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Identification of machine condition is crucial to reduce machine downtime and scrap parts in the manufacturing industries. In this paper, we propose a novel methodology to identify life stage and estimate machine wear. The proposed framework is based on stage identification using Support Vector Machines (SVMs) and machine wear estimation using AutoRegressive Moving Average with eXogenous inputs (ARMAX)...
In complex system, the safety incidents and accidents often result in a great loss of personnel and equipment. However, the traditional alarming system and applications might not capable to meet the requirements of system safety control. In engineering applications, the lack of accidents samples impacts the accuracy of predictions for potential accidents, how to use a small amount of observational...
This paper researches on ontology auto-extension, which is a hot issue of semantic web. In this paper, technology related to information processing is used to automatically extend ontology instances from free text. Firstly, three tasks are identified after analyzing on ontology auto-extension. Secondly, a new binary tree (BT) is constructed based on the ontology taxonomy, and then it is used as the...
Technical indicators are very important tools in the analysis of securities investment. Closing prices and volume of business are basic index, and they compose many complex technical index. In this paper, we represent the daily closing prices and daily volume of business as input vector, and construct 9 projects according different input vector. After 9 contrast experiments with support vector machines,...
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