CN-121981327-A - Water regime driven evolution analysis method, device, apparatus, medium and program product

CN121981327ACN 121981327 ACN121981327 ACN 121981327ACN-121981327-A

Abstract

The invention provides a water condition driving evolution analysis method, a device, equipment, a medium and a program product, and relates to the technical field of water condition driving, wherein the method comprises the steps of acquiring water surface data acquired by a plurality of observation equipment in a target area, wherein one observation equipment acquires one water surface data at one acquisition moment; the method comprises the steps of determining target water surface data of observation equipment and target driving indexes of the target water surface data according to spatial overlapping relations among a plurality of pieces of water surface data acquired by the observation equipment, wherein the target water surface data are used for predicting a water condition evolution path of a period in the future, determining water condition evolution fusion degrees of all the observation equipment according to the target driving indexes of the target water surface data of the plurality of the observation equipment, and determining target observation equipment in a target area according to the water condition evolution fusion degrees. The embodiment of the invention can improve the prediction precision of the water condition evolution path and the water condition monitoring resource utilization rate.

Inventors

LUO XIAOLIANG
SHEN BOHUI
HU JIANLONG
LIU QUNFANG
Wang Lvchun
YU WEI
PENG JIAN
WANG LONGBAO
LIN JINHUA
HE MU
YOU YUANYUAN
AO JUNJIE

Assignees

中移(江西)虚拟现实科技有限公司
中国移动通信集团江西有限公司
中国移动通信集团有限公司
河海大学

Dates

Publication Date: 20260505
Application Date: 20260123

Claims (12)

1. A water condition driven evolution analysis method, comprising: Acquiring water surface data acquired by a plurality of observation devices in a target area, wherein one observation device acquires one piece of water surface data at one acquisition time, and one piece of water surface data comprises area information of a water surface coverage area at one acquisition time; determining target water surface data of the observation equipment and a target driving index of the target water surface data according to a spatial overlapping relation among a plurality of pieces of water surface data acquired by the observation equipment, wherein the target driving index is used for representing spatial association strength between the target water surface data and the plurality of pieces of water surface data, and the target water surface data is used for predicting a water condition evolution path of a future period; Determining the water condition evolution fusion degree of each observation device according to the target driving indexes of the target water surface data of the plurality of observation devices, wherein the water condition evolution fusion degree is used for representing the water condition evolution consistent strength between the currently processed observation device and the plurality of observation devices; And determining target observation equipment in the target area according to the water condition evolution fusion degree.
2. The water condition driven evolution analysis method according to claim 1, wherein the determining the target water surface data of the observation device and the target driving index of the target water surface data according to the spatial overlapping relation between the plurality of water surface data acquired by the observation device comprises: determining a plurality of water surface data sets according to a plurality of water surface data acquired by the observation equipment, wherein one observation equipment corresponds to one water surface data set; calculating a driving index of each water surface data in the water surface data set according to the spatial overlapping relation among a plurality of water surface data in the water surface data set; And screening a plurality of water surface data in the water surface data set according to the driving index, and determining target water surface data of the observation equipment and a target driving index of the target water surface data.
3. The water condition driven evolution analysis method according to claim 2, wherein the calculating the driving index of each of the water surface data in the water surface data set from the spatial overlapping relationship between the plurality of water surface data in the water surface data set includes: For a first water surface data set which is currently processed, calculating a driving index of the first water surface data according to the space overlapping degree between the first water surface data and at least one second water surface data, wherein the first water surface data and the second water surface data belong to the first water surface data set, the acquisition time of the second water surface data is later than the acquisition time of the first water surface data, and the driving index is used for representing the space association strength between the first water surface data and at least one second water surface data.
4. The water condition driven evolution analysis method according to claim 2, wherein the screening the plurality of water surface data in the water surface data set according to the driving index, determining the target water surface data of the observation device and the target driving index of the target water surface data, comprises: And screening a plurality of water surface data in the water surface data set according to the magnitude relation of the driving indexes, and determining target water surface data of the observation equipment and target driving indexes of the target water surface data, wherein the target driving indexes of the target water surface data are larger than or equal to the driving indexes of any water surface data in the same water surface data set.
5. The water condition driven evolution analysis method according to claim 1, wherein the determining the water condition evolution fusion degree of each of the observation apparatuses according to the target driving indexes of the target water surface data of the plurality of observation apparatuses comprises: Grouping the target driving indexes according to the acquisition time of the target water surface data of the plurality of observation devices to obtain a plurality of fusion sample groups, wherein the target driving indexes in the same fusion sample group correspond to the same acquisition time; And calculating the water condition evolution fusion degree of each observation device according to the fusion sample group corresponding to the target driving index.
6. The water condition driven evolution analysis method according to claim 5, wherein the calculating the water condition evolution fusion degree of each observation device according to the fusion sample group corresponding to the target driving index comprises: for a first observation device currently processed, determining the target drive index of the first observation device as a centroid of a first fused sample group, wherein the first fused sample group is a fused sample group to which the target drive index of the first observation device belongs; According to the first fusion sample group, calculating the water condition evolution fusion degree of the first observation device, wherein the water condition evolution fusion degree is used for representing the water condition evolution consistent strength between the first observation device and a plurality of observation devices in the first fusion sample group.
7. The water condition driven evolution analysis method according to claim 1, wherein before the acquiring the water surface data acquired by the plurality of observation devices in the target area, the method further comprises: acquiring a grid chart of the target area, wherein the grid chart comprises a plurality of water surface grids; Acquiring initial area information of the water surface coverage area acquired by a plurality of observation devices in the target area, wherein one observation device acquires one initial area information at one acquisition time; And identifying and counting the water surface grids corresponding to the initial area information of the water surface coverage area, and generating the water surface data, wherein one piece of water surface data comprises the area information of the water surface coverage area at one acquisition moment, and the area information is formed by a plurality of water surface grids.
8. The water condition driven evolution analysis method of claim 7, further comprising: and longitudinally stacking and arranging the area information of the water surface coverage area according to the sequence of acquisition time from beginning to end to obtain a water condition space-time interaction diagram of each observation device.
9. A water condition driven evolution analysis device, comprising: the first acquisition module is used for acquiring water surface data acquired by a plurality of observation devices in a target area, wherein one observation device acquires one water surface data at one acquisition time, and one water surface data comprises area information of a water surface coverage area at one acquisition time; The first determining module is used for determining target water surface data of the observing equipment and target driving indexes of the target water surface data according to the spatial overlapping relation among the plurality of water surface data acquired by the observing equipment, wherein the target driving indexes are used for representing spatial association strength between the target water surface data and the plurality of water surface data, and the target water surface data are used for predicting a water condition evolution path of a future period; The second determining module is used for determining the water condition evolution fusion degree of each observing device according to the target driving indexes of the target water surface data of the plurality of observing devices, wherein the water condition evolution fusion degree is used for representing the water condition evolution consistent strength between the currently processed observing device and the plurality of observing devices; and the third determining module is used for determining target observation equipment in the target area according to the water condition evolution fusion degree.
10. A network device comprising a processor, a memory and a program stored on the memory and executable on the processor, which when executed by the processor implements the water condition driven evolution analysis method of any one of claims 1 to 8.
11. A readable storage medium, characterized in that it has stored thereon a program, which when executed by a processor, implements the steps of the water condition driven evolution analysis method according to any one of claims 1 to 8.
12. A computer program product comprising computer instructions which, when executed by a processor, implement the steps of the water condition driven evolution analysis method of any one of claims 1 to 8.

