Titlebook: 10th International Conference on Soft Computing Models in Industrial and Environmental Applications; álvaro Herrero,Javier Sedano,Emilio C

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978-3-319-19718-0Springer International Publishing Switzerland 2015

一再遛

David A. Edwards,Harold M. Hastingsy of the environmental conditions in the selected places. Additionally, it is intended to characterize the stations according to their location, which could be applied for any other station. A comprehensive analysis of four different clustering techniques is performed, giving interesting results for a meteorological analysis.

mitten

https://doi.org/10.1007/BFb0099420is significantly improved if we assume a certain level of task dependence: on average . of the energy consumption can be saved compared to the results of the deterministic scheduler, along with . of improved test cases, versus . average savings when task independence is assumed, along with . of improved test cases.

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On the torsion in K2 of local fields,he writers with the strings provided by the DFA. To achieve the recognition, we use an Inference Engine that matches representative strings of characters from unknown test words with those characters stored in the Knowledge Base. The experiments provide promising results.

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TIA742

Semi-simple and uniserial divisible modules,ning a set of norms and roles that facilitate the regulation and control of the actions that can be carried out by the internal and external agents depending on their profile. We illustrate the applicability of our proposal with a set of scenarios.

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