Abstract
This paper analyses several currently used computing methods inspired by the nature and concludes their common properties and their disadvantages. It then proposes a more abstract computing model inspired by the nature according to theoretical results on number theory. We also present a good lattice points method based on the number theory for problem solving, of which the discrepancy of the new method is minimized in the sense when the number of points are fixed. This method is dimensional independent and can be used to solve high dimensional problems. A typical algorithm is proposed to apply Genetic Algorithm and Immume Algorithm. Some comparable examples are given to show the advantages of our new method.
This work is partly supported by a grant of Ministry of Education, P.R. China (20040357002).
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Cheng, Jx., Zhang, L., Zhang, B. (2007). A Theoretical Framework of Natural Computing – M Good Lattice Points (GLP) Method. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_47
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DOI: https://doi.org/10.1007/978-3-540-72524-4_47
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