regression model
This study identifies representative sensors for monitoring fan performance by analyzing vibration data collected from piezoelectric sensors during various operational modes. The dataset, which includes measurements at a rate of 300 samples/sec from 10 sensors, covers six modes of operation: Maximum Speed, Maximum Speed with Oscillation, Minimum Speed, Minimum Speed with Oscillation, Minimum to Maximum Speed, and a comprehensive dataset combining all modes.
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Transistor models are crucial for circuit simulation. Reliable design of high-performance circuits requires that transistor characteristics are adequately represented, which makes accurate and fast models indispensable. Scattering (or S-)parameters are perhaps the most widely used RF characteristics, employed in the design and analysis of linear devices and circuits for calculation of the input and output impedance, isolation, gain, as well as stability, all being important performance figures for small-signal or low-noise amplifiers.
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Shannon’s Index of Difficulty (ID), reputable for quantifying the perceived difficulty of pointing tasks as a logarithmic relationship between movement-amplitude (A) and target-width (W), is used for modelling the corresponding observed movement-times (MT_O) in such tasks in controlled experimental setup.
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To train the machine learning model, a dataset was generated containing data for «Budennovskoye» field, part of which is shown in title figure. (AR and SP are given for 90 centimeter intervals, for which, in turn, the actual values K_fpo. obtained by pumping out (pump out) was determined. As a result, the input variable set consisted of 19 values, including the rock code (AR, SP). The target column isK_f_pump_out .
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