Abstract: Systems, apparatuses, and methods of an event-based automatic transaction on behalf of a user include and not limited to, determining, based on a plurality of information sources including a plurality of news information sources independent of a particular physical location, a probability of an event occurring, the probability being based on a predetermined percentage of news information sources indicating that the event is going to occur or is occurring, in response to the probability of the event occurring satisfying a predetermined threshold corresponding to the predetermined percentage, determining a location impacted by the event, in response to determining that the location of the user is proximate to the location impacted by the event, initiating a transaction with a mobile banking client application linked to an authorized financial account on behalf of the user, the authorized financial account being associated with the user and provided by the financial institution computing system.

Abstract: A life consumption estimation device for estimating life consumption of at least one part of a gas turbine includes: a predicted air temperature information acquisition unit configured to acquire predicted air temperature information regarding a future air temperature; a predicted load information acquisition unit configured to acquire predicted load information regarding a future load of the gas turbine; a gas turbine state quantity estimation unit configured to estimate at least one gas turbine state quantity regarding a future state quantity of the gas turbine, on the basis of predicted air temperature information acquired by the predicted air temperature information acquisition unit and the predicted load information acquired by the predicted load information acquisition unit; and a life consumption estimation unit configured to estimate the life consumption of the at least one part, on the basis of the gas turbine state quantity estimated by the gas turbine state quantity estimation unit.

Abstract: An automated global weather notification system is provided. The automated global weather notification system is capable of obtaining observational weather data, including data form of forecast grids, and applying business rules and conditional variables to that data. Based on the business rules and conditional variables, notifications are generated. Relevant users are identified in particular geographic areas and notifications are delivered to those users via, for example, SMS, MMS, email, or other methods of electronic information delivery.

Abstract: An apparatus, method, and non-transitory medium for betting on weather predictions are disclosed herein. A plurality of longitude and latitude coordinate pairs may be received from a remote device. The display device may render data representing a binary option based on whether a storm will make landfall within the certain radius. A request to purchase the binary option may be received. It may be determined whether the landfall location corresponds to a zip code associated with the given longitude latitude pair in the memory.

Abstract: A database (102) of a rocket launch assistance device records orbit forecast information of a mega-constellation satellite group (301) that is acquired from a space information recorder included in a mega-constellation business device and space object information that is acquired from a rocket launch business device. The orbit forecast information of the mega-constellation satellite group (301) is composed of a prediction value of an orbit of at least one representative satellite (331) out of the mega-constellation satellite group (301) and a prediction value of an orbit of a constituent satellite (332), which is a value relative to the prediction value of the orbit of the representative satellite (331).

Abstract: A heating installation for premises includes a controller coupled to an air source heat pump; a premises heating arrangement; and a local weather sensing arrangement. The controller is configured to receive weather forecast data from an external source, and local weather status information from the local weather sensing arrangement. The controller is also configured to set a control algorithm based on both the weather forecast data and the local weather status information, and control a supply of energy from the air source heat pump to the heating arrangement based on the set control algorithm; and increasing energy input into the heating arrangement in anticipation of a forecast fall in the temperature of the air from which the air source heat pump extracts energy. A method of controlling a premises heating installation is also disclosed.

Abstract: A processor may receive weather event data. The processor may determine, utilizing an artificial intelligence model mapping weather events having weather impacts with a higher likelihood of occurrence proximate to each other in the latent space, a weather impact associated with a weather event. In some embodiments, the artificial intelligence model may be trained using historical weather event data and historical weather impact data associated with the historical weather event data. The processor may output the weather impact associated with the weather event to a user.

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 at least one weather monitoring station and at least one processor 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 the at least one weather monitoring station 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 at least one processor is 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: An embodiment for dynamically arranging vehicles on a smart crossing is provided. The embodiment may include receiving data relating to a maximum carrying capacity of a smart crossing having one or more sensors. The embodiment may also include predicting a current load carrying capacity of the smart crossing. The embodiment may further include identifying a number of vehicles traveling towards the smart crossing within a pre-defined distance of the smart crossing. The embodiment may also include identifying one or more specifications and a current arrangement of each vehicle. The embodiment may further include executing a digital twin simulation of a digital twin model of each vehicle driving across the smart crossing. The embodiment may also include in response to determining the current load carrying capacity is exceeded, assigning a priority level to each vehicle. The embodiment may further include predicting a modification of the current arrangement of each vehicle.

