270 results about "Cloud cover" patented technology

A method is performed by a computer configured to facilitate brokering of cloud services. The method includes a plurality of operations. An operation of receiving a request for instantiating an instance of a cloud service budget for a customer is performed. An operation of receiving budget configuration information is performed after receiving the request for instantiating the instance of the budget. The budget configuration information specifies a cloud service budget threshold. An operation of determining a budgetary impact of the cloud service order is performed. An operation of receiving information defining a price of a cloud service order subject to the cloud service budget is performed. In response to the budgetary impact indicating that a price of the cloud order will cause a cloud service billing amount for the customer to exceed the budget threshold, an operation of implementing at least one budgetary action associated with the budgetary impact determination.

Administration of virtual machine affinity among data centers in a cloud computing environment, where the cloud computing environment includes a plurality of virtual machines (‘VMs’), the VMs composed of modules of automated computing machinery installed upon cloud computers disposed within data centers, the cloud computing environment further including a cloud operating system and data center administration servers operably coupled to the VMs, including installing, by the cloud operating system on at least one VM, an indicator that at least two of the VMs have an affinity requirement to be installed upon cloud computers in separate data centers; communicating, by at least one of the VMs, the affinity requirement to at least one data center administration server; and moving by the at least one data center administration server the VMs having the affinity requirement to cloud computers in separate data centers in the cloud computing environment.

Cloud cover assessment system and method provides for automatically determining whether a target digital image acquired from remote sensing platforms is substantially cloud-free. The target image is acquired and compared to a corresponding known cloud-free image from a cloud-free database, using an optimized feature matching process. A feature matching statistic is computed between pixels in the target image and pixels in the cloud-free image and each value is converted to a feature matching probability. Features in the target image that match features in the cloud-free image exhibit a high value of feature matching probability, and are considered unlikely to be obscured by clouds, and may be designated for inclusion in the cloud-free database.

Deploying a virtual machine in a cloud computing environment, the cloud computing environment including one or more virtual machines (‘VMs’), the VMs being modules of automated computing machinery installed upon cloud computers disposed within data centers, the cloud computing environment also including a cloud operating system and data center administration servers operably coupled to the VMs, including deploying, by the cloud operating system in a local data center, a VM, including flagging the VM for disaster recovery; storing, by the cloud operating system in computer memory in a remote data center, a copy of the flagged VM; and configuring, by the cloud operating system, the remote data center to replace data processing operations of the flagged VM in the local data center with data processing operations of the copy in the remote data center when the flagged VM in the local data center is lost through disaster.

A method for forecasting reduction in sunlight intensity due to cloud cover at a photovoltaic power plant is described. The method comprises determining characteristics of one or more clouds from sensors surrounding the photovoltaic power plant. The cloud characteristics are used to create a 3D map of the clouds. The 3D map in combination with information on the angle of the sun is used to create a 3D projection on the surface of the earth, resulting in a 2D surface irradiance map. The 2D surface irradiance map may be taken in successive projections or used in combination with wind speed data to forecast fluctuation in irradiance at the photovoltaic power plant. The forecasted reductions in power may be used to enact measures at the plant such as reducing the power output of inverters to prevent sudden fluctuations in the power output of the photovoltaic plant feeding the utility.

A pod (34) containing sensors and / or targeting systems such as laser designators or range finders are hung on a cable (30) below an aircraft (12). The line (30) can be reeled in or out similar to towed decoys. This allows the aircraft (12) to operate above or in the cloud cover while the sensors / targeting equipment (34) are operating below the cloud cover to find the enemy forces.

The invention provides a cloud intelligent cooking method, a cloud intelligent cooking device and a cloud server. The cloud intelligent cooking method includes the steps of receiving a cooking instruction and sending the cooking instruction to the cloud sever; receiving a cooking method, sent by the cloud server, of food materials to be cooked; informing a user of the cooking method; obtaining information of the food materials to be cooked after the food materials to be cooked are detected; sending the information of the food materials to be cooked to the cloud server; receiving a heating control instruction sent by the cloud server; cooking the food materials to be cooked according to the heating control instruction and the cooking method selected by the user. After the cooking instruction is received, the cloud intelligent cooking device can interacts with the cloud server automatically according to the cooking instruction, the food materials placed in the cloud intelligent cooking device are cooked, operation is easy and convenient, and the user experience degree is high.

