With the accelerated urbanization process and the continuous growth of power demand, substations are a critical component of the power system. However, the main noise sources in substations, such as main transformers,...
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ISBN:
(纸本)9798350366105;9798350366099
With the accelerated urbanization process and the continuous growth of power demand, substations are a critical component of the power system. However, the main noise sources in substations, such as main transformers, reactors, and cooling fans, have a significant impact on the surrounding environment. Therefore, this paper proposes an optimization design method for ventilation and noise reduction in substations based on deep learning. Firstly, the finite element method is used to simulate the ventilation and noise data of substations under multiple operating conditions to obtain sufficient samples. Secondly, the construction of the Convolutional Neural Network (CNN) model is completed, and the obtained data is used for model training. Finally, the optimization solution of parameter design is achieved using the SAC algorithm. The results show that the designed parameters for substations using this method can effectively reduce noise and comply with national standards.
An on-site fault remote intelligent diagnosis and warning method for electricity information collection terminal based on deep learning is proposed to address the complex forms of faults and the difficulty of manual i...
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ISBN:
(纸本)9798350378467;9798350367676
An on-site fault remote intelligent diagnosis and warning method for electricity information collection terminal based on deep learning is proposed to address the complex forms of faults and the difficulty of manual inspection in meeting operation and maintenance needs. Firstly, model the fault diagnosis and warning system for the electricity information collection terminal, including the state monitoring layer, prediction and diagnosis layer. Then, the deep forest algorithm is improved by setting weights and applied to remote real-time intelligent diagnosis of faults in electricity information collection terminals. Finally, a BLSTM-GRU model is constructed by combining bidirectional long short-term memory network (BLSTM) and gated recurrent unit (GRU) networks, and applied to fault prediction of electricity information collection terminals, as well as issuing warnings based on the prediction results. Based on the selected data samples, experimental analysis is conducted on the proposed method, and the results shows that its fault diagnosis accuracy reaches 96.03%, and the fault warning results are reliable.
Due to their diverse species and complex morphology, the automatic identification of marine plankton has always been a challenging task. In response to this problem, this study proposes an innovative deep learning-bas...
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The Peer-to-peer (P2P) lending platform allows borrowers to connect directly with lenders outside traditional banking systems. Therefore, for the sustainability of these platforms, they must accurately assess the cred...
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intelligent big data financial management is a new industry that uses intelligent technology and big data analysis to process and manage financial data. As a key problem in this industry, how to find the optimal solut...
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This paper introduces an innovative method for improving solar power prediction accuracy by integrating realtime weather forecasting, advanced machine learning techniques, and hybrid modelling frameworks. The proposed...
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As edge-based decisions continue to grow in demand, organizations are increasingly seeking user data, raising privacy concerns. Federated learning (FL) addresses this problem but is typically dependent on computationa...
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