15 results about "Weather analysis" patented technology

The invention discloses an agricultural big data multivariate fusion supervision system, and relates to the technical field of agricultural supervision, and the system comprises a soil analysis module which is used for obtaining soil parameter data of an agricultural region, carrying out the analysis of the soil parameter data through a K-Means clustering model, and outputting the quality score and improvement suggestion information of agricultural products in the agricultural region; the meteorological analysis module is used for collecting historical meteorological data of the agricultural region, constructing a time sequence prediction model, predicting a meteorological trend of a future time window and generating meteorological forecast information; through multi-source data fusion of the meteorological analysis module, the agricultural product quality supervision module and the market prediction module, the agricultural product quality, the future meteorological trend and the agricultural product market supply and demand state of a land parcel in an agricultural area are comprehensively judged, and a crop variety recommendation scheme is output based on a decision tree and a scoring function through the planting recommendation module. The decision making is more scientific and accurate, so that the crop yield and the economic benefit are improved.

The invention discloses an intelligent management and control system for a digital flow of port production operation, and particularly relates to the field of data management, and the system comprises a port order information extraction module, an operation plan generation module, a port departure operation perception module, an operation risk analysis module, a position recognition module, an abnormal meteorological analysis module, and an operation load prediction module. According to the method, the operation plan is produced, time state sensing and departure ship monitoring are carried out based on the operation plan, and then the operation risk is analyzed, so that departure is flexibly adjusted, position deviation and meteorological abnormity are sensed through the positioning equipment and the environment sensing terminal after departure, and the working efficiency is improved. When the position of the ship deviates due to stormy waves, the weather and deviation relevance is quantified, and the subsequent operation plan is optimized accordingly, so that the future production operation difference caused when the port operation is greatly influenced by external factors such as weather, tide and channel conditions is avoided, and the operation and transportation efficiency can be improved on the premise of ensuring normal production operation.

A weather fusion observation method, platform, medium and equipment based on radar technology, relate to the field of weather information digital intelligent technology. The method comprises: receiving a plurality of types of weather data sent by each local radar device; converting each weather data into standard weather data according to a preset standard format block; filtering impurity data in each standard weather data to obtain target weather data; in response to a fusion instruction, fusing at least two target weather data according to the fusion instruction to obtain fusion weather data for weather analysis through the fusion weather data. Through the data fusion of multiple weather equipment, the accuracy of analyzing weather data can be improved by implementing the technical solution provided in the application.

The invention discloses a grid reanalysis data-based whole-process objective identification method for a southwest low vortex, and a medium, and relates to the technical field of meteorological big data processing and numerical weather analysis. The method comprises the following steps: eliminating high-altitude grid points in a target identification area by using a terrain mask; searching a closed isoline according to an equivalence distance based on a preset air pressure horizon potential height field, extracting a closed low-pressure candidate body and determining a low-pressure center; calculating the attribution of a closed region, screening an effective candidate body, constructing a time sequence track by adopting adjacent time space adjacent matching, and introducing displacement constraint and duration criterion to confirm a low eddy process; and outputting starting and ending moments, duration time and a moving path, and supporting frequency, path and rainfall influence statistics. According to the method, automatic identification, stable tracking and consistency statistics of the southwest low vortex in a long-time sequence can be realized, subjective identification deviation and labor cost are reduced, and rechecking performance and service availability of an identification result under a complex terrain condition are improved.

An object of a system according to an embodiment is to reduce food loss by adjusting a price based on a best-before date.SOLUTION: A system includes a price adjustment unit, a weather analysis unit, a store visit prediction analysis unit, and a reward program application unit. The price adjustment unit adjusts the price based on the best-before date. The weather analysis unit analyzes weather data. The store visit prediction analysis part analyzes the store visit prediction data. The Rewards Program Applier applies the Rewards Program.SELECTED DRAWING: Figure 1

The application discloses a kind of big data-based water conservancy project intelligent analysis system and method.This application belongs to the technical field of intelligent monitoring and early warning of water pollution prevention and control.The system includes: environmental analysis module, for obtaining the first influence data of environmental data on lake;Weather analysis module, for obtaining the second influence data of weather data on lake;Runoff analysis module, for obtaining the third influence data of runoff water replenishment data on lake;Model construction module, for constructing virtual lake model;Change analysis module, for generating lake change data from each influence data, to obtain model change data;Instruction generation module, for generating initial lake regulation instruction, and correcting to obtain lake regulation instruction, according to lake regulation instruction to carry out water resources regulation.This technical solution can improve the intelligent level of lake water resources management, while avoiding artificial decision bias, improving the accuracy of water level and water quality management.

The invention discloses mobile photovoltaic equipment for ground mining area communication equipment, which comprises a mobile base, a T-shaped folding frame and two rolling and folding assemblies, and a use method comprises the steps of weather analysis, light analysis, mobile installation and mobile installation. According to the ground mining area communication equipment mobile photovoltaic equipment and the use method thereof, the space utilization rate is large, the solar energy collection rate is high, the equipment is very suitable for mining area mobile communication, and the problem that mobile storage conflicts with low photovoltaic collection efficiency is solved.

Disclosed is technology for modifying activities based on probabilistic weather scenarios. A method can include: receiving weather scenarios and respective probabilities, determining event predictions for each weather scenario using a machine learning model trained with historical weather condition data and historical data about event conditions, clustering the event predictions with a time-series clustering approach to identify similarities amongst the weather scenarios and combine similar event conditions to generate a set of weather analytical scenarios, generating a probability of an occurrence of each weather analytical scenario, the probability being based on a total percentage probability of the weather scenarios corresponding to each respective weather analytical scenario, and determining an activity modification based on at least one aggregated event prediction from the probabilities of the weather analytical scenarios or an aggregate impact of the activity modification over a collection of event predictions corresponding to the weather analytical scenarios and the respective probabilities.

