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Accurate predictions of both process-execution time and process status are crucial for the development of an intelligent enterprise information system (EIS). We have developed new automated learning-based process-execution time-prediction and process status-prediction methods that can be embedded into an EIS. Process-execution time prediction is a regression problem and state-of-the-art (baseline)...
The autonomic management of large-scale distributed systems now allows performance improvement, availability, and security, while simultaneously reducing the effort and skills required of system administrators. One way that systems can support these abilities is by relying on a continuous monitoring service to keep track of the states of the targeted systems. However, it is challenging to achieve...
In many industries, there are serious safety concerns related to the used of flammable gases in both indoor and outdoor environments. Any accidental and dispersion of toxic gases were always major hazards for public health and safety that industries had to deal with. Accident can happen due to many reasons, such as damaged pipes, leakage at storage tank, or while the gas being transport. For these...
The fluctuation of oil prices attracts the great attention of the world. However, the prediction of oil prices is very difficult because the oil price system is so complex. In this paper, AR-GMDH algorithm and AC algorithm are adopted to forecast oil prices. The validity and feasibility of self-organizing data mining are manifested by the comparisons of the prediction result with that of conventional...
Software fault prediction models play an important role in software quality assurance. They identify software subsystems (modules,components, classes, or files) which are likely to contain faults. These subsystems, in turn, receive additional resources for verification and validation activities. Fault prediction models are binary classifiers typically developed using one of the supervised learning...
Through statistic analysis on the donor site sequences in the dataset of HS3D, the rules that the bases appear in the adjacent sites around the splice sites are used for constructing motifs, which are then utilized as the attributes of the DNA sequences. And by setting the value of each attribute the literal sequences are transformed into quasi numeric vectors, based on which a decision tree (C4.5...
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