flavonoids
发表于 2025-3-25 03:28:00
Commercial Banking Risk Managementented to solve the problem that there is not effective method for reciprocating compressor valve fault detection. The Local Wave method was used to decompose vibration signals, which acquired from valves surface, into sub-band signals. Then the higher-order statistics were calculated as the input fe
semble
发表于 2025-3-25 11:24:02
Commercial Banking Risk Management states are classified by the work with ANN. The derived features of the signal, pitch, and loudness are quantitatively contributed to the classification of emotions. Firstly we analyze the acoustic elements for using as emotional features and the elements are evaluated by ANN classifier. Secondly,
Aura231
发表于 2025-3-25 12:59:04
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Dappled
发表于 2025-3-25 18:18:46
Leonidas Zelmanovitz,Bruno Meyerhof Salamaich has enhanced generalization performance, operates in a reduced principal component analysis (PCA) space. SVM is a powerful supervised learning algorithm, which is rooted in statistical learning theory. SVM has demonstrated high generalization capabilities in many pattern recognition problems. In
厨师
发表于 2025-3-25 22:49:17
https://doi.org/10.1007/978-3-031-45289-5 date many linear discrimination methods have been put forward. Despite these efforts, there persist in the traditional PCA and LDA some weaknesses. In this paper, we propose a new Line-based methodes called Line-based PCA and Line-based LDA that can outperform the traditional PCA and LDA methods. A
Capture
发表于 2025-3-26 02:43:12
Shalina Daved,Clare Merrifield,Michael Salibnetwork models are developed to recognize the system. One is a back propagation neural network to recognize ideal system under equilibrium status, and the other is a counter propagation model to recognize real system with probe vehicle data. By recognizing ideal system, it turn out that neural netwo
abduction
发表于 2025-3-26 04:40:52
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CONE
发表于 2025-3-26 10:19:32
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separate
发表于 2025-3-26 12:59:50
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bacteria
发表于 2025-3-26 20:19:00
XVA in the Wake of the Financial Crisisd on the maximum/minimum of color component between the three components (R,G,B) of a pixel. The proposed algorithm has less number of features, and the change of illumination, etc. is also taken into account.