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Titlebook: Advances in Neural Networks - ISNN 2017; 14th International S Fengyu Cong,Andrew Leung,Qinglai Wei Conference proceedings 2017 Springer Int

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樓主: tornado
11#
發(fā)表于 2025-3-23 11:59:25 | 只看該作者
https://doi.org/10.1007/978-1-349-02617-3tificial neural network model using well-known open software. The model shows the accuracy of 67%, making it possible to estimate next day behavior, select the best demand model, and estimate power demand for vehicle-to-grid trades.
12#
發(fā)表于 2025-3-23 14:04:01 | 只看該作者
0302-9743 ully reviewed and selected from 259 submissions. The papers cover topics like perception, emotion and development, action and motor control, attractor and associative memory, neurodynamics, complex systems, and chaos.. .978-3-319-59071-4978-3-319-59072-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
13#
發(fā)表于 2025-3-23 19:38:12 | 只看該作者
14#
發(fā)表于 2025-3-24 00:25:38 | 只看該作者
Stephen White,John Gardner,George Sch?pflinvery different commodities. To deal with such problems, we propose a LSTM (Long Short-Term Memory) Neuron Tensor Network architecture to encode the common features of all shops’ data and model the personalized features of each shop. Extensive experiments demonstrate that our method outperforms four baseline methods evaluated by recall metric.
15#
發(fā)表于 2025-3-24 06:19:29 | 只看該作者
16#
發(fā)表于 2025-3-24 08:35:57 | 只看該作者
Michael Waller,Bogdan Szajkowskiservation, we then present an algorithm to estimate data density without parameter input. Experiments on various datasets and comparison with other density kernels demonstrate the effectiveness of our algorithm.
17#
發(fā)表于 2025-3-24 10:54:49 | 只看該作者
https://doi.org/10.1007/978-1-349-02617-3riments are carried out based on huge amounts of historical data. The experimental results demonstrate the effectiveness and superior abilities of the arctan-activated WASD neural network for predicting the Dow Jones Industrial Average.
18#
發(fā)表于 2025-3-24 17:17:31 | 只看該作者
https://doi.org/10.1007/978-1-349-02617-3ed via Lyapunov analysis. The proposed observer can be used in various motion control scenario, such as target tracking, trajectory tracking, path following, formation control, and even sideslip angle identification, not only for fully-actuated marine vehicles but also for under-actuated marine vehicles.
19#
發(fā)表于 2025-3-24 22:37:58 | 只看該作者
20#
發(fā)表于 2025-3-25 00:33:27 | 只看該作者
Online Multi-threshold Learning with Imbalanced Data Streamion of ISS originally given by Teel, employs saturated controls to enforce ISS of the dynamics, without resorting to input/output linearization techniques, and thus avoiding the need to deal with critically stable or locally asymptotically stable zero-dynamics. The aforementioned techniques- saturat
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