Abstract: 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.

Abstract: An adaptive method and device for predicting a weather-related characteristic of a surface of a segment of a road network. The method includes obtaining a location and of measuring a weather-related characteristic of the surface of the roadway of a road segment on which a measuring vehicle is traveling; predicting a weather-related surface characteristic of the road segment using a weather-observation history and a first prediction model associated with the road segment; associating a second prediction model with the road segment when a difference between the measured characteristic and the predicted characteristic is greater than a threshold; and transmitting to a vehicle a prediction made by applying the associated model to the weather-observation history.

Abstract: A computer device, having at least two long-range wireless profiles and coupled with a communication bus of a vehicle, receives a notice that a vehicle-centric download for the computer device, or for a vehicle device coupled to the communication bus, is pending from a remote server. The vehicle computer device determines the size and security requirement associated with the pending download, and a current operational state of the vehicle. If the size or security requirement is low, a consumer-centric profile may be used for the download even if the vehicle is currently being used. If the download file size is large or requires very high security, or if a user is currently using the computer device according to the consumer-centric profile, the computer device may schedule the download to occur after receiving a trigger event occurrence message.

Abstract: A method includes receiving a satellite image of an area and classifying each pixel in the satellite image as representing water, land or unknown using a model. For each of a plurality of possible water levels, a cost associated with the water level is determined, wherein determining the cost associated with a water level includes determining a number of pixels for which the model classification must change to be consistent with the water level and determining a difference between the water level and a water level determined for the area at a previous time point. The lowest cost water level is selected and used to reclassify at least one pixel.

Abstract: Various embodiments for a connection topology reconfiguration technique for photovoltaic (PV) arrays to maximize power output under partial shading and fault conditions using neural networks are disclosed herein.

Abstract: An energy management device according to an embodiment of the present invention comprises: a communication unit for receiving energy information of a system to which the energy management device belongs; a display unit for displaying any one energy information icon on the basis of the received energy information; and a control unit for displaying at least one energy information icon corresponding to a lower level of the energy information icon upon receiving a command to select an expansion icon corresponding to the energy information icon, and connecting the energy information icon having the selected expansion icon and the energy information icon corresponding to the lower level to energy nodes having different thickness according to the amount of energy.

Abstract: A storage unit stores ranking information including an index value relating to past rainfall and a corresponding date-time and damage information including details of damage that occurred due to past rainfall and a corresponding date-time. A real-time data reception unit acquires a spot value and a forecast value of current precipitation. Also, a comparison operation unit computes an index value relating to current rainfall using the acquired spot value and forecast value. The comparison operation unit specifies, with reference to the ranking information, the date-time of an index value relating to past rainfall whose similarity to the computed index value relating to current rainfall is not less than a threshold value. An information output unit presents, with reference to the damage information, details of damage that occurred in a period whose difference from the specified date-time of the index value relating to past rainfall is in a predetermined range.

Abstract: Aspects of the present invention disclose a method for recommending an activity based on a social media profile, IoT devices, and historical engagements of the user. The method includes one or more processors determining a past activity of a user based at least in part on social media posts and internet of things (IoT) enabled devices of the user. The method further includes determining a set of historical conditions corresponding to the past activity, wherein the set of conditions correspond to a positive sentiment of the user. The method further includes identifying a location of the user. The method further includes generating an activity recommendation based on the location of the user and the set of historical conditions corresponding to the past activity, wherein the activity recommendation includes a set of future conditions of a future activity, wherein the set of future conditions correlate with the set of historical conditions.

Abstract: The present disclosure describes various embodiments of systems, apparatuses, and methods for large-scale processing of weather-related data. For one such system, the system comprises a database of weather-related data providing from a plurality of weather monitoring stations and a plurality of interconnected processors for coordinating a data processing job for processing a set of input weather-related data from the database. Accordingly, the input data comprises sensor data from an array of weather monitoring stations positioned on an open shoreline during a hydrodynamic event, weather model data for the hydrodynamic event, and at least one of air-craft reconnaissance data or satellite reconnaissance data regarding the hydrodynamic event, wherein the plurality of interconnected processors are configured to assimilate the input data and generate, using machine learning, an improved weather prediction model for the hydrodynamic event. Other systems, apparatuses, and methods are also provided.

