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Titlebook: Data Mining and Big Data; First International Ying Tan,Yuhui Shi Conference proceedings 2016 Springer International Publishing Switzerland

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發(fā)表于 2025-3-25 06:14:32 | 只看該作者
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發(fā)表于 2025-3-25 08:17:34 | 只看該作者
Controlling and Directing Accreditationhe unified management of trajectories, underlying geographical space and social relationships for massive moving objects. A bulk of . . and corresponding . are also proposed to facilitate geo-social queries on moving objects.
23#
發(fā)表于 2025-3-25 13:54:17 | 只看該作者
Enhanced Versions of the CBO Algorithmze the possibility of collisions between crossing and through traffic, Precaution Areas (PAs) were laid out to remind mariners where the crossing and encountering situations may occur in the strait. Recent advances in telemetry technology help to collect ships movement data more efficiently and accu
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發(fā)表于 2025-3-25 18:50:27 | 只看該作者
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發(fā)表于 2025-3-25 20:10:24 | 只看該作者
Colliding Galaxies: The Discovery,that the current models used in liver transplantation prognosis seems to be less accurate. In this paper, we propose a highly improved model for predicting three month post liver transplantation survival. We performed experiments on the United Nations Organ Sharing dataset, with a 10-fold cross-vali
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發(fā)表于 2025-3-26 04:03:09 | 只看該作者
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發(fā)表于 2025-3-26 05:36:29 | 只看該作者
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發(fā)表于 2025-3-26 11:46:45 | 只看該作者
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發(fā)表于 2025-3-26 15:44:20 | 只看該作者
Jurisdiction and the Dutch Collective Actionand artificial neural networks to predict compressed air energy consumption in a manufacturing facility is presented. Predictions made using DM were consistently more accurate than those found using traditional approaches when the training period was greater than two months.
30#
發(fā)表于 2025-3-26 17:48:12 | 只看該作者
Exploding and Peculiar Galaxies,e year. Our main objective is to device a light weight prediction for the bulk of companies with fair accuracy, useful enough for algorithmic trading. We present a minimal discussion on these classical models followed by our Spark RDD based implementation of the proposed fast forecast model and some results we have obtained.
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