- author = "Chen Chen and Changtong Luo and Zonglin Jiang",
- booktitle = "2017 10th International Symposium on Computational Intelligence and Design (ISCID)",
- title = "Fast Modeling Methods for Complex System with Separable Features",
- year = "2017",
- volume = "1",
- pages = "201--204",
- abstract = "Data-driven modelling 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 analyse different types of separability and establish a generalised separable model (GSM). In order to get the structure of the GSM, a multi-level block search method is 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 optimised and assembled with a global optimisation 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.",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/ISCID.2017.144",
- month = dec,
-
notes = "School of Engineering Sciences, University of Chinese
Academy of Sciences, Beijing 100049, China
Also known as \cite{8275752}",
