17 results about "Weather index" patented technology

The invention discloses an urban rail transit pull-in passenger flow prediction method fusing multi-source spatio-temporal data. The method comprises the following steps: collecting multi-source spatio-temporal data of a target station and a corresponding associated station; kernel density estimation is carried out on the surrounding POI density corresponding to each site, the spatial thermal characteristics of each site are generated, one-hot coding is carried out on the real-time weather index corresponding to each site, the weather influence characteristics of each site are generated, segmented coding is carried out on the date type identifier corresponding to each site, and the periodic effect characteristics of each site are generated. Performing differential stabilization on the historical pull-in passenger flow sequence of each station to generate a time sequence fluctuation characteristic of each station; tensor splicing is carried out on the space thermal characteristics, the weather influence characteristics, the periodic effect characteristics and the time sequence fluctuation characteristics of all the stations, a space-time fusion characteristic tensor is constructed and input into a space-time self-adaptive prediction model, and an inbound passenger flow prediction value of the target station is generated. The accuracy and timeliness of urban rail transit pull-in passenger flow prediction can be improved.

The invention discloses a weather modification operation information display method and system based on multi-source information fusion, and relates to the technical field of meteorological information intelligent decision making, and the method comprises the steps: carrying out the reasoning analysis of a time sequence knowledge graph through a graph neural network, recognizing the cloud system development change, reasoning the evolution of cloud physical characteristics, and predicting the space-time range of an operation potential region, generating an accurate forecast conclusion and a figure operation suggestion; and converting the accurate forecast conclusion and the weather modification operation suggestion into a visual instruction set, and generating a visual comprehensive situation map through highlighting core weather indexes, displaying evolution paths by dynamic arrows and marking operation potential areas and operation corridors by color coverage. According to the method, reasoning analysis is carried out on the time sequence knowledge graph by using the graph neural network, the operation potential area is automatically identified from a historical mode, the dynamic evolution of the operation potential area is predicted, and the perspectiveness and the accuracy of figure operation decision making are improved.

The invention provides a weather index insurance scheme optimization and optimization degree evaluation method based on basis risk, and belongs to the technical field of agricultural insurance, and the method comprises the following steps: step 1, obtaining meteorological data of a place where an insured crop is located; step 2, obtaining actual loss of crops caused by disasters; step 3, obtaining the compensation amount obtained by the insuring crop location; step 4, obtaining the basic difference risk of the weather index insurance scheme and the basic difference over the years of the place where each insured crop is located; step 5, decomposing the base difference to obtain space, time and design base difference; step 6, optimizing a weather index insurance scheme; step 7, decomposing the ground base differences over the years into space, time and design base differences; step 8, obtaining the optimization degree of the weather index insurance scheme; and step 9, constructing F test statistics, and judging the significance of the optimization degree of the weather index insurance scheme. According to the method, basis difference quantitative decomposition, basis difference risk quantitative calculation, a weather index insurance scheme optimization method and an optimization degree evaluation method are introduced, and optimization of the weather index insurance scheme is promoted.

The invention discloses a regional resident load meteorological sensitivity analysis method, device and equipment based on fused meteorological indexes, and a medium, and relates to the field of power load characteristics, and the method comprises the steps: constructing a multi-factor fused meteorological index model of a single meteorological point, determining a multi-meteorological point fusion meteorological index of the target area according to the resident load proportion corresponding to the target area and a multi-factor fusion meteorological index model, and then constructing a target data set according to the multi-meteorological point fusion meteorological index and the resident load data; and segmenting the target data set to perform piecewise nonlinear regression analysis on the obtained target first data set and the target second data set, and determining the current residential load meteorological sensitivity of the target area through a target piecewise regression analysis function obtained through analysis and the target data set. Therefore, nonlinear segmented regression modeling and sensitivity analysis of the resident load and the fused meteorological indexes in the target area can be realized, and support is provided for refined analysis and management of the resident load.

This invention discloses an automatic method for extracting ionospheric TEC anomalies based on global seismic events. The method acquires a global seismic event catalog, global ionospheric TEC data, and space weather indices, performs data preprocessing, and for each seismic event, selects those occurring during quiescent periods based on space weather conditions. Ionospheric TEC data within fixed observation windows and space windows are extracted and differiated with contemporaneous background TEC data to obtain ionospheric TEC difference values. Normalized statistical analysis is then performed on the quiescent period TEC difference values ​​and their frequency corresponding to global seismic events to obtain statistical characteristics of ionospheric TEC anomaly rates and frequencies. Random seismic events are generated globally for comparison. This method is comprehensive, programmable, and suitable for automated processing of large global samples, possessing good scientific rigor, scalability, and engineering application value.

