Economic water consumption data spatial discretization method based on RBF neural network

A technology of neural network and water use data, applied in biological neural network models, data processing applications, instruments, etc., can solve problems such as lack of water use data

Inactive Publication Date: 2014-06-25
BEIJING NORMAL UNIVERSITY
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  • Claims
  • Application Information

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Problems solved by technology

At present, there is a scarcity of data on water use according to water resource divisions at all levels

Method used

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  • Economic water consumption data spatial discretization method based on RBF neural network
  • Economic water consumption data spatial discretization method based on RBF neural network
  • Economic water consumption data spatial discretization method based on RBF neural network

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Embodiment Construction

[0080] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0081] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are to distinguish two entities with the same name but different parameters or parameters that are not the same, see "first" and "second" It is only for the convenience of expression, and should not be construed as a limitation on the embodiments of the present invention, which will not be described one by one in the subsequent embodiments.

[0082] Refer to attached figure 1 , is a schematic flowchart of an embodiment of the RBF neural network-based economical water data space discretization method provided by the present invention.

[0083] The method for discretizing economic water data space based on ...

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Abstract

The invention discloses an economic water consumption data spatial discretization method based on an RBF neural network. The economic water consumption data spatial discretization method comprises the steps of obtaining a basic calculation unit; obtaining spatial element data sets of the basic calculation unit and an administration unit; using a quota method to supplement domestic water, industrial water and agricultural water and adopting a correlation factor apportionment method to supplement ecological environment water consumption; adopting a combination weighting method to confirm weight coefficients in an ecological environment water consumption computational formula; obtaining a discrete prediction result of the basic calculation unit through analog computation; performing result correction; performing step-by-step summarizing according to water resource partition properties of the basic calculation unit to obtain corresponding water consumption data. By adopting the economic water consumption data spatial discretization method based on the RBF neural network, economic and social water consumption data of water resource subareas at all levels in our country can be obtained, and water resource integrated management is facilitated.

Description

technical field [0001] The invention relates to the field of water conservancy science and technology, in particular to a method for discretizing economic water data space based on an RBF neural network. Background technique [0002] Economic and social water use data are mainly collected from administrative units whose boundaries do not coincide with those of water resource areas, making it very difficult to obtain data on water use in water resource areas. The existing economic and social water use data still have problems such as difficulty in sharing, difficulty in statistics and diversity of statistical data. The use of computer technology to obtain economic and social water use data in water resource areas is very important for improving the data base of water resources to support the unified management of water resources administrative regions and river basins and to reduce the input of human census. [0003] Water use refers to the behavior of using certain attribut...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/06G06N3/02
Inventor 杨中文许新宜豆俊峰宾零陵王崴陈午刘虹利
Owner BEIJING NORMAL UNIVERSITY
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