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Space filling optimal-design method for high flux combination experiment

A technology of space filling and design method, applied in the direction of calculation, calculation model, special data processing application, etc., can solve the problem that the optimal design structure cannot be fully utilized, and achieve the effect of improving the efficiency and high reliability of the optimal design

Inactive Publication Date: 2011-04-13
JIANGNAN UNIV
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Problems solved by technology

In addition, in the case of new data, these design methods cannot make full use of the original optimized design structure, and can only re-learn or train the entire set of data.

Method used

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  • Space filling optimal-design method for high flux combination experiment
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  • Space filling optimal-design method for high flux combination experiment

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specific Embodiment approach

[0046] Step 1: Determine the dimensionality of the experimental data space (that is, the number of experimental factors), and then calculate the optimal index (mean square approximation error ε) to obtain the optimal design of the entire basic cell.

[0047] The present invention proposes a method based on adaptive space filling optimal design, mainly based on an optimal index (mean square approximation error ε) to evaluate the quality of the design, and "fill" experimental data for experiments or sampling points space. The basic principles are as follows:

[0048] Considering the n-dimensional experimental data space, define:

[0049]a, E=[-h, h] n It is an experimental cell whose data range is contained in [-h, h], h>0;

[0050] b.y i1 ,...,y in (i=1,...,n+1) the i-th group of measured experimental point data sets, for example, the first dimension (temperature) attribute of the i-th measured experimental point data is y i1 , the i-th measurement experimental point data...

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Abstract

The invention provides a space filling optimal design method for a high flux combination experiment, which can effectively solve the problem that the optimal design of the high flux combination experiment in the prior art excessively depends on an initial value. The space filling optimal design method comprises the following steps: firstly, determining experiment data space dimensions (i.e. the number of experiment factors); establishing an optimal index model; and solving an optimal index (a mean square is approximate to an error) to obtain an optimal design structure of an experiment structure cell; then expanding a basic structure cell and also expanding a design result to a plurality of experiment design structure units in order to cover experiment data of a needed range; and finally carrying out self-adapting precise design for the basic structure cell to obtain an obvious experiment improved result. The invention provides the data space optimal method in the high flux combination experiment, thereby reducing the repetitiveness of design processing, enhancing the scientificalness and the reliability of design and being suitable for high and low dimensional data space optimal design; and in addition, the invention has substantive characteristics, thereby being an important link of the design of the high flux combination experiment in a materials science field, an engineering field, and the like.

Description

technical field [0001] The invention relates to an optimal design method, in particular to a space-filling optimal design method suitable for high-throughput combined experiment systems and also applicable to the analysis of system data in low-throughput combined experiments. Background technique [0002] In recent years, high-throughput combinatorial experiments have been widely used in materials science, especially in the development of new materials. Regarding the preparation and special characteristics of the sampled data, although the experimental equipment and technology have been greatly improved (one of the representative improvements is the high-end automatic operation), there is still less attention paid to the experimental design and the analysis of the experimental results. Many methods used in traditional experimental design and data analysis are still simply ported for high-throughput combinatorial experiments. However, it is worth noting that high-throughput ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/50G06N7/00
Inventor 楼旭阳崔宝同
Owner JIANGNAN UNIV
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