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Coal moisture automatic online control has important practical significance on the actual production, which is realized by analyzing and modelling the existing coal moisture control system. In this research, experimental training data are used RHM (Resembling by Half-Mean) to exclude abnormal values. The study adopts RBF (Radical Basis Function) neural network for coal moisture control system to model,...
The MapReduce programming model has introduced simple interfaces to a large class of applications. Its easy-to-use APIs and autonomic parallelization are attracting attentions from scientific community. However, current MapReduce-style scientific frameworks focus more on the most popular MapReduce applications that can be easily partitioned and involve little communication across map or reduce tasks...
MapReduce programming model is widely used for large scale and one-time data-intensive distributed computing, but lacks flexibility and efficiency of processing small incremental data. IncMR framework is proposed in this paper for incrementally processing new data of a large data set, which takes state as implicit input and combines it with new data. Map tasks are created according to new splits instead...
This paper studies the optimization problem of minimizing resource rental cost for running elastic applications in cloud while meeting application service requirements. Such a problem arises when excessive generated data incurs significant monetary cost on transfer and inventory in cloud. The goal of planning is to make resource rental decisions in response to varying application progress in the most...
In this paper, we propose an autonomic management framework (ASGrid) to address the requirements of emerging large-scale applications in hybrid grid and sensor network systems. To the best of our knowledge, we are the first who proposed the autonomic sensor grid system concept in a holistic manner targeted at non-trivial large applications. To bridge the gap between the physical world and the digital...
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