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Titlebook: Enterprise Information Systems VII; Chin-Sheng Chen,Joaquim Filipe,José Cordeiro Conference proceedings 2006 Springer Science+Business Med

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樓主: Fillmore
31#
發(fā)表于 2025-3-26 21:51:16 | 只看該作者
32#
發(fā)表于 2025-3-27 01:40:20 | 只看該作者
,Taking the Mic: Hip Hop’s Call for Change,ices, but also on those of its business partners. This paper reviews the conditions promoting and inhibiting benefit realization from IOS, presents two examples of companies that successfully addressed those conditions, and examines why some organizations find it challenging to imitate these examples.
33#
發(fā)表于 2025-3-27 06:51:19 | 只看該作者
https://doi.org/10.1057/9781137367884ithm takes advantage of the absence of overhead in unstructured P2P networks and minimises the required traffic for all operations with the use of an intelligent sampling scheme. Detailed experimental results show the efficiency of the proposed algorithm compared to an existing baseline algorithm.
34#
發(fā)表于 2025-3-27 11:01:21 | 只看該作者
35#
發(fā)表于 2025-3-27 14:56:31 | 只看該作者
BUILDING SUCCESSFUL INTERORGANIZATIONAL SYSTEMSices, but also on those of its business partners. This paper reviews the conditions promoting and inhibiting benefit realization from IOS, presents two examples of companies that successfully addressed those conditions, and examines why some organizations find it challenging to imitate these examples.
36#
發(fā)表于 2025-3-27 18:30:42 | 只看該作者
MUSICAL RETRIEVAL IN P2P NETWORKS UNDER THE WARPING DISTANCEithm takes advantage of the absence of overhead in unstructured P2P networks and minimises the required traffic for all operations with the use of an intelligent sampling scheme. Detailed experimental results show the efficiency of the proposed algorithm compared to an existing baseline algorithm.
37#
發(fā)表于 2025-3-27 22:22:41 | 只看該作者
AN APPLICATION OF NON-LINEAR PROGRAMMING TO TRAIN RECURRENT NEURAL NETWORKS IN TIME SERIES PREDICTIOhigh. The objective of this work is to show that the use of some non-linear programming techniques is a good choice to train a Neural Network, since they may provide suitable solutions quickly. In the experimental section, we apply the models proposed to train an Elman Recurrent Neural Network in real-life Time Series Prediction problems.
38#
發(fā)表于 2025-3-28 02:45:31 | 只看該作者
39#
發(fā)表于 2025-3-28 09:33:15 | 只看該作者
40#
發(fā)表于 2025-3-28 14:10:33 | 只看該作者
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