Abstract: A vehicular central monitoring system includes a forward-viewing camera, a plurality of non-vision sensors and an electronic control unit. A wireless communication device wirelessly communicates to a central server (i) vehicle data indicative of operation of the vehicle and (ii) environment data indicative of the environment in which the vehicle is traveling. The central server processes the wirelessly received vehicle data and environment data. Responsive to processing at the central server of the vehicle data and environment data received at the central server from the vehicle, the central server determines if the vehicle is at or approaching a hazardous condition. Responsive to the determination that the vehicle is at or approaching the hazardous condition, the vehicular central monitoring system (i) alerts a driver of the vehicle of the determined hazardous condition and/or (ii) controls a vehicle system of the vehicle to mitigate the determined hazardous condition.

Abstract: An apparatus, method and computer program product are provided for determining a state of visibility for a road object. In one example, the apparatus receives temporal data, calculates an orientation of a light source with respect to a road object using the temporal data, and predicts a state of visibility for the road object based on the orientation of the light source. In another example, the apparatus determines an artificial light source associated with a road object, receives attribute data associated with the artificial light source, determines a state of the artificial light source using the attribute data, and predicts a state of visibility for the road object based on the state of the artificial light source.

Abstract: A method of determining a corrected wind speed in the region of a wind turbine including the steps of measuring a wind speed in the region of a wind turbine, determining a force exerted on at least one rotor blade by the wind, determining a wind speed difference value which is dependent on the determined force and determining a corrected wind speed by correcting the measured wind speed in dependence on the wind speed difference value. A wind turbine for carrying out the method.

Abstract: Embodiments of the present invention provide the use of a conditional Generative Adversarial Network (GAN) to simultaneously correct and downscale (super-resolve) global ensemble weather or climate forecasts. Specifically, a generator deep neural network (G-DNN) in the cGAN comprises a corrector DNN (C-DNN) followed by a super-resolver DNN (SR-DNN). The C-DNN bias-corrects coarse, global meteorological forecasts, taking into account other relevant contextual meteorological fields. The SR-DNN downscales bias-corrected C-DNN output into G-DNN output at a higher target spatial resolution. The GAN is trained in three stages: C-DNN training, SR-DNN training, and overall GAN training, each using separate loss functions. Embodiments of the present invention significantly outperform an interpolation baseline, and approach the performance of operational regional high-resolution forecast models across an array of established probabilistic metrics.

Abstract: Methods, systems, and computer readable media for predictively determining a risk of damage to a property are provided. To determine the risk, a high resolution virtual model of a region that includes the property is obtained. The virtual model is imported into a simulation environment. One or more of the simulation parameters are set based on historic weather data for the region. For example, each parameter may be associated with a probability distribution derived based on the historic weather data that is sampled prior to executing the simulation. One or more simulations are executed in accordance with the sampled inputs to simulate the likely weather patterns the property will experience. The result of the simulation is analyzed to determine the predicted risk of damage to the property.

Abstract: A method of forecasting transport of a region of plasma density enhancement within a polar region is provided. The method comprises: providing a convection model for predicting electrostatic potential distribution within the polar region over time; determining the total electron content distribution within the polar region; and determining whether reconnection is occurring. If reconnection is determined to be occurring, the method comprises: identifying a region of plasma density enhancement using the total electron content distribution; and calculating a velocity of at least a portion of the plasma density enhancement using the convection model, such that transport of a region of plasma density enhancement over time can be forecast.

Abstract: An intensification mechanism analysis and anthropogenic climate change signal identification method for terrestrial water cycle (TWC) in dry and wet regions, includes: identifying dry regions and wet regions worldwide with observed data; quantifying a precipitation increasing rate; calculating a regional warming rate and a precipitation response warming rate, and investigating a difference between dry regions and wet regions; identifying a fingerprint pattern of a precipitation increase in dry regions and wet regions in response to global warming, and calculating a signal-to-noise ratio (SNR) to quantify a possibility of an anthropogenic climate change signal in dry regions and wet regions; and detecting different external forcing signals in a precipitation change of dry regions and wet regions with an optimal fingerprinting method, and quantifying a contribution of each of the different external forcing signals to the precipitation change.