Abstract: A system and method for performing novel wind forecasting that is particularly accurate for forecasting over short-term time periods, e.g., over the next 1-5 hours. Such wind forecasting is particularly advantageous in wind energy applications. The disclosed method is anchored in a robust physical model of the wind variability in the atmospheric boundary layer (ABL). The disclosed method approach leverages a physical framework based on the unsteady dynamics of earth's atmosphere, and drives forecasting as a function of previously-observed atmospheric condition data observed at the same location for which a wind forecast is desired.

Abstract: Embodiments of the present disclosure provide a method and apparatus for predicting a severe convection weather. The method may include: acquiring a current radar echo map sequence, the current radar echo map sequence being a radar echo map sequence within a current time period; generating, based on the current radar echo map sequence, a future radar echo map sequence, the future radar echo map sequence being a radar echo map sequence within a future time period; and inputting the future radar echo map sequence into a pre-trained severe convection weather predicting model to obtain a severe convection weather intensity predicting map, where the severe convection weather predicting model is used to predict the intensity of a severe convection weather.

Abstract: A method includes displaying a first graphical representation on a screen. The first graphical representation includes a box-and-whisker plot of a dataset. The method also includes receiving a first interaction indication indicating a graphical user interaction by a user at a first interaction location on the first graphical representation. In response to the received first interactive indication, the method includes displaying a second graphical representation on the screen based on the first interaction indication, the second graphical representation including a density plot of the dataset having a respective scale equal to a corresponding scale of the box-and-whisker plot. The method also includes receiving a second interaction indication indicating the graphical user interaction by the user at a second interaction location on the second graphical representation, and in response, displaying an updated second graphical representation of the dataset on the screen based on the second interaction indication.

Abstract: Image modification using detected symmetry is described. In example implementations, an image modification module detects multiple local symmetries in an original image by discovering repeated correspondences that are each related by a transformation. The transformation can include a translation, a rotation, a reflection, a scaling, or a combination thereof. Each repeated correspondence includes three patches that are similar to one another and are respectively defined by three pixels of the original image. The image modification module generates a global symmetry of the original image by analyzing an applicability to the multiple local symmetries of multiple candidate homographies contributed by the multiple local symmetries. The image modification module associates individual pixels of the original image with a global symmetry indicator to produce a global symmetry association map.

Abstract: A measurement apparatus for determining a bending moment acting on a hollow cylindrical body in a current state as well as to a method of operating such a measurement apparatus. The measurement apparatus may include a sensor support structure, a sensor arrangement with sensors, and a processing system. The processing system may determine displacements of the inner surface of the hollow cylindrical body relative to the sensors based on the distances measured in the current state compared to the distances measured during an initial undeformed state, and determine the bending moment acting on the hollow cylindrical body based on the displacements.

Abstract: A photovoltaic system can include multiple photovoltaic power inverters that convert sunlight to power. An amount of power for each of the inverters can be measured over a period of time. These measurements, along with other data, can be collected. The collected measurements can be used to generate artificial neural networks that predict the output of each inverter based on input parameters. Using these neural networks, the total solar power generation forecast for the photovoltaic system can be predicted.

Abstract: A method, apparatus and computer program product for determining a rain event warning are described herein. In the context of a method, an indication of the rain event warning for one or more locations may be received. The method may obtain, for a respective rain event warning, sensor data corresponding to a weather condition within a region that includes the location with which the respective rain event warning is associated. The method may evaluate the sensor data to determine whether the sensor data is indicative of the weather condition (e.g., rain). The method may determine a rain event warning confidence based at least in part on evaluation of the sensor data. The method may cause the rain event warning to be published in an instance in which the rain event warning confidence satisfies a confidence threshold.

Abstract: Systems and methods include one or more dwelling sensors configured to generate sensor data representative of characteristics of a dwelling; a telematics device configured to generate telematics data representative of operational characteristics of a vehicle; and an analysis server. The analysis server receives the sensor data; receives the telematics data; receives credit information regarding an insured; and determines one or more insurance policy decisions based upon the sensor data, the telematics data, and the credit information the one or more insurance policy decisions comprising: a premium amount, a deductible amount, a coverage amount, a coverage term, or any combination there of for the insured.

Abstract: A flood detection device includes a detection result acquisition section, a weather information acquisition section and an identification section. The detection result acquisition section acquires a detection result that, on the basis of a plurality of kinds of running state data relating to running of a vehicle, detects flooding of a road on which the vehicle is running. The weather information acquisition section acquires weather information including at least one of rainfall information representing a measured rainfall amount in a region in which the vehicle is running or rainfall estimation information representing an estimated rainfall amount. The identification section uses the respective acquisition results of the detection result acquisition section and the weather information acquisition section to identify flooding of the road.

