2073 results about "Distribution model" patented technology

The present disclosure provides methods for determining the ploidy status of a chromosome in a gestating fetus from genotypic data measured from a mixed sample of DNA comprising DNA from both the mother of the fetus and from the fetus, and optionally from genotypic data from the mother and father. The ploidy state is determined by using a joint distribution model to create a plurality of expected allele distributions for different possible fetal ploidy states given the parental genotypic data, and comparing the expected allelic distributions to the pattern of measured allelic distributions measured in the mixed sample, and choosing the ploidy state whose expected allelic distribution pattern most closely matches the observed allelic distribution pattern. The mixed sample of DNA may be preferentially enriched at a plurality of polymorphic loci in a way that minimizes the allelic bias, for example using massively multiplexed targeted PCR.

A method and apparatus (system) for providing forward-link channel-frequency allocation for multiple-satellite cellular communications networks is disclosed. The system has a centralized ground-operations control center that provides bi-weekly minute-by-minute allocation plans for geographically-defined service areas. This enables each service area to set its diversity policy in accordance with the requirements of the government regulators and customer preferences within the service area. The system has a user model having a frequency re-use pattern, a channel allocation model for modelling the power allocated to each channel, and a gateway channel model for allocating channels in accordance with the user model and the channel allocation model. The allocation is made for each satellite of the plurality of satellites. The traffic allocation induces an operating frequency for each of the one or more links in each satellite of the plurality of satellites. The satellite communication system computed frequency allocation is optimized to minimize total radiation from all forward links for one or more of the plurality of satellites.

Disclosed herein are systems, methods, and devices for classifying ophthalmic images according to disease type, state, and stage. The disclosed invention details systems, methods, and devices to perform the aforementioned classification based on weighted-linkage of an ensemble of machine learning models. In some parts, each model is trained on a training data set and tested on a test dataset. In other parts, the models are ranked based on classification performance, and model weights are assigned based on model rank. To classify an ophthalmic image, that image is presented to each model of the ensemble for classification, yielding a probabilistic classification score—of each model. Using the model weights, a weighted-average of the individual model-generated probabilistic scores is computed and used for the classification.

The invention discloses a multiple obstacle-avoidance control method of an unmanned plane used for electric wire inspection. The multiple obstacle-avoidance control method of the unmanned plane used for the electric wire inspection comprises an unmanned plane subsystem and a ground station subsystem. The unmanned plane subsystem comprises an embedded flight control device, a position detection module, an information processing module and an airborne terminal of a wireless data chain. The position detection module comprises a global navigation satellite system (GNSS) receiver, an electromagnetic field sensor and ultrasonic ranging sensors, wherein the ultrasonic ranging sensors are symmetrically arranged on the periphery of a machine body of the unmanned plane. The ground station subsystem comprises a ground terminal of the wireless data chain and an embedded supervisory control computer. The embedded supervisory control computer is loaded with a data base, wherein the data base contains an electric transmission line electromagnetic field distribution model and an electric transmission line space three-dimensional model. According to the multiple obstacle-avoidance control method of the unmanned plane used for the electric wire inspection, a security constraint area for the operation of the unmanned plane is built, the information processing module is adopted for integration of unmanned plane position information provided by an information detection module, relative distance between the unmanned plane and an electric transmission line is detected, and multiple obstacle-avoidance of the unmanned plane used for the electric wire inspection is achieved.

The invention discloses a track predication method based on a Gauss mixture time series model (GMTSM for short) to carry out model regression and analysis of road vehicle flow on a large quantity of vehicle historical tracks to realize vehicle track predication. The method mainly comprises the following steps: (1) carrying out unsupervised learning cluster on vehicle historical tracks through a k-means algorithm; (2) constructing a historical track probability distribution model through a Gauss mixture time series model; and (3) predicating tracks of mobile objects through a regressive processof the mixture model. An experiment result shows that the Gauss mixture time series model automatically adjusts the weight of sub-models and selects a predication track with the largest probability in a condition that road vehicle flows change suddenly.

Methods, systems, and computer-readable medium are provided for constructing multi-dimensional data models for distribution networks. Geometric features are extricated from a 2D representation of a distribution network comprising a plurality of objects having a relationship to each other within a network. Distribution network elements are generated from the geometric elements according to a network distribution model. The distribution network elements comprise objects and components of the network and include semantic information on associated attributes and relationships thereof. The distribution network element(s) can be validated using rules to detect errors in the generation of the distribution network element(s). The distribution networks element(s) can be refined and a multi-dimensional digital model constructed from the distribution network elements according to the distribution network model.

