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Short term electricity load forecasting is nowadays, of paramount importance in order to estimate next day electricity load resulting in energy save and environment protection. Electricity demand is influenced (among other things) by the day of the week, the time of year and special periods and/or days such as Ramadhan, all of which must be identified prior(More)
The study of multiple classifier systems has become recently an area of intensive research in pattern recognition in order to improve the results of single classifiers. In this work, two types of features combination for handwritten Arabic literal words amount recognition, using neural network classifiers are discussed. Different parallel combination(More)
This paper describes the constituents, as well as, the general layout of a collaborative environment dedicated to the maintenance of steam turbines. The core component of the environment is a shared ontology of the domain. The developed ontology contains information on every component, its relationship with the upper and lower component class, as well as a(More)
SUMMARY This paper investigates the problem of robust fault detection observer design for nonlinear Takagi–Sugeno models with unmeasurable premise variables subject to sensor faults and unknown bounded disturbance. The main idea is to synthesize a robust fault detection observer by means of a mixed H =H 1 performance index. The considered observer is used(More)
Electrical load is a major input factor in economic development. To support economic growth and meet the demands in the future, the load forecasting has become a very important task for electric power stations. Therefore, several techniques have been used to accomplish this task. In this study, our interest is focused on the multiple regression approach,(More)
In this paper, we present the results obtained by our ontology matching system XMap++ within the OAEI 2014 campaign. XMap++ is a scalable ontology alignment tools capable of matching large scale ontology. This is our second participation in the OAEI, and we can see an overall improvement on nearly every task. 1 State, purpose, general statement XMap(More)
Predictive Functional Control (PFC), belonging to the family of predictive control techniques, has been demonstrated as a powerful algorithm for controlling process plants. The input/output PFC formulation has been a particularly attractive paradigm for industrial processes, with a combination of simplicity and effectiveness. Though its use of a lag plus(More)