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We present a data modelling methodology, which introduces a novel biologically inspired universal generative modelling approach called Hierarchical Spatial Temporal State Machine (HSTSM).
This paper presents a general modelling methodology which utilises the higher bandwidth and number of signal levels of a pulse-multisine signal to estimate the battery dynamics and non-linear characteristics without the need of a 3D look-up table for the model parameters.
In this paper, we develop a new modelling methodology, which combines the fidelity of CFD models with the computational attractiveness of BEM-type models.
The modelling methodology, which has been designed to be applicable to any European country, is fully dynamic and based on an aggregated description of the building stock.
In order to determine the architecture of the SSB24, first we obtained CCS values using IM-MS and then applied our modelling methodology which in this case follows the pathway C (Figure 2).
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The reactor is nodalized to employ the lumped parameter modeling methodology, which is mathematically described by differential algebraic equations (DAEs).
demonstrated a novel integrative modeling methodology, which promises to enable researchers to build comprehensive models of individual cells (2).
Next we discuss the data modeling methodologies, which is followed by a data model description we used for the storage of the real-time temporal data of ANT+ sensors in the healthcare domain.
This paper presents a novel offline thermal error modelling methodology using finite element analysis (FEA) which significantly reduces the machine downtime required to establish the thermal response.
This enables a formal model-engineering methodology which combines the convenience of intuitive modeling in Timed Rebeca with formal verification in Real-Time Maude.
Two studies used modelling methodologies [ 35, 50].
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