The application discloses a kind of southwest vortex whole process objectification identification method based on grid reanalysis data, medium, it is related to meteorological big data processing and numerical weather analysis technical field.The method is in target identification area using topographic mask to eliminate high-altitude grid point;Based on the potential height field of pre-set air pressure layer, search closed contour according to equivalent distance, extract closed low pressure candidate body and determine low pressure center;Calculate the effective candidate body of closed region attribution screening, adopt adjacent time space adjacent matching to construct time sequence track, introduce displacement constraint and duration criterion to confirm low vortex process;Output start and end time, duration and moving path, and support frequency, path and precipitation influence statistics.The application can realize the automatic identification, stable tracking and consistency statistics of long time sequence southwest vortex, reduce subjective identification deviation and labor cost, improve the reviewability and business availability of identification result under complex topographic conditions.

The invention discloses an Internet of Vehicles cooperative motorcycle intelligent lighting control method and system and a medium, and relates to the technical field of novel lighting, and the method comprises the steps: obtaining the driving state information of surrounding motor vehicles and non-motor vehicles, road environment state data and road condition data interactively shared by other vehicles through the Internet of Vehicles, the dangerous driving behavior of the non-motor vehicle and the dangerous point of the front road are sensed, and the non-motor vehicle conflict risk degree is determined; analyzing a current environment illumination condition and a weather condition, and calculating an environment adaptability factor according to a weather analysis result; and on the basis of the non-conflict risk degree and the environmental adaptability factor, calculating a comprehensive illumination regulation and control index by adopting a weighted fusion model, and matching a preset illumination control strategy to dynamically adjust the form, brightness and irradiation range of the illumination beam. According to the method, the illumination regulation and control effect under the complex working condition is optimized, the overall traffic safety under the group riding scene is improved, and adaptive optimization of illumination output and the actual riding environment is achieved.

The invention provides a weather effect generation method and device and electronic equipment, and the method comprises the steps: determining description information corresponding to an information input instruction in response to the information input instruction; inputting the description information into a weather analysis model, and generating weather effect parameters through the weather analysis model; the weather effect parameter is used for indicating the display degree of the plurality of weather elements; and based on the weather effect parameters, performing rendering on the graphical user interface to generate a target weather effect. According to the method, the generation efficiency of the weather effect is improved, and the interpersonal cost is reduced.

This application discloses a radar echo spatial downscaling method, apparatus, equipment, medium, and program product, relating to the field of meteorological information processing technology. The method includes: acquiring low-resolution radar echo data to be processed; upsampling the low-resolution radar echo data to be processed through interpolation to obtain high-resolution target echo data; extracting features from the high-resolution target echo data to obtain an initial high-frequency information representation map; and inputting the low-resolution radar echo data to be processed and the high-resolution target echo data into a downscaling model to obtain a high-resolution radar echo field corresponding to the low-resolution radar echo data to be processed. This application enhances the application value of radar echo data in refined weather analysis and severe weather early warning.

The invention discloses a tourist behavior prediction and scenic area congestion early warning system based on deep learning, and particularly relates to the field of deep learning. Comprising a scenic spot online consumption port acquisition module, a tourist consumption parameter acquisition module, a scenic spot welcome degree analysis module, a scenic spot priority determination module, a scenic spot flow sensing module, a road section congestion analysis module, an abnormal weather analysis module and a scenic spot road section optimization module. The scenic spot welcome degree is analyzed through multi-source data fusion, weather condition analysis is carried out in combination with weather data, and the crowd density is sensed through scenic spot priority determination, so that flexibility analysis of a congested road section is carried out, correlation analysis of road section congestion and tourist behaviors is further realized, and the accuracy of tourist behavior analysis is improved. Therefore, the influence of overall flow limiting on tourist experience is avoided to a certain extent, meanwhile, accurate intervention in a high-risk scene can be ensured, and differentiated services can be pushed under the condition that normal activities of tourists are guaranteed.

The invention relates to the technical field of meteorological detection and numerical weather analysis, and discloses a complex terrain low-layer wind field reconstruction and enhancement method and device, and the method comprises the steps: obtaining the terrain elevation data of a target region and the data of a multi-layer isobaric surface wind field; calculating to obtain a ground air pressure field consistent with topographic relief based on the topographic elevation data; converting the multi-layer isobaric surface wind field data into wind field data under a sigma coordinate system based on a ground air pressure field and a preset atmosphere top air pressure; sequentially performing vertical layering and merge averaging on the wind field data under the sigma coordinate system to obtain average wind field data of each sigma layer; on the basis of the average wind field data of all the sigma layers, the dynamic diagnostic quantity of the low-layer wind field is calculated, and the average wind field data of all the sigma layers and the dynamic diagnostic quantity serve as low-layer wind field dynamic characteristic enhancement products. The problems that a traditional isobaric surface wind field is poor in continuity and unclear in dynamic characteristic in a complex terrain area are solved.

The embodiment of the invention provides a dangerous weather analysis and forecast method and system based on multi-source fusion data. The method is applied to the technical field of dangerous weather analysis and forecast. The method comprises the following steps: acquiring a multi-source live data set; substituting the multi-source real-time data set into an analysis forecasting model, and selectively sending out at least one forecasting instruction corresponding to the dangerous weather according to the multi-source real-time data set; and based on the forecasting instruction corresponding to the at least one dangerous weather, executing early warning of the at least one dangerous weather. In this way, multi-source live data are fused, the accuracy of the data is improved, the accuracy of subsequent analysis and forecasting is further improved, analysis, forecasting and early warning of dangerous weather are achieved, and the accuracy and timeliness of dangerous weather forecasting and early warning are improved.