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Titlebook: Nature of Computation and Communication; 7th EAI Internationa Phan Cong Vinh,Nguyen Huu Nhan Conference proceedings 2021 ICST Institute for

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樓主: Fixate
41#
發(fā)表于 2025-3-28 14:55:50 | 只看該作者
Numerical Results via High-Order Iterative Scheme to a Nonlinear Wave Equation with Source Containider iterative scheme is constructed by the finite-difference method. Finally, a numerical example is presented to evaluate the errors between the exact solution and the approximate solution. The numerical results show that the errors are decreasing as the fineness of meshes is increasing.
42#
發(fā)表于 2025-3-28 21:34:52 | 只看該作者
1867-8211 ion, ICTCC 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually.. The 17 revised full papers presented were carefully selected from 43 submissions. The papers of ICTCC 2021 cover formal methods for self-adaptive systems and discuss natural approaches and techniques
43#
發(fā)表于 2025-3-28 23:00:53 | 只看該作者
44#
發(fā)表于 2025-3-29 04:27:19 | 只看該作者
,Adaptive Deep Learning Technique to Predict Student’s Graduation Results,age academic points data of the six main semesters out of a total of eight main semesters of students to predict their graduation result with the accuracy of about 90.53%. To objectively evaluate the effectiveness of the proposed method, the results of the proposed method, which compared with the other methods, are better than the other methods.
45#
發(fā)表于 2025-3-29 08:49:04 | 只看該作者
46#
發(fā)表于 2025-3-29 15:06:46 | 只看該作者
47#
發(fā)表于 2025-3-29 18:37:00 | 只看該作者
48#
發(fā)表于 2025-3-29 20:03:20 | 只看該作者
Predicting Vietnamese Stock Market Using the Variants of LSTM Architecture,g that the Bidirectional LSTM architecture gives good results in short- and long-term prediction for the Vietnamese stock market. In conclusion, the LSTM architecture is very suitable for the stock prediction problem in the long- and short- term.
49#
發(fā)表于 2025-3-30 01:44:00 | 只看該作者
Dimensionality Reduction Performance of Sparse PCA Methods,by experimentally evaluating the dimensionality reduction performance of the two methods mentioned above on ten real-world data sets. Difference from previous beliefs, the experimental results show that the dimensionality reduction performance of the PCA and SPCA methods is competitive.
50#
發(fā)表于 2025-3-30 04:37:42 | 只看該作者
Implementation of the Motion Controller for an Omni Mobile Robot Using the Trajectory Linearizatione effectiveness and feasibility. From the simulation results, the proposed controller achieves superior performance such 20% better tracking error, 10% faster transient period and converge to finite time.
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