Autonomic scaling of virtual machines in a cloud computing environment, the cloud computing environment including virtual machines (‘VMs’), the VMs installed upon cloud computers disposed within a data center, also including a cloud operating system and a data center administration server operably coupled to the VMs, including deploying, by the cloud operating system, an instance of a VM, flagging the instance of a VM for autonomic scaling; monitoring, by the cloud operating system, one or more operating characteristics of the instance of the VM; deploying, by the cloud operating system, an additional instance of the VM if a value of an operating characteristic exceeds a first predetermined threshold value, including executing a portion of the data processing workload on the additional instance of the VM; and terminating operation of the additional instance of the VM if a value of an operating characteristic declines below a second predetermined threshold value.

A modular reconnaissance capsule or reconnaissance pod is provided that is suitable for deployment by means of an artillery launching platform, such as a conventional 40 mm grenade launcher or 155 mm cannon wherein a parachute is deployed at a pre-calculated observation altitude, the parachute being designed to yield a sufficiently slow rate of descent to permit live video capture and transmission of images as forward observation information. Alternatively, pods according to the invention may also be air dropped from an aircraft, either piloted or pilotless, thus allowing the aircraft to operate at a safe distance and yet provide close reconnaissance even under a cloud cover. Accurate information about targeting dynamics is made available to the user through commercially available products. The invention complements other reconnaissance methods and provides easy-to-use real-time visual information for a desired area of interest.

A constellation of satellites may include a plurality of satellites in each of two or more different orbits. Satellites in a given orbit may operate in pairs, flying in tandem, one satellite leading, the other trailing closely behind, to be positioned to image the same target(s) of interest with substantially the same orientation (geographical coincident) at substantially the same time (temporally coincident). The first satellite may acquire SAR data, determine a location of a target of interest, assess cloud cover, and based on an extent of cloud cover, can acquire additional SAR data or cause the second satellite to capture optical imaging data (e.g., cross-cueing). Selection of orbits can provide a relatively high revisit rate may be obtained, allowing frequent opportunities to image given locations on a planet (e.g., Earth). One or more ground stations communicate with the constellation of satellites, and inter-satellite communications may be employed.

The invention provides a photovoltaic super-short-term generated power forecasting method based on cloud cover simulation. The method comprises the following steps that photovoltaic super-short-term generated power of a photovoltaic power station in the next four hours is forecasted according to a weather-type cloudless sky forecasting method; cloud cover information of the photovoltaic power station in the next four hours is simulated, forecasted data correction is carried out for horizontal plane irradiance attenuation caused by cloud, and forecasting of the photovoltaic super-short-term generated power of the photovoltaic power station is finished. The forecasting method has the greater advantages on the aspect of capturing the cloud cover shading information than a cloudless sky working condition photovoltaic power super-short-term forecasting model, and the effective time duration is greatly prolonged compared with that forecasted by a photovoltaic power super-short-term forecasting model based on a foundation cloud picture.

The invention discloses a data fusion-based atmosphere particulate matter remote sensing monitoring method, and relates to the technical field of air quality monitoring. According to the method, particulate matter concentration data of complete coverage space are obtained by fusing satellite remote sensing inversion data and ground surface monitoring data and performing interpolation operation on a fused result, so that the problem of particulate matter concentration data deficiency caused by weather, a satellite orbit interval, a cloud cover problem and the limitation of a dim target inversion algorithm is effectively solved, and the accuracy rate of air quality monitoring is greatly improved.

A pod (34) containing sensors and / or targeting systems such as laser designators or range finders are hung on a cable (30) below an aircraft (12). The line (30) can be reeled in or out similar to towed decoys. This allows the aircraft (12) to operate above or in the cloud cover while the sensors / targeting equipment (34) are operating below the cloud cover to find the enemy forces.

Disclosed is a system and a method for detecting the presence of one or more objects in a turbid medium, the method including: illuminating at least a portion of the turbid medium with incident light having at least one wavelength which interacts with the one or more objects contained in the turbid medium differently than the incident light interacts with the turbid medium; measuring light that emerges from the turbid medium; and detecting and locating the one or more objects using Independent Component Analysis (ICA) of the emergent light from the turbid medium. The present invention is useful for medical applications, such as for finding and locating, a tumor(s) in body organs, or excised tissues. Moreover, the present invention can be used to locate objects in obscuring medium, such as, mines in shallow coastal water, a plane in fog, military targets under fog, smoke or cloud cover.