A method for producing a substantially calibrated numerical model, which can be used for calculating a stress on any point in a formation, accounts for a formation's geologic history using at least one virtual formation condition to effectively “create” the present-day, virgin stress distribution that correlates, within acceptable deviation limits, to actual field stress measurement data obtained for the formation. A virtual formation condition may describe an elastic rock property (e.g., Poisson ratio, Young's modulus), a plastic rock property (e.g., friction angle, cohesion) and/or a geologic process (e.g., tectonics, erosion) considered pertinent to developing a stratigraphic model suitable for performing the desired stress analysis of the formation.

The invention provides a full-sew-length three-dimensional crushing data simulation method and device for oil and gas reservoir development. The method comprises obtaining pre-stack seismic data of an oil and gas reservoir development object region, obtaining the pre-stack seismic data to conduct elastic parameter inversion and obtaining an elastic parameter data body of the oil and gas reservoir development object region, constructing a rock mechanic parametric model based on three-dimensional grid nodes according to the elastic parameter data body, calculating stress information on the three-dimensional grid nodes, generating three-dimensional stress field distribution model; and conducting full-sew-length three-dimensional numerical simulation in a crushing process according to the rock mechanic parametric model and the three-dimensional stress field distribution model. The full-sew-length three-dimensional crushing data simulation method and device can improve accuracy and efficiency of crushing data.

The present invention provides a fault prediction and condition-based repair method of an urban rail train bogie. An optimum service life distribution model of a framework, a spring device, a connecting device, a wheel set and axle box, a driving mechanism, and a basic brake device of a bogie is determined by adopting a method based on survival analysis; a reliability characteristic function of each subsystem is obtained; then, a failure rate of each subsystem of the bogie is calculated by adopting a neural network model optimized by an evolutionary algorithm; and finally, proportional risk modelling is conducted by taking the failure rate and safe operation days of each subsystem of the bogie as concomitant variables; and on the basis of cost optimization, thresholds and control limits for condition-based repair of a bogie system are obtained.

A battery model unit includes an electrode reaction model unit based on the Butler_Volmer equation, an electrolyte lithium concentration distribution model unit analyzing a lithium ion concentration distribution in an electrolyte solution by a diffusion equation, an active material lithium concentration distribution model unit analyzing an ion concentration distribution in a solid state of an active material by a diffusion equation, a current/potential distribution model unit for obtaining a potential distribution according to the charge conservation law, a thermal diffusion model unit and a boundary condition setting unit. The boundary condition setting unit (66) sets a boundary condition at an electrode interface such that a reacting weight at the electrode interface is not determined by a difference in material concentration between positions but a deviation from an electrochemically balanced state causes a change with time in lithium concentration at the interface and thus a (time-based) drive power for material transportation. Thereby, an appropriate charge/discharge control can be performed based on the battery model having the appropriately set battery condition.

A method for combining multiple probability of click models in an online advertising system into a combined predictive model, the method commencing by receiving a feature set slice (e.g. corresponding to demographics or taxonomies or clusters), and using the sliced data for training multiple slice-wise predictive models. The trained slice-wise predictive models are combined by overlaying a weighted distribution model over the trained slice-wise predictive models. The combined predictive model then is used in predicting the probability of a click given a query-advertisement pair in online advertising. The method can flexibly receive slice specifications, and can overlay any one or more of a variety of distribution models, such as a linear combination or a log-linear combination. Using an appropriate weighted distribution model, the combined predictive model reliably yields predictive estimates of occurrence of click events that are at least as good as the best predictive model in the slice-wise predictive model set.

The invention provides a fissure-cave type carbonate-reservoir reservoir body modeling method, and belongs to the field of carbonate reservoir exploitation geology. The method comprises the steps of (1) distinguishing karst cave reservoir body development segment in a single well; (2) building karst zone models along the vertical direction, building ancient landform unit distribution models in a plane; (3) respectively imitating three-dimensional distribution of the karst cave reservoir body in different karst zones and different ancient landform units, obtaining a three-dimensional distribution model of the karst cave reservoir body of a modeling target stratum; (4) counting development occurrence of a fissure reservoir body and single-well fissure development density; and (5) under control of a fault, building a three-dimensional discrete distribution model of the fissure reservoir body. According to the fissure-cave type carbonate-reservoir reservoir body modeling method, accuracy of the class of reservoir modeling is improved, a true condition of the reservoir is approached in a more objective mode, and important practical significance is provided for exploitation of the reservoir.

