Abstract: A method for obtaining an emission probability includes obtaining a plurality of measurement reports (MRs) of a terminal in a target region and an engineering parameter of at least one base station in the target region, obtaining, based on parameter information in each of the plurality of MRs and the engineering parameter of the at least one base station, a feature vector corresponding to each of the plurality of MRs, processing, using a regression model, location information in each of the plurality of MRs and the feature vector corresponding to each of the plurality of MRs, to obtain a single-point positioning model, calculating, based on the single-point positioning model, the location information in each of the plurality of MRs, and the feature vector corresponding to each of the plurality of MRs, an emission probability of the feature vector corresponding to each of the plurality of MRs.

Abstract: The present disclosure relates to task solving methods. One example method includes obtaining importance of each first scheduling constraint in a plurality of first scheduling constraints in a first linear-programming task, where the importance indicates a degree of contribution of the first scheduling constraint to reducing a time for solving the first linear-programming task. The plurality of first scheduling constraints are sampled based on the importance to obtain a subset of the obtained plurality of first scheduling constraints, where the importance is used to determine sampling probability of the first scheduling constraints. A second linear-programming task is constructed based on the subset of the plurality of first scheduling constraints. The second linear-programming task is solved to obtain a first solving result. A first solving result is used as an initial value of the first linear-programming task, and an initialized first linear-programming task is solved.

Abstract: An industrial programming method and apparatus, a device, a storage medium, and a program product are provided. In a programming scheme generation method, a programming device obtains a first group of constraints for a plurality of parameters in an industrial programming job. Further, the programming device constructs, based on the first group of constraints, a cut constraint associated with at least one integer parameter in the plurality of parameters, and constructs a second group of constraints based on the cut constraint and the first group of constraints, where a type of the at least one integer parameter in the second group of constraints is changed. The programming device determines values of the plurality of parameters based on the second group of constraints, to generate a programming scheme for the industrial programming job.

Abstract: A service data processing method is provided, including: obtaining a target function and a constraint condition, where the constraint condition includes a constraint relationship between a plurality of variables, and the target function includes at least one variable of the plurality of variables; selecting an initial variable from the plurality of variables for a base variable group; sorting optimized values of variables in a non-base variable group to obtain a maximum heap structure, where each node in the maximum heap structure stores an identifier of a variable and an optimized value corresponding to the variable; updating the non-base variable group and the base variable group based on a first target variable; and obtaining a solving target of a service problem based on a variable in an updated base variable group and the constraint condition.

Abstract: An automatic test pattern generation-based circuit verification method, comprises: determining a to-be-detected first logic cone from a fan-out logic cone corresponding to the target line; determining, based on the first logic cone, a to-be-detected second logic cone from a fan-in logic cone corresponding to the target line; generating a first CNF based on the first logic cone and the second logic cone, and detecting the target line by using the first CNF to obtain a first detection result; and if the first logic cone is a partial region in the fan-out logic cone, and the first detection result meets a first specified condition corresponding to the first logic cone, determining a first verification result of the target line based on the first detection result.

Abstract: This application provides a data processing method, including: obtaining service data used to define a service feature, where the service data includes constant data, the service data is used to solve an objective function; obtaining at least one constraint item, where the constraint item includes a constraint relationship between a decision variable in the objective function and the constant data; splitting the constant data to obtain a plurality of data blocks, where each data block is corresponding to at least one sub-constraint item; allocating the plurality of data blocks to a plurality of compute nodes for parallel processing, so that the plurality of compute nodes generate a plurality of constraint blocks in parallel based on the plurality of data blocks and a corresponding sub-constraint item, to obtain a constraint matrix; and then determining a value of the decision variable based on the constraint matrix.

Abstract: A method for obtaining an emission probability includes obtaining a plurality of measurement reports (MRs) of a terminal in a target region and an engineering parameter of at least one base station in the target region, obtaining, based on parameter information in each of the plurality of MRs and the engineering parameter of the at least one base station, a feature vector corresponding to each of the plurality of MRs, processing, using a regression model, location information in each of the plurality of MRs and the feature vector corresponding to each of the plurality of MRs, to obtain a single-point positioning model, calculating, based on the single-point positioning model, the location information in each of the plurality of MRs, and the feature vector corresponding to each of the plurality of MRs, an emission probability of the feature vector corresponding to each of the plurality of MRs.