A foundation cloud measuring method combining infrared and lasers comprises the following steps that (1) atmosphere downward infrared radiation data are obtained through an uncooled infrared focal planar array sensor, zenith backward extinction coefficient profile data are obtained through a laser sensor, and the obtaining time of the atmosphere downward infrared radiation data is synchronous with the obtaining time of the zenith backward extinction coefficient profile data; (2) water vapor and aerosol radiation under cloud are estimated by combining the data, clear sky threshold values calculated through a radiation transmission pattern are used for conducting initial cloud detection, it is assumed that the cloud is a black body, and the cloud base height is obtained through inversion; (3) sequence analysis is conducted on infrared radiation images with high time resolution, the clear sky threshold values are combined to conduct further cloud detection, and the cloud cover is calculated; (4) proportionality coefficients between the cloud base height obtained through the infrared radiation inversion and the cloud base height obtained through laser measurement are fitted; (5) the cloud base height of a whole view field is corrected, and the typical cloud base heights of every ten minutes are obtained through calculation.

The invention discloses a system and a method for the meteorological information-assisted satellite imaging task planning. The method comprises the steps of 1, collecting observation requirements; 2,performing imaging task treatment on an observation target; (wherein the target region divided into small regions of 10 * 10 degrees by dividing longitude and latitude grids in the global range according to a cone projection mode during the task planning process; and the divided small regions are subjected to matching and judging during the cloud cover judgment) 3, performing cloud cover inspection for each imaging scheme (based on a statistical threshold value of 75%), removing pre-arranged plans which do not meet the cloud cover constraint condition, screening out a plan set which most meetsan optimal strategy, arranging plans according to the imaging time and the imaging angle, and generating a final planning scheme; 4, respectively transmitting the information of an imaging scheme and a receiving scheme to a satellite and a ground receiving station. According to the scheme, the cloud cover in each target imaging region can be evaluated before satellite imaging, so that the imaging quality can be obviously improved.

The present invention discloses a satellite remote sensing image cloud amount calculation method on the basis of random forest. The satellite remote sensing image cloud amount calculation method on the basis of random forest comprises six steps: sample acquisition, feature extraction, image classifier training, segmentation of image to be measured, image classification, cloud amount calculation and the like. Through adoption of the method provided by the invention, multiple detections may be performed after training just once, an image classifier is obtained through a large number of image trainings, and the image classifier may be used again when cloud detection is performed. The random forest algorithm is low in time complexity at the prediction classification stage, and the cloud zone detection may be rapidly carried out. Through the test, the method provided by the invention is applicable to panchromatic images (ten-dimensional characteristic vector) and also applicable to n-channel multispectral images (10n-dimensional characteristic vector), and has been applied to an actual quality control system of satellite image products, so that the cloud detection of remote sensing images of multiple domestic satellites such as the resource satellite-3, mapping satellite-1, GF-1 and the like are performed, wherein the accuracies reach, respectively, 91%, 88% and 92.4%.

The invention discloses a cloud and aerial total cloud amount detection method and system. The system comprises an image obtaining device, a sky type confirming module, a cloud detection module and an aerial total cloud amount computing module, wherein the image obtaining device is used for obtaining an aerial cloud picture at a preset moment, the sky type confirming module is used for confirming the type of the sky at the preset moment, the cloud in the cloud picture is detected through the cloud detection module according to partition threshold values, and the aerial total cloud amount computing module is used for computing the aerial total cloud amount according to the ratio of the cloud in the aerial cloud picture to the whole aerial cloud picture. The cloud in the cloud picture is detected through the aerial cloud picture partition threshold values corresponding to the different sky types, the influences of different weather conditions on the detection result of the aerial cloud picture are taken into full consideration, and the accuracy of the cloud detection is made to be higher.

The present invention reveals one kind of air conditioner controller capable of realizing comfortable air conditioning state without need of inputting weather information and sunshine information. The air conditioner controller has one temperature change calculating unit to calculate the outdoor temperature change regularly, one operating unit to predict the standard outdoor air temperature change value, one cloud amount predicating and operating unit to calculate cloud amount corresponding to the outdoor air temperature change, one sunshine amount predicting and operating unit to calculate and predict sunshine amount, and one radiation temperature operating unit to calculate average radiation temperature. The comfort index PMV value is found out with the input variables including the average radiation temperature based on the comfort formula.