Abstract: The present disclosure provides systems and methods for flexible renewable energy power generation. The present disclosure also provides systems and methods for firming power generation from multiple renewable energy sources.

Abstract: A water level monitoring and reporting system coupled to a pumping system, using a well sensor mote coupled to a flow meter, wherein the mote sends uplinks, with data collected by the flow meter, via LoRaWAN to a gateway to a server and thence to a readable application interface.

Abstract: Event intensity assessment can include detecting an event description within textual input received via a data communication network. An event-correlated data structure based on the event can be generated, the event-correlated data structure including an event descriptor corresponding to the event. An event sentiment can be determined based on the event descriptor and an event impact based on a quantitative temporal-spatial measure corresponding to the event. An event intensity can be determined based on the event sentiment and event impact. A GUI can be modified in response to the event intensity exceeding a predetermined threshold. The GUI can be modified to indicate the event and the event intensity.

Abstract: The invention relates to pre-conditioning an animal(s) to (the risk of) heat stress. The invention provides a control device for controlling a lighting device to illuminate at least one animal in a space, wherein the control device is configured to: obtain prediction data indicative of a value of an environmental condition in said space during a future time period; determine said value of the environmental condition based on the prediction data; determine a prediction of heat stress of the at least one animal in said space during the future time period if said value of the environmental condition falls within a predefined limit for heat stress; control, upon determining said prediction of heat stress, a lighting device to illuminate the at least one animal in said space with a lighting characteristic at least partly before said future time period.

Abstract: Subject soils are classified using a sensing tool. By profiling each of a number of first locations that have a ground truth classification, using a deployed sensing tool, digital soil properties of new locations without ground truth classifications can be obtained to determine corresponding classifications for the new locations. This allows information related to classifications to be utilized for optimal use of the new locations.

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: A photovoltaic array fault diagnosis method based on composite information is provided. The method includes: collecting and preprocessing composite information data of photovoltaic array working state, including image data and text data; using the image data of photovoltaic array working state to train a pre-established fault classification model of deep convolutional neural network, to thereby obtain an image fault classification model; using the text data of photovoltaic array working state to train a pre-established fault classification model based on a support vector machine, to thereby obtain a text fault classification model; fusing the image fault classification model and the text fault classification model by logistic regression algorithm to obtain a fusion model, and training the fusion model using the composite information data of photovoltaic array working state to thereby obtain the photovoltaic array fault diagnosis model.

Abstract: Calculating energy loss during an outage, including: determining that windspeed data indicating device windspeeds measured at an energy generating device are unavailable within a particular time duration; receiving meteorological data associated with a site location of the energy generating device, the meteorological data including meteorological windspeed data collected within the particular time duration; and predicting one or more estimated device windspeeds at the energy generating device during the particular time duration based on the meteorological data using a trained model for the energy generating device, the trained model being trained using a machine learning algorithm that utilizes historical meteorological windspeed data associated with the site location collected during a previous time duration and corresponding historical device windspeed data measured at the energy generating device during the previous time duration.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: A computing system can receive monitoring data from the one or more monitoring services. Based on the monitoring data, the system can predict that an event will occur in a given area and determine a subset of users within the given area. For each respective user of the subset of users, the system generates interactive content for display on a computing device of the respective user, the interactive content providing the respective user with contextual information regarding the predicted event.

Abstract: A spatial auto-correlation clustering method for a remote correlation mode. By taking the degree of remote correlation between each spatial grid cell and an adjacent cell thereof into consideration, and on the basis of the definition of a local Moran index, an original value of a correlation coefficient is used without performing centralization processing, thereby improving a local Moran index calculation formula to obtain a new local indicator of spatial auto-correlation (LISAAC), such that the detection of a significant positive or negative remote correlation aggregation range is realized, and the identification of an abnormal value (that is, a non-significant or negative-value grid appears in a significant positive-value area, and a non-significant or positive-value grid appears in a significant negative-value area) is realized.