Abstract: To provide a precipitation particle classification apparatus for obtaining a proper classification result of precipitation particles based on information from a plurality of radar devices. The precipitation particle classification apparatus includes a data processing part, a fuzzy processing part, a coordinate conversion part, an interpolation part, and a classification part. The data processing part acquires polarization parameters obtained by reflection on the precipitation particles from each of the plurality of radar devices which are arranged at different positions and have a part of a scanning area overlapping with each other. The fuzzy processing part obtains a polar coordinate distribution evaluation value indicating the distribution in polar coordinates of an evaluation value indicating the degree of attribution to each type of precipitation particles from polarization parameters by using a fuzzy inference.

Abstract: A boom sprayer includes any number of components to treat plants as the boom sprayer travels through a plant field. The components take actions to treat plants or facilitate treating plants. The boom sprayer includes any number of sensors to measure the state of the boom sprayer as the boom sprayer treats plants. The boom sprayer includes a control system to generate actions for the components to treat plants in the field. The control system includes an agent executing a model that functions to improve the performance of the boom sprayer treating plants. Performance improvement can be measured by the sensors of the boom sprayer. The model is an artificial neural network that receives measurements as inputs and generates actions that improve performance as outputs. The artificial neural network is trained using actor-critic reinforcement learning techniques.

Abstract: A system (100) for using mobile data to improve weather information is provided. The system (100) includes a weather prediction station (120) configured to receive stationary observation data provided by a plurality of stationary weather stations (110) along with data from a plurality of input weather models (115) and generate unified weather model estimates based on the stationary observation data, the input weather model data, and a processor (130). The processor (130) is configured to aggregate mobile observation data provided by a plurality of non-stationary sensors (140) and use the aggregated mobile observation data to adjust the weather model estimates.

Abstract: A method for downscaling a weather forecast including obtaining a sky image and location data indicative of a user location via a mobile computing device; sending the location data to a weather forecast provider; generating, by the weather forecast provider, a local weather forecast for the user location; sending the local weather forecast to a server; determining, by the mobile computing device, cloud cover data and cloud type data based on the sky image, and sending the cloud cover data and cloud type data to the server or sending the sky image to the server and determining cloud cover data and cloud type data based on the sky image; increasing the resolution of the local weather forecast based on the cloud cover data and the cloud type data, thus obtaining a downscaled local weather forecast; and, sending the downscaled local weather forecast to the mobile computing device.

Abstract: According to one embodiment, there is provided an aviation weather control system including: a processing unit configured to receive weather information of an area to be overseen including a vertically integrated liquid water content, and specify a weather phenomenon affecting an airplane based on the received weather information; and a notification unit configured to notify the weather phenomenon specified by the processing unit.

Abstract: Currently available weather forecasts, which include a specific snowfall accumulation or range, do not convey the probability that snowfall will be within the forecasted snowfall accumulation range, probabilities of other snowfall accumulation amounts, or a forecaster's level of confidence. A snowfall probability distribution forecasting system is disclosed that uses a rules-based process to leverage third party weather forecasts, including members of ensemble forecasts, to generate snowfall probability distributions forecasting the most likely snowfall accumulation range, the probability that snowfall accumulation will be within the most likely snowfall accumulation range, and probabilities that snowfall accumulation will be outside of the most likely snowfall accumulation range. To ensure consistency with the deterministic forecast, the snowfall probability distribution may be shifted based on a deterministic forecast.

Abstract: A plurality of events associated with each of a plurality of computing nodes that form part of a network topology are monitored. The network topology includes antivirus tools to detect malicious software prior to it accessing one of the computing nodes. Thereafter, it is determined that, using at least one machine learning model, at least one of the events is indicative of malicious activity that has circumvented or bypassed the antivirus tools. Data is then provided that characterizes the determination. Related apparatus, systems, techniques and articles are also described.

Abstract: Long-term photovoltaic system degradation can be predicted through a simple, low-cost solution. The approach requires the configuration specification for a photovoltaic system, as well as measured photovoltaic production data and solar irradiance, such as measured by a reliable third party source using satellite imagery. Note the configuration specification can be derived. This information is used to simulate photovoltaic power production by the photovoltaic system, which is then evaluated against the measured photovoltaic production data. The simulated production is adjusted to infer degradation that can be projected over time to forecast long-term photovoltaic system degradation.