Abstract: A method for obtaining an emission probability includes obtaining a plurality of measurement reports (MRs) of a terminal in a target region and an engineering parameter of at least one base station in the target region, obtaining, based on parameter information in each of the plurality of MRs and the engineering parameter of the at least one base station, a feature vector corresponding to each of the plurality of MRs, processing, using a regression model, location information in each of the plurality of MRs and the feature vector corresponding to each of the plurality of MRs, to obtain a single-point positioning model, calculating, based on the single-point positioning model, the location information in each of the plurality of MRs, and the feature vector corresponding to each of the plurality of MRs, an emission probability of the feature vector corresponding to each of the plurality of MRs.

Abstract: Embodiments of this application provide a method for obtaining a transportation scheme, including: obtaining a plurality of route schemes and a plurality of goods allocation scheme sets corresponding to each route scheme, wherein each route scheme comprises a transportation route for transporting to-be-transported goods, and the each of the goods allocation scheme sets includes at least one goods allocation scheme; obtaining, by using a fast loading model, predicted actual loading rates of each goods allocation scheme, wherein the fast loading model is trained using offline simulation data of a loading scheme that is calculated using a three-dimensional loading algorithm; and evaluating, using the actual loading rates, each route scheme and a corresponding goods allocation scheme, to obtain a target transportation scheme.

Abstract: The present disclosure relates to item separation methods. One example method includes receiving a to-be-processed order, where the to-be-processed order includes a type of a to-be-separated item and a quantity of to-be-separated items, and obtaining a separation configuration of the to-be-processed order based on the to-be-processed order and a separation configuration of a historical order included in a separation database, where the separation configuration of the to-be-processed order includes a type of a box for packing the to-be-separated item and a first quantity of boxes, and the separation configuration of the historical order includes a type of an item, a quantity of items, a type of a box for packing the item, and a second quantity of boxes.

Abstract: A method for obtaining an emission probability includes obtaining a plurality of measurement reports (MRs) of a terminal in a target region and an engineering parameter of at least one base station in the target region, obtaining, based on parameter information in each of the plurality of MRs and the engineering parameter of the at least one base station, a feature vector corresponding to each of the plurality of MRs, processing, using a regression model, location information in each of the plurality of MRs and the feature vector corresponding to each of the plurality of MRs, to obtain a single-point positioning model, calculating, based on the single-point positioning model, the location information in each of the plurality of MRs, and the feature vector corresponding to each of the plurality of MRs, an emission probability of the feature vector corresponding to each of the plurality of MRs.

Abstract: A terminal positioning method and a network device, where the network device obtains radio signal sampling information of a first terminal at a current moment. The first terminal is any terminal in a target region, and the target region is a preset geographic region. The network device obtains position information of the first terminal at the current moment by prediction based on the radio signal sampling information of the first terminal at the current moment and a predictive model of the target region. The predictive model is obtained by extensive data training in the target region, has relatively strong error tolerance and error-correction capabilities, and can accurately reflect a relationship between radio signal sampling information and position information of a terminal. Terminal positioning accuracy is effectively improved.

Abstract: The present disclosure provides a data visualization method and apparatus. The method includes: displaying a distribution curve diagram by using a display device, where the distribution curve diagram is used to represent time-based distribution of multiple pieces of spatial-temporal data, and the distribution curve diagram includes a timeline, a curve changing with the timeline, and an irregular region enclosed by the curve; and displaying a tree map in the irregular region by using the display device, where the tree map divides the irregular region into m sub-regions that are in a one-to-one correspondence with m regions, and an area of each of the m sub-regions is used to indicate an amount of spatial-temporal data distributed in a region corresponding to each sub-region. The present disclosure implements visualization of spatial-temporal data by using the tree map.