The application discloses a kind of based on multi-source information fusion's human shadow operation information display method and system, it is related to meteorological information intelligent decision-making technical field, including, utilize graph neural network to carry out inference analysis to time series knowledge graph, identify cloud system development change and infer the evolution of cloud physical characteristics, predict the spatiotemporal range of operation potential area, generate accurate forecast conclusion and human shadow operation suggestion;Accurate forecast conclusion and human shadow operation suggestion are converted into visual instruction set, and evolution path is shown through highlighting core weather index, dynamic arrow display, and color overlay marks operation potential area and operation corridor, generates visual comprehensive situation chart.The application is analyzed by utilizing graph neural network to time series knowledge graph, realizes from historical mode automatically identifying operation potential area and predicting its dynamic evolution, improves the foresight and accuracy of human shadow operation decision.

The invention relates to the technical field of paleoclimate quantitative reconstruction, in particular to a method for rapidly and quantitatively reconstructing paleoclimate based on soil weathering indexes. The method comprises the following steps: selecting a paleo-temperature sensitive index and a paleo-rainfall sensitive index according to data of a paleo-soil sample; establishing a function based on a Chinese modern soil profile for reconstructing paleoclimate; a McLenna method is adopted to correct CaO *, and interference of carbonate and apatite on a result is eliminated; and substituting into the transfer function, correcting the influence of the dust deposition rate difference through a thickness weighted average method, and outputting the results of the annual average precipitation and the annual average temperature, thereby realizing the reconstruction of the paleoclimate.

Systems and methods for converting live weather data to a weather index for offsetting weather risk. Weather data source systems generate one or more weather data streams that include weather forecast model and observations data. A data distribution system receives a weather index request, identifies at least one instrument and at least one location associated with the request. Weather risk indication data is extracted among the weather data streams associated with the identified location based on predefined parameters associated with the identified instrument. The extracted data is converted into a set of weather index values corresponding to the location, based on a predetermined algorithm associated with the identified instrument. A weather index presentation package is generated that includes the set of weather index values for distribution to at least one user device. The weather index presentation package being distributed is updated concurrent with changes to weather risk indication data.

1. Name of the product in this design: Voice-activated graphical user interface for weather query on electronic devices. 2. Purpose of this design: An electronic device. 3. The key design feature of this product is its graphical user interface. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: For querying weather via voice. 7. Human-computer interaction method of graphical user interface: Ask questions by voice and display the answer information through the interface pop-up window. Design 1 and Design 2's main view shows the day's weather query via voice, with a pop-up window on the left side of the interface displaying the day's weather information. Design 3's main view is an interface for querying weather indices via voice, with a pop-up window on the left side of the interface displaying weather index information. Design 4's main view is an interface for querying the air quality index for multiple days via voice, with an air quality index information displayed in a pop-up window on the left side of the interface. Design 5's main view is an interface for querying the weather conditions of multiple locations on the same day via voice. A pop-up window on the left side of the interface displays the weather information for multiple locations on the same day. Design 6's main view is an interface for querying the weather for a certain location for the next week via voice. A pop-up window on the left side of the interface displays the weather information for that location for the next week. 8. Other situations requiring explanation: The red semi-transparent coating area is not fixed content and is not the part for which patent protection is sought; the design for which protection is sought does not include color.

The application relates to the technical field of logistics, and discloses a method for analyzing the overtime of a stop station, which comprises the following steps: collecting multi-source data, collecting real-time track data of the stop station, and collecting weather indexes, traffic congestion indexes and holiday factors through external data sources; constructing an overtime prediction model, inputting the preprocessed multi-source data into a neural network model to obtain an overtime rate prediction value and a confidence interval thereof; calculating a dynamic difference value, and marking the prediction result whose confidence reaches a preset threshold; performing abnormal risk detection, generating an abnormal risk index through an improved DBSCAN abnormal detection algorithm; generating a comprehensive decision output, integrating the overtime rate prediction value, the abnormal risk index and the dynamic difference value, calculating a dynamic ranking, and generating a risk analysis result containing a priority suggestion. The application can analyze the overtime of the stop station, dynamically display the overtime rule, and scientifically and reasonably evaluate the overtime problem.

The invention provides a computing power mode adjustment method and device of a photovoltaic automobile, electronic equipment and a medium, and relates to the technical field of online car hailing, and the method comprises the steps: determining a weather index representing the future weather condition; determining a judgment condition satisfied by the weather index from a plurality of judgment conditions, and taking the computing power mode corresponding to the judgment condition satisfied by the weather index as an expected computing power mode; and if the expected computing power mode is different from the computing power mode used by the photovoltaic automobile, hardware and / or software influencing the computing power are / is adjusted until the computing power mode used by the photovoltaic automobile is the expected computing power mode. Software and / or hardware consuming battery power can be adjusted according to weather conditions, and the battery power utilization rate is increased.

The invention discloses a construction method of a blood pressure meteorological risk dynamic evaluation index. The method comprises the following steps: using a mixing effect and introducing a cross basis function; selecting a random forest model to calculate a variation mean value, and dividing the variation mean value by the total variation to obtain a weight value; calculating an excess blood pressure value by adopting a mixed effect model, dividing the excess blood pressure value by the maximum excess blood pressure value, and multiplying by 10 to obtain a blood pressure meteorological index; a blood pressure meteorological index integrating various meteorological factors is constructed, risk levels are divided, risk early warning is carried out, decision buffer time is created for different subjects, people with hypertension and related managers are helped to actively cope with the influence of meteorological changes on blood pressure, and the adaptability of the people with hypertension to climate changes is improved; meanwhile, by screening meteorological factors sensitive to the blood pressure and evaluating the influence of composite exposure of the meteorological factors on the blood pressure, the method has more practical significance compared with existing single meteorological factor analysis, the interpretability of the blood pressure-meteorological association is improved, and therefore the method can also be popularized to other health outcomes caused by bad meteorological factors.