Abstract: Method of forecasting heat output of a solar collector. First, heat output for a plurality of solar collectors is simulated, located at respectively different geographic locations but having the same solar collector settings as the solar collector to be forecasted. The simulation is performed by calculating a dataset of theoretical heat outputs for the plurality of solar collectors, based on acquired 802 related weather data. From the calculated dataset a function is adjusted 810, the function defining the theoretical heat output of any solar collector related to its geographic location, e.g. latitude, solar Direct Normal Irradiation, DNI, and collector settings, e.g. operation temperature, and forecasting the heat output of the solar collector based on the adjusted function.

Abstract: A computer-implemented method simulates an atmospheric phenomenon within a simulation volume. At each time step of a plurality of time steps, the method automatically determines a temperature distribution of the atmospheric phenomenon based on an assumption of fixed volume, and then automatically determines a velocity field of the atmospheric phenomenon, based on an assumption of adiabatic expansion.

Abstract: This invention is to provide a method to entirely and effectively shade fixed tracts of land, such as school yard or athletics stadium, etc., with no roof, pole to support roof, or the like. To fix a sheet to multiple flying objects so that such sheet forms a fixed size of surface and make such flying objects fly in accordance with flying positions (including heights) decided based on elements, such as positions of the sun, etc.

Abstract: A computerized method of processing data for use in weather modeling is provided. The method includes receiving, from a first data source, by a first server, microwave link data including signal attenuation information. The method also includes pre-processing, in real time, by the first server, the microwave link data, thereby producing pre-processed microwave link data. The method also includes storing the pre-processed microwave link data in a first data store. The method also includes receiving, from the first data store, by a second server, the pre-processed microwave link data. The method also includes processing, on a scheduled routine, by the second server, the pre-processed microwave link data using a data transform, thereby producing first weather data.

Abstract: A system and method for outputting weather data associated with a user-specified location based on a user-specified weather inquiry, including weather data output based on user-specified weather conditions, locations output based on a user-specified weather inquiry, notifications output regarding weather-related warnings, and notifications output based on weather-related notification thresholds.

Abstract: Methods and systems for process speed-based forecasting, in which historical data of a process is first aligned to account for latency in the process. Optionally, incorporation of memory and/or clustering can be included in the pre-processing of the historical data before being used to train a machine learning model.

Abstract: A method for determining a location of a pollutant source, comprises: obtaining wind direction information for a region of interest; measuring pollutant concentrations for a first plane of interest in the region of interest with a movement determined based on the wind direction information using a drone equipped with a chemical sensor, the first plane of interest being determined based on a current altitude of the drone; lowering by a predetermined descending distance an altitude of the drone from a descent position on the first plane of interest determined on the basis of a result of the measuring; and determining a pollutant source candidate area based on a location of the drone after the lowering if the lowered altitude of the drone is equal to or less than a predetermined reference altitude.

Abstract: A system for identifying information in high dimensional, low latency streaming data having dynamically evolving data patterns. The system processes, continuously and in real-time, the streaming data. Processing includes filtering the data based on event data to identify diagnostic data points by comparing the event data with an experimental design matrix and performing a modeling operation using the identified diagnostic data points in order to identify efficiently any current and emerging patterns of relationships between at least one outcome variable and predictor variables. The at least one a-priori, pre-designed experimental design matrix is generated based on combinations of the predictor variables and at least one outcome variable. The experimental design matrix is also generated based on at least one of main effects, limitations, constraints, and interaction effects of the predictor variables and combinations.

Abstract: A server system comprising a processor configured to manage an extensible taxonomy of impression tags for categorizing the plurality of locations, monitor content sources for visitor impressions of the plurality of locations and extract a plurality of impression tag inputs from the visitor impressions, each impression tag input including an identified impression tag, a visited location of the plurality of locations, and visited location context data including a visited time interval of the plurality of time intervals, for each impression tag input, aggregate that impression tag input into aggregated impression tag input data in a location profile of the plurality of location profiles that is associated with the visited location of that impression tag input, and for each location profile, select one or more categorizing impression tags from the extensible taxonomy of impression tags based on at least the aggregated impression tag input data of that location profile.