Abstract: A terminal positioning method and a network device, where the network device obtains radio signal sampling information of a first terminal at a current moment. The first terminal is any terminal in a target region, and the target region is a preset geographic region. The network device obtains position information of the first terminal at the current moment by prediction based on the radio signal sampling information of the first terminal at the current moment and a predictive model of the target region. The predictive model is obtained by extensive data training in the target region, has relatively strong error tolerance and error-correction capabilities, and can accurately reflect a relationship between radio signal sampling information and position information of a terminal. Terminal positioning accuracy is effectively improved.

Abstract: The present disclosure provides a data visualization method and apparatus. The method includes: displaying a distribution curve diagram by using a display device, where the distribution curve diagram is used to represent time-based distribution of multiple pieces of spatial-temporal data, and the distribution curve diagram includes a timeline, a curve changing with the timeline, and an irregular region enclosed by the curve; and displaying a tree map in the irregular region by using the display device, where the tree map divides the irregular region into m sub-regions that are in a one-to-one correspondence with m regions, and an area of each of the m sub-regions is used to indicate an amount of spatial-temporal data distributed in a region corresponding to each sub-region. The present disclosure implements visualization of spatial-temporal data by using the tree map.

Abstract: A data visualization method includes acquiring a spatiotemporal behavior data set generated by network users, determining, according to a time point at which or a time period in which each piece of spatiotemporal behavior data is generated, an amount of spatiotemporal behavior data that is in the spatiotemporal behavior data set and generated at a time point or in a time period falling within each time period in N time periods, and presenting a column bar corresponding to an ith time period in the N time periods, where the column bar is in a radial direction of a first circle representing a full time domain and intersects the first circle and the length of a column bar represents a quantity of behaviors in a time period corresponding to the column bar.

Abstract: A trajectory data query method includes establishing a spatial-temporal index and an inverted index for trajectory data in a spatial-temporal database, where the inverted index is used to form a first relationship correspondence table that includes a correspondence between each trajectory and its associated index leaf node; performing sampling for an index leaf node included in a space area specified by a user, where a quantity of index leaf nodes in the space area and a quantity of index leaf nodes obtained by sampling are determined; determining, according to the index leaf nodes obtained by sampling and the first relationship correspondence table, a correspondence between each trajectory included in the index leaf nodes obtained by sampling and an index leaf node associated with the trajectory, to form a second relationship correspondence table; and determining an unbiased estimation operator according to the quantity of index leaf nodes in the space area.

Abstract: A user unsubscription prediction method and apparatus includes obtaining service consumption feature data, position activity feature data, and social network feature data of a user within a first preset time period, where the position activity feature data refers to data related to communication between the user and each base station within the first preset time period, and the social network feature data refers to data related to communication between the user and another user in a social network within the first preset time period, and inputting the obtained service consumption feature data, position activity feature data, and social network feature data to a pretrained classifier for calculation and outputting a calculation result, where the calculation result is a user unsubscription prediction result.

Abstract: A topic mining method and apparatus are disclosed. When an iterative process is executed each time, an object message vector is determined from a message vector according to a residual of the message vector, so that a current document-topic matrix and a current term-topic matrix are updated according to only the object message vector, and then calculation is performed, according to the current document-topic matrix and the current term-topic matrix, on only an object element that is in the term-document matrix and that corresponds to the object message vector, thereby avoiding that in each iterative process, calculation needs to be performed on all non-zero elements in the term-document matrix, and avoiding that the current document-topic matrix and the current term-topic matrix are updated according to all message vectors, which greatly reduces an operation amount, increases a speed of topic mining, and increases efficiency of topic mining.

Abstract: An entity matching method and apparatus, where the method includes, calculating kernel matrices K and L after reading a first data source and a second data source with inconsistent entity quantities, respectively, solving a first optimization objective function to obtain a matrix M of a correspondence between an entity on the first data source and an entity on the second data source, and outputting the obtained matrix M. Hence, according to the entity matching method and apparatus provided in the present disclosure, entity matching when entity quantities of data sources are inconsistent may be performed such that accuracy of data mining may be effectively improved, and data value may be effectively presented.