Abstract: The present disclosure provides a method and system for hierarchical processing of gas data based on smart gas Internet of Things (IoT). The method is executed via the smart gas IoT. The method includes obtaining gas data sending and receiving information of at least one node in at least one period. The method also includes predicting a gas data communication load of the at least one node in at least one future period based on the gas data sending and receiving information. The method further includes determining a time-sharing processing scheme for the at least one future period based on the gas data communication load of the at least one node in the at least one future period.

Abstract: In accordance with one aspect of the present disclosure, there is provided an apparatus for detecting rain using a wire mesh sensor including: a wire mesh which is configured to include a plurality of transmitters and a plurality of receivers; and a fixing part for fixing the wire mesh; wherein the plurality of transmitters supply electricity to the wire mesh, and wherein, in response to rain being positioned between a specific transmitter among the plurality of transmitters and a specific receiver among the plurality of receivers, the specific receiver is configured to receive the electricity from the specific transmitter and then transmit the electricity to a measuring part, to thereby allow the measuring part to measure conductivity. This hemispherical apparatus can detect rain accurately by making the incident angles of the rain to be vertical regardless of the directions of the rain.

Abstract: Road condition prediction for potentially hazardous road segments is described. For roadways that may contain accumulated frozen precipitation, a road segment for road condition prediction is selected based on weather conditions. Various models including a solar radiation budget model, a permanent structures model, a dynamic structures model, and a road condition model are generated for the selected road segment and account for shading effects on the road segment caused by objects near the road segment. A road condition prediction for hazardous conditions on the road segment is determined based on the road condition model and provided to a driver to alert the driver of any potentially hazardous conditions.

Abstract: A method of controlling an air blowing apparatus includes: determining whether there is precipitation through a rain sensor by a controller; determining whether the air blowing apparatus is in an automatic mode in a precipitation condition by the controller; determining a vehicle speed when the air blowing apparatus is in the automatic mode in the precipitation condition; and setting power and a spray angle of the air blowing apparatus by comparing a rainfall received from the rain sensor to a stored rainfall by the controller. Setting the power and the spray angle of the air blowing apparatus includes compensating the spray angle and a spray amount by measuring a flow speed and a flow angle of rainwater through the rain sensor by the controller.

Abstract: The present disclosure provides systems and methods for flexible renewable energy power generation. The present disclosure also provides systems and methods for firming power generation from multiple renewable energy sources.

Abstract: A system and method provides a route and turn-by-turn directions based on estimates of current and future traffic along the route. A client device may request turn-by-turn directions between an initial and a final location. A server may identify a plurality of routes between the locations. Each route of the plurality of routes may be divided into route segments. For each route segment of a particular route, the server may estimate a travel time. The travel time may be based on estimated vehicle volume data generated from information received from other users vehicle Based on the estimated travel time for each route segment of a particular route, the server may estimate a total travel time for the particular route. The server may repeat this estimate for each of the plurality of routes between the locations and select the route with the lowest estimated travel time. Based on the selected route, the server may generate turn-by-turn directions and transmit the directions to the client device for display.

Abstract: Reduced-size user interfaces for providing weather information are disclosed. At an electronic device with a touch-sensitive display, indications of a location and a temperature at the location may be displayed. In some examples, a user may provide input through a touch on the touch-sensitive display and/or through a rotation of a rotatable input mechanism to display additional weather information, such as weather information for another location, another temperature, another time, and so forth. In some examples, the device may obtain data representing an upcoming activity, determine whether the activity is to begin within a threshold amount of time, and display weather information based on the upcoming activity. In some examples, the device may display an affordance at a position to indicate the time of day for which a weather condition is provided.

