Data-driven modelsare based on data. Machine and statistical learning algorithms are used for building such models from data. For this, data need to be explored, usually several models are considered, and finally a model is built through the application of a particular algorithm. This model will...
Rowley, C. W., et al. (2004). "Model reduction for compressible flows using POD and Galerkin projection." 189(1-2): 115-129.
This study presents an improved data-driven Model-Free Adaptive Control (MFAC) strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft...
In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT incl...
Business Intelligence Database Systems can be categorized into two major types: model - driven and data - driven. 商业智能数据库系统可以分为两大类: 模型驱动和数据驱动的. 互联网 In discussing successful projects, we saw two classes of approaches, data - driven design and framework - based desig...
Hence, it is suggested that the EEF should be lined up for maintenance and reliability monitoring. Furthermore, the impact of the harsh environmental conditions (p and q) which were captured in the model and given the fixed values [0.4700 and 0.0180] were modelled. 展开 ...
The above also indicates that if ideal theory or a spatially homogeneous model is unable to provide reliable predictions for a particular location, then spatial data will need to be collected and assimilated effectively into models to learn the features of local dynamics, whether this be for finer...
There are two objectives to this study. The first objective is to develop a hybrid mapping approach that combines the data-driven model and IDW interpolation to produce the PM10concentration maps from global meteorological data. The second objective is to employ this approach to construct the monthl...
We argue that this agent-based model is correct if it is able to reproduce a specific set of macroscopic properties of the different collaboration networks, namely degree distribution, path length distribution, distribution of community sizes, that are not used for the calibration of the model. ...
In this paper, a novel data-driven model-free adaptive predictive control method based on lazy learning technique is proposed for a class of discrete-time single-input and single-output nonlinear systems. The feature of the proposed approach is that the controller is designed only using the input...