The structure of input data and error discovered through fuzzy clustering is captured in the form of a collection of fuzzy clusters, which helps eliminate (compensate) error produced by the global model.
Our method named the dual subspace projections (DSP) embeds high-dimensional data in an optimal low-dimensional space, which is learned with a few user-supplied constraints and the structure of input data.
The ROMP scheme employs the random linear projections, which can basically preserve the structure of input signals that are usually sparse in some basis (e.g., time domain).
In standard formulations, such as Michael Porter's "Five Forces" (Porter 1980), competition is determined primarily by the structure of input and end-user markets.
A data handler is used to describe the structure of input data and to deal with data load and removal events after the data handler is associated (bound) to the chart.
In the designing of neuro-fuzzy hybrid model, the structure of optimized inputs was determined by a trial-and-error process.
The hypothesis is that such a system will be able to organize itself appropriately (depending on the structure of its inputs) without substantial additional information being "built-in" from the start.
For example, in multiple input laminar flow cells, if there is variance in the structure of the input channels or the length of the tubing leading from the reservoir the width and flow rate of each lane in the main channel may vary slightly.
Therefore, the resulting solution corresponds to a minimal square error, while at the same time it maintains the structure of the input data.
Finally, we describe the program organisation of the publicly available 3D version of the code, as well as details concerning the structure of the input and output files and the execution of the program.