Abstract: Systems and methods for machine-learning-based aircraft icing prediction use supervised and unsupervised learning to process real-time environmental data, such as onboard measurements of outside air temperature and dew point, to predict a risk of icing and determine whether to issue an icing risk alert to an onboard crewmember or a remote operator, and/or to recommend an icing avoidance maneuver. The systems and methods can use reinforcement learning to generate a confidence metric in the predicted risk of icing, to determine a time or distance to predicting icing, and/or to not issue an alert or recommend a maneuver in consideration of historical data in a “library of learning” and/or other flight data such as airspeed, altitude, time of year, and weather conditions. The predictive systems and methods are low-cost and low-power, do not require onboard weather radar, and can be effective for use in smaller aircraft that are completely icing-intolerant.

Abstract: Systems and methods for incorporating social content items into a produced video are provided. The system presents a producer interface to a user that allows the user to query for social content items. The user may then select and arrange social content items in an on-air queue. In an on-air mode, the system generates a broadcast-ready on-air format of the social content items and provides a video stream including the broadcast-ready social content items in the on-air queue to a video production system. The broadcast-ready social content items are incorporated into a produced video by the video production system. The user may navigate through the social content items in the on-air queue while on camera as part of the produced video.

Abstract: Systems and methods for improving the use of precipitation sensors, such as radar and rain gauges, are described herein. In an embodiment, an agricultural intelligence computer system receives one or more digital precipitation records comprising a plurality of digital data values representing precipitation amount at a plurality of locations. The system additionally receives one or more digital forecast records comprising a plurality of digital data values representing precipitation forecasts, each of which comprising predictions of precipitation at a plurality of lead times. The system identifies a plurality of forecast values for a plurality of locations at a particular time, each of the plurality of forecast values corresponding to a different lead time. The system uses the plurality of forecast values to generate a probability of precipitation at each of the plurality of locations.

Abstract: A communications device inputs channel state information to an artificial neural network. The communications device predicts weather conditions with the artificial neural network based on the channel state information. The communications device further adjusts communications based on the predicted weather conditions.

Abstract: Train a machine learning model, using an image-based knowledge graph of tropical cyclone data, for implementing a surface field modeling architecture that produces images of at least surface wind fields and surface rainfall fields from images of at least tropical cyclone tracks and pressure intensities. Generate model images of a modeled surface wind field and a modeled surface rainfall field by providing images of at least a user-generated tropical cyclone track and pressure intensity to the trained machine learning model.

Abstract: A method, apparatus, system, and computer program product for visualizing aircraft configurations. A computer system determines a set of weight differences between weights for spatial zones in an aircraft and corresponding spatial zones in a comparison aircraft. The computer system displays a visual representation of the aircraft in a graphical user interface on a display system. The computer system displays the spatial zones in the visual representation of the aircraft in association with a set of graphical indicators identifying the set of weight differences between the spatial zones and the corresponding spatial zones in the graphical user interface on the display system. According to other illustrative embodiments, a computer system and a computer program product for visualizing aircraft configurations are provided.

Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.

Abstract: Disclosed is a method for processing an irradiation forecast. The method includes: acquiring irradiation forecast data corresponding to a target time period; calling a stacked generalization model including a first-layer generalizer and a second-layer generalizer; determining, using the first-layer generalizer, intermediate forecast data based on the irradiation forecast data corresponding to the target time period; and determining, using the second-layer generalizer, an output forecast value corresponding to the target time period based on the intermediate forecast data. In a technical solution according to an embodiment of the present disclosure, a method for processing an irradiation forecast is achieved.

Abstract: Systems and methods are provided for impervious surface mapping of a target geographic area. The impervious surface mapping utilizes four-band imagery data and light detection and ranging (LIDAR) data collected from the target geographic area. The identified impervious surfaces can be attributed to parcels within the target geographic area for purposes of generating bills for storm water runoff to parcel owners.

Abstract: Methods and systems for generating a multi-model ensemble of global climate simulation data from a plurality of pre-existing global climate simulation model (GCM) datasets, are disclosed. The methods and systems perform steps of computing a GCM dataset validation measure based on at least one sample statistic for at least one climate variable from the pre-existing GCM dataset; selecting a validated subset of the plurality of pre-existing GCM datasets; selecting a subset of GCM datasets; generating one or more candidate ensembles of GCM datasets; computing an ensemble forecast skill score for each candidate ensemble of GCM datasets; generating the multi-model ensemble of GCM datasets by selecting a candidate ensemble of GCM datasets with a best ensemble forecast skill score; and training the NN-based climate forecasting model using the multi-model ensemble of GCM datasets.

