Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast Modeling Methods for Complex System with Separable Features   Data-driven modeling plays an increasingly important role in different areas
of engineering. For most of existing methods, such as genetic programming (GP),
the convergence speed might be too slow for large scale problems with a large
number of variables. Fortunately, in many applications, the target models are
separable in some sense. In this paper, we analyze different types of
separability of some real-world engineering equations and establish a
mathematical model of generalized separable system (GS system). In order to get
the structure of the GS system, two concepts, namely block and factor are
introduced, and a special method, block and factor detection is also proposed,
in which the target model is decomposed into a number of blocks, further into
minimal blocks and factors. Compare to the conventional GP, the new method can
make large reductions to the search space. The minimal blocks and factors are
optimized and assembled with a global optimization search engine, low
dimensional simplex evolution (LDSE). An extensive study between the proposed
method and a state-of-the-art data-driven fitting tool, Eureqa, has been
presented with several man-made problems. Test results indicate that the
proposed method is more effective and efficient under all the investigated
cases.

35
The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph