Basin water environment big data mining and business decision support system
Through the basin water environment big data system for data collection, classification, prediction and real-time monitoring, the problem of inaccuracy and long-term plan formulation of the basin water environment big data decision support system is solved, and real-time monitoring and accurate decision support of the basin water environment is realized.
Patent Information
- Application Number
- CN202510581031.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-07
- Publication Date
- 2025-08-01
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing big data mining decision support system for water environment in the basin is not accurate enough when formulating prediction plans, and the plan is formulated for a long time, which makes it impossible to get support as soon as possible.
Data collection, classification, basin change prediction, analysis risk assessment and implementation of detection and update modules are adopted, and information from industrial basins, residential basins and natural basins is combined to conduct real-time monitoring and program updates to ensure the accuracy of predictions.
Through real-time monitoring and updates of solutions, we improve prediction accuracy, reduce decision-making disputes, and ensure that decision makers can obtain the best solutions in a timely manner.
Smart Images
Figure CN120410218A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of river basins, and specifically relates to a big data mining and business decision support system for river basin water environment. Background Art
[0002] In recent years, with the development of Internet of Things and big data technologies, new opportunities and challenges have been brought to the processing and decision-making of river basin water environment data. While the water environment industry has accumulated rich data information resources, a large number of related data application software, information systems and interactive platforms have also emerged.
[0003] However, in the existing big data mining decision support system for river basin water environment, when formulating a prediction plan, the reason why it is often inaccurate is that the time for formulating the prediction plan is relatively long, resulting in disputes and unable to obtain support in a timely manner.
[0004] In view of this, the present invention is specifically proposed. Summary of the Invention
[0005] In order to solve the above technical problems, the basic concept of the technical solution adopted by the present invention is as follows: A big data mining and business decision support system for river basin water environment, including the following systems: Data acquisition module: The data acquisition module is used to collect the basic information of a selected river basin area; Data classification module: The data classification module is used to specifically classify the information collected in a certain area; River basin change prediction module: The prediction module makes a prediction based on the specific information growth and decrease changes of the river basin every day in recent days, so as to formulate a plan; Analysis risk assessment module: The risk of river basin change in the plan is evaluated according to the formulated plan; Implementation detection and update module: The implementation detection module is used to detect the river basin information in this area in real time, collect according to the changes in different time periods of the river basin, and then adopt corresponding plans.
[0006] As a preferred implementation manner of the present invention, the specific acquisition system based on the above data acquisition module includes: The staff selects a river basin area and detects the specific information of this area, where the specific detection is the basic information of the river basin, such as industrial river basin, residential river basin and natural river basin, etc.
[0007] As a preferred implementation manner of the present invention, the specific classification system based on the above data classification module includes: Classify the information collected in the above data acquisition module, and the specific classification is as follows: For example, Industrial watershed: Watershed pollution, sewage discharge, waste gas discharge, solid discharge, and soil changes, etc.; Residential watershed: Watershed pollution, water resource consumption, and soil changes, etc.; Natural watershed: Watershed pollution, topography, flow changes, natural weather, and soil changes, etc.
[0008] As a preferred embodiment of the present invention, the specific prediction system based on the above watershed change prediction module includes: Based on the classified watershed information above, judge the change situation of the watershed in this area in the next day according to the growth degree of different watersheds in the previous two days: Among them, for the change situation judgment example of the natural watershed: According to weather changes: Implement in combination with a weather warning system, etc., to obtain the weather changes in all areas connected to this watershed: For example: Other watersheds are rainy: Then there may be an increase in flow in this area, resulting in more soil erosion; Other areas are cloudy: Affected by the weather, the water evaporation in this area is less, the flow decreases, and the overall soil erosion slows down; Other areas are sunny: More water evaporates in this area, resulting in a decrease in flow, thus reducing the overall amount of soil erosion; When this watershed is rainy, sunny, and cloudy, it respectively has the characteristics of the above other watersheds; Based on the above characteristics of weather changes and the estimated growth degree of industrial watersheds and residential watersheds, and combining them, it is possible to estimate the situations that occur under different changes, and thus formulate corresponding plans according to different situations.
[0009] As a preferred embodiment of the present invention, the specific systems for predicting industrial watershed changes and residential watersheds based on the above watershed change prediction module include: Industrial watershed: According to the increase rate of sewage discharge, waste gas discharge, and solid discharge, predict the future increase rate, and thus evaluate the risk of the degree of harm caused to the watershed according to the amount of discharge; Residential module: According to the population change and water consumption increase rate in this area, judge whether the degree of water source use in this area poses a risk of increasing or decreasing the flow.
[0010] As a preferred embodiment of the present invention, the specific risk assessment system based on the above analysis risk assessment module includes: Based on the above formulated plans, at this time, the staff conducts a preview. According to the preview results, at this time, the staff evaluates the risks existing in each plan and takes corresponding preparatory measures.
[0011] As a preferred embodiment of the present invention, based on the above-mentioned fact detection and update module, the specific fact detection system includes: Based on the detection system, the changes in the industrial watershed, residential watershed, and natural watershed in this area are checked and transmitted to the data acquisition module. Specifically, the transmission is carried out once within a period of time. Therefore, when conducting detection, it is possible to avoid the occurrence of sudden reasons, so that the predicted plan can be updated in real time, thus ensuring the accuracy of the plan.
[0012] The present invention has the following beneficial effects compared with the prior art: In the present invention, by combining the degree of increase in hazards in the industrial watershed and residential watershed in recent days and the impact of weather changes in the natural watershed on this watershed, multiple plans can be formulated. According to the real-time monitoring system, real-time monitoring is carried out, ensuring that the specific changes in this watershed can be updated at different time periods, thus revising the predicted plan, facilitating the acquisition of the plan for the next time period, ensuring the accuracy of the prediction, and enabling decision-makers to obtain the best plan, thereby reducing decision-making disputes.
[0013] The following further describes in detail the specific embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] In the accompanying drawings: Figure 1 It is a system schematic diagram of a big data mining and business decision-making support system for watershed water environment; Figure 2 It is an overall system schematic diagram of a big data mining and business decision-making support system for watershed water environment; Figure 3 It is a specific schematic diagram of the watershed change prediction module of a big data mining and business decision-making support system for watershed water environment; Figure 4 It is a specific schematic diagram of the analysis risk assessment module of a big data mining and business decision-making support system for watershed water environment. SPECIFIC EMBODIMENTS
[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention.
[0016] As Figures 1 to 4 shown, a big data mining and business decision-making support system for watershed water environment includes the following systems: Data acquisition module: The data acquisition module is used to collect the basic information of the watershed in a selected area; Data Classification Module: The data classification module is used to specifically classify the information collected from Area 1 of the mold. Watershed Change Prediction Module: The prediction module makes predictions based on the specific information growth and decline changes of the watershed every day in recent days, and thus formulates a plan. Analysis Risk Assessment Module: The module assesses the risks of watershed changes in the plan according to the formulated plan. Implementation Detection and Update Module: The implementation detection module is used to detect the watershed information in this area in real time, collect according to the changes of the watershed at different time periods, and thus adopt corresponding plans.
[0017] In the specific implementation manner, the specific acquisition system based on the above data acquisition module includes: Staff members select the watershed in a certain area and detect the specific information of this area. The specific detection is the basic information of this watershed, such as industrial watershed, residential watershed, and natural watershed, etc.
[0018] Furthermore, based on the above data classification module, the specific classification system includes: Classify the information collected in the above data acquisition module, and the specific classification is as follows: For example, Industrial Watershed: Watershed pollution, sewage discharge, waste gas discharge, solid discharge, and soil changes, etc. Residential Watershed: Watershed pollution, water resource consumption, and soil changes, etc. Natural Watershed: Watershed pollution, terrain and landform, flow changes, natural weather, and soil changes, etc.
[0019] Furthermore, based on the above watershed change prediction module, the specific prediction system includes: According to the classified watershed information above, judge the change situation of the watershed in this area in the next day according to the growth degree of different watersheds in the previous two days. Among them, for the change situation judgment of the natural watershed, for example: According to weather changes: Implement in combination with the weather warning system, etc., to obtain the weather changes of all areas connected to this watershed. For example: If other watersheds belong to rainy days: Then there may be an increase in the flow in this area, resulting in more soil erosion. If other areas belong to cloudy days: Affected by the weather, the water evaporation in this area is less, the flow decreases, and the overall soil erosion slows down. If other areas belong to sunny days: The water evaporation in this area is more, resulting in a decrease in the flow, and thus the overall amount of soil erosion becomes less. When this watershed belongs to rainy days, sunny days, and cloudy days, it respectively has the characteristics of the above other watersheds. Based on the characteristics of the above-mentioned weather changes and the estimated growth levels of industrial and residential watersheds, they are combined, so that the situations occurring under different changes can be predicted, and corresponding plans can be formulated according to different situations.
[0020] Furthermore, the system for predicting specific industrial watershed changes and residential watershed predictions in the above-mentioned watershed change prediction module includes: Industrial watershed: According to the increase rates of sewage discharge, waste gas discharge, and solid discharge, predict the future increase rate, and thus evaluate the risk of the degree of harm caused to the watershed according to the amount of discharge. Residential module: According to the population change and water consumption increase rate in this area, judge whether the use degree of the water source in this area poses risks of flow increase and decrease.
[0021] Furthermore, the specific risk assessment system in the above-mentioned analysis risk assessment module includes: Based on the above-mentioned formulated plans, at this time, the staff conduct a preview. According to the preview results, the staff evaluate the risks existing in each plan and take corresponding preparatory measures.
[0022] Furthermore, the specific fact detection system in the above-mentioned fact detection update module includes: Based on the detection system, the changes in the industrial, residential, and natural watersheds in this area are repaired and transmitted to the data acquisition module. Specifically, the transmission is once within a period of time. Therefore, when conducting detection, the occurrence of unexpected reasons can be avoided, so that the predicted and formulated plans can be updated in real time, thus ensuring the accuracy of the plans.
[0023] The implementation principle of a big data mining and business decision support system for the water environment of a river basin of the present invention is as follows: Staff members select a river basin in a certain area and detect the specific information of this area. The specific detection includes the basic information of this river basin, such as industrial river basins, residential river basins, and natural river basins, etc.; classify the information collected in the above data collection module. The specific classification is as follows: For example, industrial river basins: river basin pollution, sewage discharge, waste gas discharge, solid discharge, and soil changes, etc.; residential river basins: river basin pollution, water resource consumption, and soil changes, etc.; natural river basins: river basin pollution, terrain and landform, flow changes, natural weather, and soil changes, etc.; according to the classified river basin information above, judge the change situation of the river basin in this area in the next day according to the growth degree of different river basins in the previous two days. Among them, for the change situation judgment of the natural river basin, for example, according to weather changes: Implement and combine with a weather warning system, etc., to obtain the weather changes of all areas connected to this river basin. For example, if other river basins are rainy days: then there may be an increase in the flow in this area, resulting in more soil erosion; if other areas are cloudy days: affected by the weather, the water evaporation in this area is less, the flow decreases, resulting in a slowdown in the overall soil erosion; if other areas are sunny days: the water evaporation in this area is more, resulting in a decrease in the flow, thus making the overall amount of soil erosion less; when this river basin is rainy, sunny, and cloudy, it respectively has the characteristics of the above other river basins; industrial river basins: According to the increase rate of sewage discharge, waste gas discharge, and solid discharge, predict the future increase rate, and thus evaluate the risk of the degree of harm caused to the river basin according to the amount of discharge; residential module: According to the population change and the increase rate of water use in this area, judge whether the degree of water source use in this area causes the risk of flow increase and decrease; Based on the above characteristics of weather changes and the growth degree estimation of industrial and residential river basins, combine them, so that the situation occurring under different changes can be estimated, and thus corresponding plans can be formulated according to different situations; Based on the above formulated plans, at this time, the staff members preview them. According to the preview results, at this time, the staff members evaluate the risks existing in each plan and take corresponding preparatory measures; Based on the detection system, the changes in the industrial, residential, and natural river basins in this area are checked and transmitted to the data collection module. The specific transmission is once in a period of time. Therefore, when detecting, the situation of sudden reasons can be avoided, so that the predicted and formulated plans can be updated in real time, thus ensuring the accuracy of the plans.
[0024] By combining the degree of harm increase in industrial and residential basins in recent days with the impact of weather changes on the basin under natural conditions, multiple solutions can be formulated. Real-time monitoring of the basin using a real-time monitoring system ensures that specific changes in the basin can be updated at different time intervals, enabling the revision of predicted solutions, facilitating the acquisition of solutions for the next time period, ensuring the accuracy of predictions, and enabling decision-makers to obtain the best solutions.
Claims
1. A large data mining and business decision support system for the water environment of a river basin, characterized in that, It includes the following systems: Data acquisition module: The data acquisition module is used to collect the basic information of the river basin in a selected area; Data classification module: The data classification module is used to specifically classify the information collected in a certain area; River basin change prediction module: The prediction module makes predictions based on the specific increase and decrease changes of the river basin information every day in recent days, so as to formulate a plan; Analysis risk assessment module: Assess the risks of river basin changes existing in the plan according to the formulated plan; Implementation detection and update module: The implementation detection module is used to detect the river basin information in this area in real time, collect according to the changes in different time periods of the river basin, and then adopt corresponding plans.
2. The basin water environment big data mining and business decision support system according to claim 1, characterized in that Based on the specific acquisition system in the above data acquisition module, it includes: Staff select the river basin in a certain area and detect the specific information of this area. The specific detection is the basic information of this river basin, such as industrial river basin, residential river basin and natural river basin, etc.
3. A large data mining and business decision support system for watershed water environment according to claim 1, characterized in that, Based on the above data classification module, the specific classification system includes: Classify the information collected in the above data acquisition module, and the specific classification is as follows: Industrial river basin: River basin pollution, sewage discharge, waste gas discharge, solid discharge and soil change, etc.; Residential river basin: River basin pollution, water resource consumption and soil change, etc.; Natural river basin: River basin pollution, terrain and landform, flow change, natural weather and soil change, etc.
4. A large data mining and business decision support system for basin water environment according to claim 1, characterized in that, Based on the specific prediction system in the above river basin change prediction module, it includes: According to the classified river basin information above, judge the change situation of the river basin in this area in the next day according to the growth degree of different river basins in the previous two days. Among them, for the change situation judgment of the natural river basin, the changes are as follows: According to weather changes: Implement in combination with the weather warning system, etc., to obtain the weather changes of all areas connected to this river basin. For example: If other river basins are rainy days: Then there may be an increase in flow in this area, resulting in more soil erosion; If other areas are cloudy days: Affected by the weather, the water evaporation in this area is less, the flow decreases, and the overall soil erosion slows down; If other areas are sunny days: The water evaporation in this area is more, resulting in a decrease in flow, so that the overall amount of soil erosion becomes less; When this river basin is rainy, sunny and cloudy, it respectively has the characteristics of the above other river basins; Based on the above characteristics of weather changes and the growth degree estimation of industrial river basins and residential river basins, and combining them, it is possible to estimate the situations occurring under different changes, and then formulate corresponding plans according to different situations.
5. A large data mining and business decision support system for watershed water environment according to claim 4, characterized in that, Based on the specific industrial river basin change and residential river basin prediction systems in the above river basin change prediction module, it includes: Industrial river basin: According to the increase rate of sewage discharge, waste gas discharge and solid discharge, predict the future increase rate, and then assess the risk of the degree of harm caused to the river basin according to the amount of discharge; Residential module: According to the population change and water consumption increase rate in this area, judge whether the degree of water source use in this area causes the risk of flow increase and decrease.
6. The water environment big data mining and business decision support system for a river basin according to claim 1, characterized in that Based on the above analysis risk assessment module, the specific risk assessment system includes: Based on the above-established plan, at this time, the staff conducts a preview. According to the preview results, the staff then assesses the risks existing in each plan and takes corresponding preparatory measures.
7. A big data mining and business decision support system for watershed water environment according to claim 1, characterized in that, Based on the above fact detection and update module, the specific fact detection system includes: Based on the detection system, the changes in the industrial basin, residential basin, and natural basin in this area are overhauled and transmitted to the data acquisition module. Specifically, the transmission is carried out once within a certain period of time. Therefore, when conducting detection, it is possible to avoid the occurrence of unexpected reasons, so that the predicted and established plan can be updated in real time, thus ensuring the accuracy of the plan.