Abstract: Various aspects of the present disclosure generally relate to sensor targets. In some aspects, a method may include obtaining a detection resolution of a sensor that is to detect a target on a roadway; obtaining a designated speed limit of the roadway; estimating an exposure time of the target based on the detection resolution and the designated speed limit; determining, based on the exposure time, a target dimension of the target and a quantity of surface depths of the target; generating a code for the target based on the quantity of surface depths, wherein the code corresponds to a physical configuration of the target; and storing, in a mapping associated with the sensor, the code in association with the target to permit the target to be identified by the sensor. Numerous other aspects are provided.

Abstract: The present invention relates to a wireless sensing apparatus 100. A wireless sensing apparatus 100 comprises a housing 200 containing one or more sensor devices 120A, 120B each configured to detect an environmental attribute in the vicinity of that sensor device, wireless communication circuitry 130 configured to transmit telemetry data from the one or more sensor devices 120A, 120B, and Near Field Communications (NFC) circuitry 140 configured to receive configuration data for the wireless sensing apparatus from an external device. The wireless sensing apparatus may be used for detecting an environmental attribute of a structure, such as a tunnel or building.

Abstract: A precipitation nowcasting method using dynamic motion vectors includes calculating a multiscale motion vector of a radar precipitation motion vector and a numerical model precipitation motion vector by changing spatial scale of cross correlation analysis for reach of a preset time interval from precipitation data obtained through a dual polarization radar, calculating a dynamic motion vector by merging the radar precipitation motion vector and the numerical model precipitation motion vector, generating a precipitation development and dissipation map through precipitation tracking and matching using the dynamic motion vector, and outputting a precipitation forecast field for each forecast time by applying the dynamic motion vector and the precipitation development and dissipation map to Lagrangian backward extrapolation. Accordingly, it is possible to achieve realistic precipitation forecast field simulation.

Abstract: Techniques described herein include utilizing a mobile device as a proxy receiver for a vehicle such that a driver of the vehicle can be presented driving assistance information based on messages received by the mobile device. The mobile device can determine that it is temporally located with the vehicle. If so, the mobile device can be configured to receive messages from other entities (e.g., vehicles, roadside units, traffic signals, and the like) in a vehicle-to-everything network. On reception, the mobile device may determine whether a received data message is relevant to the vehicle. In response to determining that the data message is, in fact, relevant to the vehicle, the mobile device may provide driving assistance information that is generated based at least in part on the information provided in the received data message.

Abstract: The systems and methods described herein provide a mechanism for collecting information from a diverse suite of sensors and systems, calculating the current precipitation, atmospheric water vapor, or precipitable water and other atmospheric-based phenomena based upon these sensor readings, and predicting future precipitation and atmospheric-based phenomena.

Abstract: Traditionally, forecasting models were developed using pest or disease instances collected through pest or disease surveillance. The present disclosure relates to pest forecasting using historical pesticide usage information thereby obviating need for voluminous and time consuming effort of collecting site specific data. Firstly forecasting models for different pests or diseases of different crops are generated based on historical data on pesticide usage and historical weather data collected for a geo-location under consideration. The model is validated and adapted with the current scenario of pests. Current scenario is captured using image samples sent from the field or farm through participatory sensing platform. The images are then analyzed to extract information like actual pest infestation in the field, severity, if there was infestation and the like. This analyses helps to derive the actual pest infestation instances in the field.

Abstract: A system and method for forecasting perceived transitions to the four annual seasons in geographic areas is disclosed. The perceived transitions are identified by comparing forecasted daily temperatures in each geographic area to thresholds generated based on normal daily temperatures in those geographic areas. The forecasted daily temperatures may be calculated using both forecasted temperatures and forecasted perceived ambient temperatures (calculated using both temperature and humidity, cloud cover, sun intensity, and/or wind speed).

Abstract: Methods and systems for damage assessment and restoration. One system includes an electronic processor configured to receive weather data for an area of interest. The electronic processor is also configured to determine a first damage prediction for the area of interest using a damage prediction model developed with machine learning using training data, the training data including historical weather data for the area of interest and associated damage. The electronic processor is also configured to determine a restoration time estimate based on the first damage prediction for the area of interest based on different resource allocations. The electronic processor is also configured to transmit a damage assessment report for display on a user device, where the damage assessment report includes the restoration time estimate.