The invention discloses a sewage treatment plant biochemical unit carbon source prediction method based on time sequence data driving, which comprises the following steps: S1, carrying out data acquisition on a plurality of key process sections, and adopting a clock synchronization technology to keep multi-source data of different process sections consistent in time; s2, screening out core features with relatively high correlation with carbon source demands from the multi-source data by using a mutual information algorithm, and constructing a feature data set containing seasonal features and weather indexes; s3, constructing and training a hybrid prediction model, wherein the model comprises an input layer, a data preprocessing layer, a multi-scale attention layer, a bidirectional LSTM layer and a full-connection fusion layer; and S4, according to a set time interval, triggering model reasoning, inputting latest characteristic data, outputting a carbon source demand prediction curve in a future period of time, and automatically starting a rapid prediction mode when detecting that the water quality is suddenly changed. The method improves the accuracy of carbon source prediction.

The invention discloses a power adjustment method of an FSO and RF hybrid link and a transmitter, and the transmitter comprises an FSO transmitter and an RF transmitter, and can support the FSO link and the RF link at the same time. The method comprises the following steps: acquiring current weather index data including rainfall speed and visibility; and determining the transmitting power distribution proportion of the FSO link according to the first model, the weather index data and the channel state information, and adjusting the transmitting power of the FSO link and the RF link according to the proportion. The channel state information comprises respective signal-to-noise ratios of the FSO link and the RF link and is determined according to the weather index data. The input of the first model is weather index data and channel state information, the output of the first model is the transmission power distribution proportion of the FSO link, and the first model can minimize the bit error rate and maximize the channel capacity. Through the method, power adaptive distribution of the FSO and RF hybrid link under different atmospheric conditions can be realized, and performances such as transmission reliability and transmission efficiency of the system are improved.

The invention discloses a power grid low-temperature congelation disaster weather index construction method and system, and relates to the technical field of power grid disaster assessment, and the method comprises the steps: obtaining low-temperature congelation disaster events based on power grid observation data, carrying out the preliminary classification, and determining the disaster types of which weather indexes need to be established; evaluating the matching relationship between the temperature and humidity in the high temporal-spatial resolution meteorological data and the power grid observation data, and establishing a multi-element database corresponding to the low-temperature congelation disaster event; extracting multi-element features and combinations corresponding to different disaster types in a multi-element database through a deep learning algorithm; and analyzing the multi-element characteristics and combination to obtain a corresponding relation between the power grid congelation disaster and the combined meteorological condition, and establishing a weather index. According to the method, high-temporal-spatial-resolution meteorological data, power grid observation data, a deep learning algorithm and the like are utilized, basic characteristics which effectively extract influence low-temperature congelation meteorological conditions are constructed for power grid high influence meteorological conditions, and power grid congelation weather indexes are established.

The application provides a gale disaster weather index prediction system based on a long short-term memory network model, relates to the technical field of weather monitoring, and specifically comprises the following steps: collecting historical meteorological data of an area to be evaluated and a disaster area and duration of a gale disaster event occurring at a corresponding time; establishing an index prediction model based on a long short-term memory network, inputting the historical meteorological data into the model as a training set, inputting the disaster area and duration of the corresponding gale disaster as labels, and training the model; collecting meteorological data of the area to be evaluated in real time, obtaining a predicted disaster area and a predicted duration; collecting terrain height and slope data to correct the predicted disaster area and the predicted duration, comparing the corrected predicted disaster area and the predicted duration with preset threshold values, and dividing a risk level according to a result. The application of the long short-term memory network model can learn deep correlations between factors such as wind speed, humidity and temperature and the gale disaster event from historical meteorological data, and the accuracy of prediction is improved.

The invention belongs to the technical field of electricity price prediction, and discloses an electricity price prediction method and system based on statistics, and the method comprises the steps: obtaining an original data set which comprises a historical electricity price sequence, load data, a weather index and a fuel price; preprocessing the original data set to obtain a feature set after dimension reduction, and obtaining a component set through time sequence decomposition based on the feature set after dimension reduction; constructing a trend prediction model, a seasonal prediction model and a nonlinear residual prediction model according to the component set, and fusing prediction results to obtain an electricity price prediction sequence; comparing the electricity price prediction sequence with a historical actual electricity price prediction sequence to obtain an error evaluation result; hyper-parameters of the nonlinear residual prediction model are adjusted based on the error evaluation result and the electricity price prediction sequence, an optimized prediction model is obtained, the optimized prediction model is used for predicting the electricity price in the target time period, an electricity price prediction curve is obtained, a basis is provided for the electricity market, and the operation cost is reduced.