A system and method for trading financial instruments from a master account having a plurality of sub-accounts. A user defines an account group, which includes a plurality of sub-accounts, and the user selects an allocation model for the account group from a group of allocation models. After executing an order of financial instruments for the account group, the order is allocated to the sub-accounts using the allocation model. Prior to executing the order, a financial capability of the account group to execute the order using a primary allocation model is evaluated, and a secondary allocation model is used if the order cannot be allocated using the primary allocation model. The financial capability of the account group may be evaluated in real-time, and a partially executed order may also be allocated to the sub-accounts in real-time. Upon the execution of the order being completed, the order is reallocated to the sub-accounts using the selected allocation model.

The invention discloses a method for constructing a full-space three-dimensional digital earth model. The method includes that an ellipsoid earth space mathematical model is constructed based on a center of gravity control system (CGCS) 2000 China geodetic coordinate system; an earth surface dissection network is generated based on a fictitious graticule; an earth surface digital elevation model is generated in an insertion mode; a geometric structure module of earth space inner and outer ring layers is fitted by interpolations; a three-dimensional body element mesh of the earth space inner and outer ring layers is generated based in geological cells; an attribute element three-dimensional distribution model of the earth space inner and outer ring layers is fitted by the interpolations; a geographical coordinate is converted into a geocentric space three-dimensional rectangular coordinate; an earth space model multi-scale expression mechanism based on level of detail (LOD) is constructed; three-dimensional visualization is performed; earth space positions are checked; and three-dimensional analysis is performed. According to the method, the automaticity and the adaptability are high, and an earth space solid model containing the inner and outer ring layers can be rapidly and automatically reconstructed in three-dimensional space to be displayed on a computer display screen in a three-dimensional visualization mode to support space analysis of various professionals.

The invention discloses a method for accurately estimating wind power prediction error intervals. The method comprises the following steps: firstly, obtaining historical wind power data of a wind power plant; secondly, calculating wind power predication errors of all prediction points of the wind power plant, and establishing a wind power predication error distribution model; thirdly, establishing an error probability density function according to the distribution of the predication errors; fourthly, obtaining a confidence interval, meeting a certain confidence level, of the predication errors according to a given wind power predication value; and fifthly, calculating the shortest confidence interval through a Lagrange multiplier algorithm. On the basis of point predication, a probability density function of wind power prediction errors is obtained through interval prediction, and the confidence interval under a certain confidence level is calculated by a probability theory. In this way, the reliability of the interval to contain a wind power point predication value is determined, and the precision of wind power interval prediction is effectively improved.

The invention discloses a surface-curvature-based automatic path generation method for a spraying robot. The method includes the following steps that firstly, the Gaussian curvatures of all the positions of the curved surface of a workpiece to be sprayed are measured and calculated; secondly, segmentation treatment is conducted on the curved surface of the workpiece to be sprayed through a Gaussian-curvature-based improved watershed algorithm and a projection approximate segmentation method, and multiple sub-curved-surfaces with the gentle surface curvatures and the simple topology are obtained; thirdly, a seed curve is selected on one sub-curved-surface through a geodesic line method, the current path speed and the adjacent stroke interval are optimized according to a deposition distribution model of paint sprayed by a spray gun to the surface of the workpiece to the sprayed, and a next polarization path is generated; fourthly, next polarization paths are obtained by using the third step for the other sub-curved-surfaces, and the optimized spraying paths completely covering the surface of the workpiece to be sprayed are generated. By means of the method, based on the surface curvatures of workpieces to be sprayed, the spraying quality and the spraying efficiency of the complex workpieces can be improved, and the paint cost is saved.

The invention belongs to the technical field of radar image processing, and particularly relates to a ship target detecting and discriminating method in an SAR image with a complicated background. The method comprises the following main steps of (1), fine sea-and-land dividing; (2), performing high-efficiency detection on the ship target, wherein the step comprises large-scale CFAR and small-scale iteration CFAR, wherein a synthetic aperture radar image clutter statistics distribution model based on generalized Gamma distribution is used; and (3), performing nearshore target false alarm discrimination, wherein the step comprises a false alarm discriminating algorithm based on a maximal likelihood and a false alarm discriminating algorithm based on polarization information. The method can efficiently and accurately detect the ship target in complicated backgrounds such as nearshore and harbor, and furthermore can utilize the false alarm discriminating algorithm based on maximal likelihood and the polarization information for discriminating a false alarm target, thereby improving ship target detecting accuracy. The ship detecting algorithm provided by the invention is suitable for a random SAR image background and furthermore has advantages of high robustness, high real-time performance and good popularization prospect.

