38 results about "Weather patterns" patented technology

The selection of an optimal data center location for running a computational workload is based on multiple energy criteria. The location is chosen based on multivariate and predictive analysis of total direct and indirect energy costs, and other user-defined factors. Among the direct and indirect costs are power costs and cooling costs as well as structural and other details of a given data center. Among the other factors to be considered that can have an impact on present and future costs are weather patterns, data and forecasts, availability of energy providers, and energy attributes. A forecaster factors these direct and indirect costs along with extrinsic information such as historical trends and predictive sources into a forecast which is then input to a decision engine along with user defined criteria and with anticipated compute tasks and requirements to select a final location or locations for handling the workload.

A computer generates a three dimensional map of a pathway area using a plurality of overhead images. The computer determines a forecasted weather pattern to occur in the pathway area. The computer analyzes the three dimensional map and the forecasted weather pattern to predict one or more violations of the pathway. The computer generates a priority for the one or more predicted violations of the pathway. The computer generates a plan for pathway management of the pathway area.

A computer generates a three dimensional map of a pathway area using a plurality of overhead images. The computer determines a forecasted weather pattern to occur in the pathway area. The computer analyzes the three dimensional map and the forecasted weather pattern to predict one or more violations of the pathway. The computer generates a priority for the one or more predicted violations of the pathway. The computer generates a plan for pathway management of the pathway area.

A computer-implemented method of optimizing demand-response (DR) of a heating, ventilation, and air-conditioning (HVAC) system of a building, includes determining (30, 31, 32) a value of an objective function Fij of a HVAC system for each of a plurality of DR strategies j for each of a plurality of weather patterns i that is a weighted sum of an energy cost of the HVAC system and a thermal comfort loss of the HVAC system, assigning (33, 34, 35, 36) a likelihood score Li,j to each of a selected subset of near-optimal DR strategies j for each weather pattern i, and selecting (37, 38) those near-optimal DR strategies with large overall likelihood scores Lj to create an optimal strategy pool of DR strategies. An optimal strategy pool can be searched (39) in real-time for an optimal DR strategy for a given weather pattern.

In one embodiment, a system, is provided to take not just a person's time and location into consideration, but also has knowledge of and takes into account their availability, their preferences, their schedule, their purpose for being at their current location, and / or their next goal or stop. One embodiment is able to take into account a real-time view of supplier inventory and deduce and make available much better-adapted offerings and support for that person's travels and endeavors. In one embodiment, having an understanding of a rate of conversion and its relation to traffic and weather patterns allows service providers to make more accurate predictions about various items, including but not limited to, conversion rates, offer types, offer upgrades, traffic etc. In yet another aspect of the invention, the information collected from many travelers, and also information collected from airlines and weather observers, etc., can be used to forecast inventory requirements, such as obtaining and preparing fresh food and pulling from storage chilled or frozen food, as well as man power or staffing level requirements, to meet projected demands.

The invention provides an LED intelligent display system which comprises a data platform for obtaining movement data from a client side, storing the movement data and obtaining real-time weather data from the outside world, an environment monitoring subsystem for collecting real-time environment information, a lamp monitoring subsystem for collecting running information of an LED lamp and an LED display screen, and an intelligent main controller for obtaining the weather data from the data platform and generating a corresponding weather pattern in real time so as to display the weather pattern on the LED display screen in real time, obtaining the environment information from the environment monitoring subsystem so as to display the environment data on the LED display screen in real time, obtaining the movement data from the data platform so as to display user information corresponding to the movement data ranked in the front and the movement data on the LED display screen, obtaining the running information of the LED lamp and the LED display screen from the lamp monitoring subsystem and storing the running information, and controlling the running of the LED lamp and / or the LED display screen through a controller.

The invention discloses a bridge permanent deformation analysis method based on PS‑InSAR technology. According to the statistical laws of bridge live loads (temperature loads and random traffic loads) under different weather modes, artificial PS points are set on the key deformation points of the target bridge. , using the Monte Carlo method-finite element simulation technology to give the space-time matrix of random deformation values ​​of key deformation points of the target bridge under different weather modes. Then, according to the moment when the satellite shoots the SAR image, match the random deformation value space-time matrix under the corresponding weather mode, and obtain the random deformation difference caused by the live load change of the bridge during the main and slave SAR image interference process, so as to extract from the PS-InSAR-based technology This random deformation difference is eliminated from the deformation information of the bridge to obtain the permanent deformation of the bridge, which provides a strong data support for the health and safety of the bridge.

A system and method is provided for the control of a network of devices wherein each device of the networked devices provides for the operation of a sensor such as an accelerometer, processor and communication element within each device, and network and / or cloud based processing and storage, to process collected data to permit detection and predictive analysis of traffic patterns, weather patterns and other forces of nature. The system and method can analyze duration and magnitude of vibration signals, and considering maps and known locations of devices, tracks and highways and historical data regarding each, use machine learning techniques to accurately classify the motion and provide real-time and predictive analysis.

The invention discloses a method for intelligently identifying a floor by a carrier robot based on a weather sensing time series pattern, comprising: step 1: building a floor information database; step 2: clustering the floor information data to obtain a set of weather patterns for each floor ; Step 3: Obtain the training set used to build the atmospheric pressure floor prediction model based on the weather model; Step 4: Build the atmospheric pressure floor prediction model based on the weather model; Step 5: Use the floor number of the robot's current floor and weather observations to call The air pressure floor prediction model of the weather model; step 6: use the air pressure and air pressure floor prediction model collected by the robot in real time to predict the floor number of the robot; this method uses simple temperature, humidity, and air pressure sensors to collect data, establish an environmental database, and target The characteristics of air pressure changing with altitude, using data mining technology, realize automatic high-accuracy and high-stability recognition of elevator floors by robots under different environmental conditions.

The invention relates to a power load forecasting method based on historical annual weather rules, and belongs to the technical field of electric power systems. The method includes: S1. Determine the area range of the electricity load, and divide the sub-load units or sub-power supply areas according to the actual situation, and formulate the network topology structure diagram of the geographical location relationship; S2: according to the network topology structure; S3. Input the history of the current month 12-month monthly cumulative data of electricity load; S4. Determine the weighted sub-factor of the load nature; S5: Obtain the per-unit value of the current historical 12-month load forecast by month; S6: Use the multivariate nonlinear fitting method to optimize The current historical 12-month load change curve and fitting relationship; S7: Get the power load of the next three months, six months or 12 months including the current month; S8: Check and correct the power load change curve , modify the load forecast results for the next month. Gradually achieve the goal of being as close as possible to the actual power load in the future.