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Aerobic reactors are a common device to clean waste water from many different sources. During their working phase a population of bacteria consumes the organic matter and oxygen to produce carbon dioxide. In this work a reactor controlled using PID controllers is analysed. Detecting the end of the aerobic process is a key issue to maximize the efficiency of the reactor, as fixed times are usually...
Nowadays due to the rising price of the energy, many techniques in all fields are used with the aim to reduce the energy consumption. These techniques can be new or traditional. Probably, in other time, their installation were not profitable. In this sense, the buildings heat installations include components to optimize its consumption. As an example, recently, in the rural Spanish territory, the...
This study presents a novel bio-inspired knowledge system, based in closed loop tuning, for the calculation of the Proportional-Integral-Derivative (PID) controller parameters. The aim is to achieve automatically the best parameters according with the work point and the dynamics of the plant. For it, in our study, several typical expressions and systems have been taken into account to build the model...
In this research work a neural network based technique to be applied on condition monitoring and diagnosis of rotating machines equipped with hydrostatic self levitating bearing system is presented. Based on fluid measured data, such pressures and temperature, vibration analysis based diagnosis is being carried out by determining the vibration characteristics of the rotating machines on the basis...
There are several successful approaches dealing with imbalanced datasets. In this paper, the Fuzzy Labeled Neural Gas (FLNG) is extended to work with this type of data. The proposed approach is based on assigning two different values in the learning rate depending on the data vector membership of the class. The technique is tested with several datasets and compared with other approaches. The results...
The self-organizing map (SOM) is a suitable algorithm for data visualization but its topological preservation makes the vector quantization non-optimal. This paper aims to improve the lack of quantization precision in the SOM. An energy cost function based on two different kernels is formulated to obtain a batch algorithm. A bivariate normal distribution is assumed to weight the topological preservation...
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