Description

Water regime driven evolution analysis method, device, apparatus, medium and program product Technical Field The invention relates to the technical field of water regime driving, in particular to a water regime driving evolution analysis method, a device, equipment, a medium and a program product. Background The water condition evolution analysis is one of key technologies of water area environment monitoring and disaster early warning, and is characterized in that water surface change characteristics are captured through dynamic data, and trend is predicted. The existing water regime application technology mainly uses meteorological factors to forecast and forecast water regime and realize water resource scheduling, the observation point layout of the technology depends on experience or single index, key nodes are easy to miss, the water regime monitoring resource utilization rate is low, the technology is mainly based on two-dimensional data and statistical analysis, the driving relation of water regime change under different time dimensions is difficult to quantify, the accumulated effect and the spatial relevance of water regime evolution cannot be intuitively reflected, and the forecasting precision of a water regime evolution path is low. Disclosure of Invention The invention aims to provide a water regime driven evolution analysis method, a device, equipment, a medium and a program product, which are used for solving the problems of low prediction precision and low water regime monitoring resource utilization rate of a water regime evolution path in the prior art. In order to solve the above technical problems, an embodiment of the present invention provides a water condition driven evolution analysis method, including: Acquiring water surface data acquired by a plurality of observation devices in a target area, wherein one observation device acquires one piece of water surface data at one acquisition time, and one piece of water surface data comprises area information of a water surface coverage area at one acquisition time; determining target water surface data of the observation equipment and a target driving index of the target water surface data according to a spatial overlapping relation among a plurality of pieces of water surface data acquired by the observation equipment, wherein the target driving index is used for representing spatial association strength between the target water surface data and the plurality of pieces of water surface data, and the target water surface data is used for predicting a water condition evolution path of a future period; Determining the water condition evolution fusion degree of each observation device according to the target driving indexes of the target water surface data of the plurality of observation devices, wherein the water condition evolution fusion degree is used for representing the water condition evolution consistent strength between the currently processed observation device and the plurality of observation devices; And determining target observation equipment in the target area according to the water condition evolution fusion degree. Optionally, the determining the target water surface data of the observation device and the target driving index of the target water surface data according to the spatial overlapping relation between the plurality of water surface data acquired by the observation device includes: determining a plurality of water surface data sets according to a plurality of water surface data acquired by the observation equipment, wherein one observation equipment corresponds to one water surface data set; calculating a driving index of each water surface data in the water surface data set according to the spatial overlapping relation among a plurality of water surface data in the water surface data set; And screening a plurality of water surface data in the water surface data set according to the driving index, and determining target water surface data of the observation equipment and a target driving index of the target water surface data. Optionally, the calculating a driving index of each of the water surface data in the water surface data set according to a spatial overlapping relation between a plurality of the water surface data in the water surface data set includes: For a first water surface data set which is currently processed, calculating a driving index of the first water surface data according to the space overlapping degree between the first water surface data and at least one second water surface data, wherein the first water surface data and the second water surface data belong to the first water surface data set, the acquisition time of the second water surface data is later than the acquisition time of the first water surface data, and the driving index is used for representing the space association strength between the first water surface data and at least one second water surface data. Optionally, the screening