Cloud cover assessment system and method provides for automatically determining whether a target digital image acquired from remote sensing platforms is substantially cloud-free. The target image is acquired and compared to a corresponding known cloud-free image from a cloud-free database, using an optimized feature matching process. A feature matching statistic is computed between pixels in the target image and pixels in the cloud-free image and each value is converted to a feature matching probability. Features in the target image that match features in the cloud-free image exhibit a high value of feature matching probability, and are considered unlikely to be obscured by clouds, and may be designated for inclusion in the cloud-free database.

The invention discloses a meteorological-information-based photovoltaic power generation active power online evaluation method, which comprises the following steps of: 1, selecting a reference point, a reference direction and a sample photovoltaic panel, and setting a data acquisition moment t to be an initial moment 0; 2, acquiring the axial directions of the photovoltaic panel and photometric equipment; 3, acquiring the geographical position information and dip angle data of the photovoltaic panel and the photometric equipment; 4, acquiring solar irradiation sample data, prediction data and cloud cover monitoring data measured by the photometric equipment; 5, preprocessing the solar irradiation sample data and the prediction data; 6, preprocessing the cloud cover monitoring data; 7, computing the active power output of a photovoltaic component; and 8, obtaining a photovoltaic power generation active power characteristic curve. In the method, the data actually measured by the photometric equipment in the given time period of 1min is taken as a basis and the influence of a cloud cluster on a photovoltaic power station is comprehensively taken into account to obtain the photovoltaic power generation active power characteristic curve in the future 0 to 5min by approximately equal power processing and curve fitting, so active power characteristic analysis efficiency and accuracy are effectively improved, and the bases are provided for the formulation and regulation of complementary running policies and energy efficiency management policies of joint power generation systems utilizing a plurality of power supplies such as wind, sunlight and the like.

The invention relates to an infrared sky instrument comprising an infrared temperature measurement unit, a two-dimension scanning platform, a controller and a control and data collection processing microcomputer. The infrared temperature measurement unit is a rapidly-response non-contact infrared temperature measurement thermometer; the two-dimension scanning platform comprises an azimuth scanning mechanism and a pitch scanning mechanism; the controller comprises a stepping motor driver (Motor Driver) satisfying the use requirements of a stepping motor, a micro chip computer and a communication interface chip; the two-dimension scanning platform drives the rapidly-response infrared temperature measurement unit to carry out all-day sky stereoscan under the control of the controller and the data collection processing micro computer and stores the measured cloud base infrared radiation bright temperature values in the conditions of specified azimuth and elevation into the control and data collection processing micro computer. After the scanning is finished, the infrared radiation bright temperature values corresponding to different azimuths and elevations are spliced together to form an all-sky infrared radiation bright temperature distribution chart. The measurement can be carried out whenever in the day or at night as infrared radiation of clouds are measured. The infrared sky instrument can substitute the original cloud observation means, and can obtain all-weather refined cloud data of sky cloud form and cloud cover.

The invention relates to an AC / DC (Alternating Current / Direct Current) mixed micro-grid optimized operating method based on a main-slave game model. The method comprises the following steps: acquiring weather data of an area in which a micro-grid is located such as illumination intensity, temperature and cloud cover, counting historical data of a photovoltaic power generation amount in the micro-grid, and predicting power outputted by a photovoltaic cell in an AC / DC mixed micro-grid in a next day by adopting a prediction method based on a typical trend; acquiring transmission power data at two sides of a bidirectional converter and a tendency controller in the AC / DC mixed micro-grid, and establishing a mathematic model of various devices in the AC / DC mixed micro-grid; dividing a day into various dispatching time periods, establishing a main-slave game model of cooperation of a photovoltaic operator and a grid company at each dispatching time period, wherein the main-slave game model comprises a photovoltaic utilization rate model maximizing the benefit of the photovoltaic operator and an AC / DC mixed micro-grid loss model minimizing the loss of the representative grid company; and improving the global searching performance of an algorithm by adopting a two-order oscillation particle swarm algorithm of an asynchronous variation learning factor. The AC / DC mixed micro-grid optimized operating method is high in applicability and high in prediction precision.