Abstract: A terrain referenced navigation system for a vehicle is disclosed and includes an inertial measurement unit and one or more generic terrain sensors configured to collect terrain-dependent data. The terrain referenced navigation system includes one or more processors in electronic communication with the generic terrain sensors and the inertial measurement unit, and a memory coupled to the processors. The memory stores data into one or more databases and program code that, when executed by the processors, causes the terrain referenced navigation system to determine a predicted terrain value based on a terrain value, where the terrain value is retrieved from one or more sensor specific terrain databases. The pre-Kalman filter processing values are sent to a Kalman filter. The Kalman filter determines navigation corrections and sensor corrections based on the pre-Kalman filter processing values.

Abstract: The present invention belongs to the field of nowcasting early-warning technology, and discloses a thunderstorm gale early-warning method, system, equipment and terminal. The thunderstorm gale early-warning method comprises: preprocessing single radar data to identify potential thunderstorm gale areas; and in real-time service, calling the thunderstorm gale parameter model in the potential thunderstorm gale areas identified by single radar every time to perform extrapolation for 1 hour, thereby forming a thunderstorm gale early-warning product within the next hour. The thunderstorm gale early-warning method provided by the present invention makes full use of the identification technology of dual polarization radar to identify the potential of thunderstorm gale, acquires falling areas of potential thunderstorm gale within the next hour by the extrapolation technology, and has better advance and accuracy compared with the existing thunderstorm gale early-warning method.

Abstract: An evaluation method for evaluating a precipitation-induced landslide disaster loss under climate change is provided. The evaluation method belongs to the technical field of geological disaster prevention and treatment. The evaluation method uses a physical process based model, in considering of spatial heterogeneity of land-surface features of grids in the area, to obtain precipitation thresholds corresponding to the respective grids in the area having the spatial heterogeneity. Historical data and climate model data are taken in combination to select suitable climate models, and the model then is used to simulate landslide prone zones and possible influence zones caused by landslides. An influence zones simulated by the evaluation method can better match disaster loss grid data, which can solve the problem that climate change scenarios and influence of landslide are difficult to be evaluated in landslide disaster evaluation.

Abstract: An apparatus, method, and non-transitory medium for betting on weather predictions are disclosed herein. A plurality of longitude and latitude coordinate pairs may be received from a remote device. The display device may render data representing a binary option based on whether a storm will make landfall within the certain radius. A request to purchase the binary option may be received. It may be determined whether the landfall location corresponds to a zip code associated with the given longitude latitude pair in the memory.

Abstract: The present invention discloses an intelligent soft measurement method for wind speed in front of a wind turbine. The method includes: first using laser radar data as a data sample, judging delay orders between input and output by using an AIC or BIC criterion, defining a dynamic difference regression vector according to the delay orders, dividing hyperplanes according to a clustering result by using a machine learning algorithm, and performing dynamic differential input/output nonlinear mapping modeling in a global scope and sub-scopes by using an artificial intelligence dynamic regression algorithm, respectively. Empirical mode decomposition and power spectral density analysis are performed on the wind speed in front of a laser radar measuring machine and the wind speed in front of a soft measurement machine, thereby further verifying the estimation performance of intelligent soft measurement for the wind speed in front of a wind turbine.

Abstract: A method and system is presented for short to long-term flood forecasting. At the core of the method is a neural network-based flood forecasting model. The method and system performs the steps to implement and use the neural network-based flood forecasting model comprising obtaining historical data from the region, including but not limited to climate and water level data; sampling and structuring the historical data in conjunction with data queried from a GIS (geographic information system) into a dataset; dividing the dataset into pre-processed training and validation partitions; configuring the neural network and training hyperparameters; training the neural network-based flood forecasting model on the pre-processed training partition; performing validation on the neural network-based flood forecasting model with the pre-processed validation partition. Embodiments of the invention are capable of performing flood forecasting over a region in short to long-term time intervals.