Abstract: A precipitation index estimation apparatus includes a data collection unit and an estimation processing unit. The data collection unit is configured to collect rain-related data for estimating a precipitation index indicating an intensity of precipitation within a predetermined period from vehicle state information generated in one or more vehicles. The estimation processing unit is configured to carry out a statistical processing of the collected rain-related data and estimate the precipitation index within the predetermined period. The estimation processing unit is configured to correct, before the statistical processing, a value of the rain-related data to be used for the statistical processing, according to speed of a vehicle at the time at which the rain-related data is acquired.

Abstract: A method for estimating quantitative precipitation by combining observation data of a weather radar and rain gauges includes: acquiring original accumulated data of rain gauges and original accumulated precipitation data of a weather radar to obtain rain gauge-weather radar data G/R pairs matched in the same grid; calculating an observation error of the original accumulated precipitation data of the weather radar through the G/R pairs, and detecting abnormal data to generate an initial correction factor field; determining whether a distance correlation exists between the initial correction factor field and the observation error, and if yes, adjusting the initial correction factor field, and correcting the original accumulated precipitation data of the weather radar through the adjusted correction factor field to obtain corrected accumulated precipitation data of the weather radar; and if not, obtaining the corrected accumulated precipitation data of the weather radar directly through a mean field bias (MFB) f

Abstract: A computer system provides personalized location-based weather services. Weather data for a location is processed to generate a plurality of panels, wherein each panel comprises weather information organized according to a topic of the panel. An order is determined for the plurality of panels, wherein the order is based on one or more factors including an interaction of a user with one or more previously presented panels, a selected event being identified, and a proximity of a forecasted event to a current time. A visualization is generated on a display, including the plurality of panels configured to be navigated according to the determined order. Embodiments of the present invention further include a method and program product for providing personalized location-based weather services in substantially the same manner described above.

Abstract: A spatial autocorrelation machine learning-based downscaling method of satellite precipitation data includes obtaining the TRMM precipitation data and the land surface parameters; preprocessing the land surface parameters to obtain DEM, day land surface temperature, night surface land temperature, day-and-night land surface temperature difference and NDVI with spatial resolutions of 1 km and 25 km; performing a spatial autocorrelation analysis of the TRMM precipitation data to obtain an estimated spatial autocorrelation value of the precipitation data with a spatial resolution of 25 km; downscaling the spatial resolution of the spatial autocorrelation value of the precipitation data from 25 km to 1 km; establishing a nonlinear regression model; obtaining a precipitation downscaling data with a spatial resolution of 1 km based on the nonlinear regression model. A system and a terminal are also provided.

Abstract: Apparatuses, systems and methods associated with a travel assistance system. A wearable personal navigation device may include a communication system, an indicator, and a processor coupled to the communication system and the indicator. The processor may be configured to generate a request for a navigation path from a location to a destination and transmit the request to a node of the network. The processor may be configured to determine the direction of travel from the location of the user based on a first navigation path received from the node of the network in response to the request, wherein the first navigation path includes at least one modification from a second navigation path, wherein the modification is based on data received by the network from a remote device that indicates an object, and cause the indicator to indicate the direction of travel. Other embodiments may be described and/or claimed.

Abstract: The calculation of the variance of a correlation coefficient matrix for a photovoltaic fleet can be completed in linear space as a function of decreasing distance between pairs of photovoltaic plant locations. When obtaining irradiance data from a satellite imagery source, irradiance statistics must first be converted from irradiance statistics for an area into irradiance statistics for an average point within a pixel in the satellite imagery. The average point statistics are then averaged across all satellite pixels to determine the average across the whole photovoltaic fleet region. Where pairs of photovoltaic systems are located too far away from each other to be statistically correlated, the correlation coefficients in the matrix for that pair of photovoltaic systems are effectively zero. Consequently, the double summation portion of the calculation can be simplified to eliminate zero values based on distance between photovoltaic plant locations, substantially decreasing the size of the problem space.

Abstract: A risk prediction and early warning method for water environments based on a water environment model predicting pollution discharge information for all pollution sources in a watershed, and including: selecting pollution sources requiring environmental risk prediction and early warning and dividing these into different risk prediction/early warning levels; determining from official environmental monitoring data and literature research initial elements for environmental pollution risk evaluation; obtaining principal pollution elements affecting pollution events; generating a plurality of environmental risk prediction and early warning models; forming a comprehensive fuzzy risk prediction and early warning model by combining the several risk prediction and early warning models having the best selective performance; inputting principal pollution element values into the comprehensive fuzzy risk prediction and early warning model, and predicting risk values for pollution events at pollution sources.