A computerized system for and method of creating applications that access information from multiple data sources into a common, role-based distribution model are described. The computerized system includes a server having one or more dynamic object libraries, one or more template libraries, and a dynamically allocated area in the computer memory where data is stored, referenced, and manipulated. The system also includes one or more adapters, each allowing the server to access one of the data sources.

The invention provides a light distribution optimization method for two-dimensional reconstruction of a combustion flow field by combining a tunable semiconductor laser absorption spectrum technology and a computed tomography technology. The method comprises the following steps: a light matrix calculation step, a combustion flow field reconstruction step and a light distribution optimization step and particularly comprises the following steps: step 1, discretizing a region to be tested; pre-setting a light space distribution manner and calculating the length of light penetrating through the discretized region to obtain a light distribution matrix; step 2, selecting a suitable absorption spectrum line and calculating a light projection result of an initial gas distribution model; reconstructing temperatures and concentrations of the tested flow field by using an algebra iterative algorithm and calculating a reconstruction error and a standard deviation; and step 3, wholly searching by using a self-adaption simulated annealing method to obtain an optimal light distribution range and partially searching by using a sequential quadratic programming method to obtain optimal light distribution.

The invention provides a coupling modeling method for hydropower station generated output scheme making and optimal load distribution. The method includes the steps that a hydropower station generated output scheme model is established with the maximum peak-load regulating capacity benefit as the target, and a in-plant set load optimal distribution model is established with the minimum water consumption as the target; the hydropower station generated output scheme model is solved, so that a hydropower station initial generated output scheme is obtained; the hydropower station initial generated output scheme serves as input of the in-plant set load optimal distribution model, simulation calculation is performed on the in-plant set load optimal distribution model, algorithm loop iteration and model trace netting correction are performed on the hydropower station initial generated output scheme through an integrated self-adapting adjustment mode, and coupled output is a final hydropower station generated output scheme. Integrated seamless coupling operation of hydropower station generated output scheme making and in-plant set load optimal distribution is achieved, wherein the hydropower station generated output scheme has the self-adapting adjustment characteristic, and the fine hydropower station generated output scheme is obtained under the condition that in-plant set load optimal distribution is met.

The invention relates to an SVG technology-based distribution network modeling system. The single-line diagram of the distribution network modeling system is generated according to the following steps: SVG entities are respectively constructed with different patterns according to different types of distribution network structures contained in a distribution model; according to the branch information contained in a distribution network wiring diagram, the basic branch entities of an SVG topological diagram are constructed; node entities and branch entities are respectively constructed with different colors and solid and dotted patterns according to operating states; the entity shape of each equipment in a distribution network is customized in advance; the data of a power grid model are accessed and read; and the single-line diagram of the distribution network is formed by merging, and a closed loop model is automatically generated. The SVG-based pattern vector display technology disclosed by the invention can efficiently and visually display distribution network wiring diagrams in real time. The SVG technology-based distribution network modeling system can effectively increase working efficiency and provide a variety of appropriate topological diagram display modes for users, and is used in various power grid analysis works.

The invention relates to an overlay network layered multicast optimal resource allocation method for a scalable video stream, and provides a new measurement standard for the multicast performance, namely layer extensity which is used for measuring end-to-end time delay of video layers during data distribution aiming at layered multicast communication of the scalable video stream in the overlay network. In order to realize the overall minimization of the layer extensity, the method carries out the combined optimization on the network code of relay nodes, the receiving end driven flow control, and multi-path route strategy, and adopts a linear programming method to establish a layered multicast resource optimum allocation model for the overlay network. On one hand, the method adaptively matches the interlayer dependency of the scalable video code; on the other hand, the method allows a receiving node to decide and regulate the required video quality of own accord. In addition, the invention also provides a distributed heuristic algorithm which has low complexity, approaches the globally optimal solution and is applied to the construction of a scalable video flow distribution network.

A topic analyzing method is provided in which the number of main topics in text data which is added in time series and generation and disappearance of topics are identified in real time as needed, and features of main topics are extracted and thereby one can know a change in the content of a topic with a minimum amount of memory and processing time. There is provided a system that detects topics while sequentially reading text data in a situation where the text data is added in time series, including learning means for representing a topic generation model by a mixture distribution model and learning the topic generation model online while more-heavily discounting the older data on the basis of a timestamp of the data; and model selecting means for selecting an optimal topic generation model from among a plurality of candidate topic generation models on the basis of information criteria of the topic generation models, wherein the topics are detected as mixture components of the optimal generation model.