Methods, a computer-readable medium, and a system are provided for determining whether a data point indicates a presence of a cloud using visible near-infrared data and short wavelength infrared data. A first comparison of a cirrus-band reflectance of the data point with a threshold cirrus-band reflectance value is made, classifying the data point as a cloud point if the cirrus-band reflectance of the data point exceeds the threshold cirrus-band reflectance value. When the comparing of the cirrus-band reflectance of the data point with the threshold cirrus-band reflectance value does not classify the data point as a cloud point, a further analysis is performed, including performing a second or more comparisons of additional cloud indicators derived from at least one of the visible, near-infrared, and short wavelength infrared data with related empirically-derived, landcover-dependent thresholds for classifying the data point as a cloud point or a non-cloud point.

The invention discloses an all-weather surface temperature generation method and device based on machine learning. The method comprises: extracting an MODIS data set subjected to remote sensing inversion through an MODIS tool MRT; combining static meteorological satellite data with DEM topographic data of the ALOS satellite, and estimating and obtaining surface incident solar radiation; performingspatial aggregation on data sets with the same spatial scale, and taking the data sets and the MODIS data set as a machine learning training data set; constructing a surface temperature relation model through a random forest model; estimating the real temperature of the earth surface with the cloud coverage pixels; and combining the real earth surface temperature of the cloud-covered pixel with the data set of the cloudless-covered pixel to generate the all-weather earth surface temperature. According to the method, the problems that current thermal infrared remote sensing is easily influenced by cloud and mist, and a large number of blank value-lacking areas exist in surface temperature products are solved, cloud condition surface temperature estimation is achieved, and an important basis is provided for all-weather surface temperature product generation.

The present invention is directed to a mobile light tower that utilizes multiple sources of energy to provide a highly energy efficient source of illumination. The lights of the light tower draw power from the energy stored in the batteries. During the day, solar energy can captured and stored in batteries. In times of cloud cover, or at night, wind energy can be captured and stored in the batteries. Additional alternative energy sources can also be incorporated. In the event that neither of these sources are sufficient, a fuel powered generator can be utilized to generate energy to be stored in the batteries.

Methods, a computer-readable medium, and a system are provided for determining whether a data point indicates a presence of a cloud using visible near-infrared data and short wavelength infrared data. A first comparison of a cirrus-band reflectance of the data point with a threshold cirrus-band reflectance value is made, classifying the data point as a cloud point if the cirrus-band reflectance of the data point exceeds the threshold cirrus-band reflectance value. When the comparing of the cirrus-band reflectance of the data point with the threshold cirrus-band reflectance value does not classify the data point as a cloud point, a further analysis is performed, including performing a second or more comparisons of additional cloud indicators derived from at least one of the visible, near-infrared, and short wavelength infrared data with related empirically-derived, landcover-dependent thresholds for classifying the data point as a cloud point or a non-cloud point.

The invention discloses a fragmented remote sensing image synthesis method and device for a cloudy and rainy region, and the method comprises the following steps: obtaining a multi-satellite and multi-phase initial image data set of the cloudy and rainy region; carrying out the radiation difference correction of a sensor and an external factor for the initial image data set, so as to obtain a first image data set consistent with the radiation features; obtaining a cloud layer and shadow distribution range of the first image data set, and obtaining a cloudless data fragment set of the cloudy and rainy region through mask processing; selecting a reference data subset from the cloudless data fragment set, repairing a loss region through employing other cloudless data fragment sets, and obtaining the complete cloudless synthetic image of the cloudy and rainy region. The method makes the most of conventional useless data (high cloud images) for synthesis, effectively improves the space-time coverage frequency of the remote sensing observation of the cloudy and rainy region, and provides powerful data support for the remote sensing application based the domestic satellite data especially the application with the high requirements for timeliness.

The invention discloses a photovoltaic power station output data repairing method based on weather information. The method comprises the following steps: repeated, missing and unreasonable abnormal data in data are obtained through screening, and according to the length of a continuous time sequence corresponding to the abnormal data, a continuous abnormal type and a local abnormal type are divided; the correlation between the selected weather information data items and the normal photovoltaic power station output data is checked item by item, and uncorrelated data items are removed; the known weather information, a cloud covering factor at the photovoltaic power station and the temperature are used for training a BP neural network model, and all parameters of the BP neural network model are obtained; as for the local abnormal data, an interpolation method is adopted to obtain repaired photovoltaic power station output data; as for the continuous abnormal type data, the weather information at the corresponding time is used to obtain the temperature and the cloud covering factor data; and the effectiveness of the repaired data is checked, and a repairing report is outputted. By using the open and free weather information, the photovoltaic power station output data are repaired.