Some applications such as sensor networks, internet traffic analysis, location-based services, and health measurements are always required for considering unbounded, fast, large-volumes, continuous, even for distribut...
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ISBN:
(纸本)9783642394799;9783642394782
Some applications such as sensor networks, internet traffic analysis, location-based services, and health measurements are always required for considering unbounded, fast, large-volumes, continuous, even for distributed stream data. It's a better way to use synopsis as a list of partial summaries of unknown item sets in order to reduce the memory space usage, let it can afford to process so fast and huge incoming data. Normally, different quantity of item set leads to different summaries, especially for Top-k operator which as a partial preprocess over synopsis. Therefore, we proposed smooth synopsis that dynamically assigns a numeral interval to resolve the items set, in order to maintain a more accurate approximate answers' list from partial Top-k processing. In particular, we proposed an algorithm (called sfi algorithm) to mine the most frequent items by a more adaptive and fast way in specific stream resources. Finally, our experimental results demonstrate the accuracy and efficiency of our approximation techniques.
It is shown that the effects of olfactory sensor drift can be counteracted by appropriately selecting the features that characterise the sensor responses. To this end, a supervised version of the fuzzy isodata (sfi) a...
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It is shown that the effects of olfactory sensor drift can be counteracted by appropriately selecting the features that characterise the sensor responses. To this end, a supervised version of the fuzzy isodata (sfi) algorithm is adopted. In addition to selecting features, the sfi algorithm computes both the memberships of patterns in classes, and the shape of classes. The output of the sfi is then used by a fuzzy k-nearest neighbour algorithm to identify unknown odours.
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