22 results about "Column generation" patented technology

The invention provides an autonomous controllable database intelligent adaptation method and system oriented to localization ecology, and belongs to the technical field of database middleware and cloud native resource management. When the request label is missing or wrong, JDBC metadata, a system function return value and system table structure features are collected through detection connection to generate database fingerprints, and the database type and version are recognized in the localized feature library. For an SQL execution request, parsing the SQL into an abstract syntax tree based on a unified syntax parser, rewriting nodes according to a dialect rule base to generate a target dialect SQL, and performing paging, identification column generation, identifier reference, transaction-related semantic verification, execution plan optimization and dynamic routing execution; and thermally loading from the plug-in warehouse when the driver is missing. And for the resource opening request, calling a Kubernetes Operator to automatically create a domestic database instance, and returning connection information. The system integrates a national cryptographic algorithm and behavior auditing, and realizes connection information protection and abnormal SQL detection.

The invention discloses a dynamic column report generation method and system based on multi-source data fusion, a terminal and a storage medium, and the method comprises the steps: obtaining multi-source heterogeneous data, and preprocessing the multi-source heterogeneous data to obtain preprocessed multi-source heterogeneous data; constructing a multi-source data association knowledge graph and a work order process execution track according to the preprocessed multi-source heterogeneous data, and constructing a distributed data association calculation engine according to the multi-source data association knowledge graph; and obtaining a target query condition, and according to the target query condition, performing report column number generation processing and report column number expansion processing by adopting the distributed data association calculation engine and the work order process execution track to obtain a target demand dynamic list. By constructing the distributed data association calculation engine, report column number generation processing and report column number expansion processing can be performed according to the target query condition, so that the target demand dynamic list is obtained, and the generation efficiency of the gas report is effectively improved.

The invention relates to the technical field of network security intelligence, in particular to an information acquisition scheduling system based on dynamic weight optimization, which comprises a data monitoring and acquisition module, a scheduling queue generation module, a content analysis and feedback module, a crawler execution module and a content analysis and feedback module. Collecting user interaction data, content change rate and the like of a target intelligence source through a data monitoring and collecting module; the dynamic weight calculation module calculates an activeness score, a historical hit rate and a low-frequency protection gain according to the data and fuses the data to obtain a comprehensive final weight; a scheduling queue generation module builds a main queue and a low-frequency guarantee pool according to weight sorting, and distributes differential grabbing parameters; the crawler execution module performs distributed parallel grabbing; the content analysis and feedback module judges validity and feeds back adjustment parameters to form a closed loop; according to the method, the capture coverage rate and timeliness of the low-frequency high-value intelligence source can be improved, the utilization rate of system resources is optimized, and the requirements of network security intelligence for information comprehensiveness, timeliness and accuracy are met.

The application discloses a kind of management systems and implementation methods of full life cycle operation and maintenance, it is related to full life cycle technical field.Constructs full cycle initial dynamic operation and maintenance hypergraph;Generation represents the dynamic hypergraph time sequence evolution sequence of system topology evolution along with life cycle;Generation full cycle space-time fusion operation and maintenance representation;Output the multidimensional abnormal risk prediction distribution atlas of the future operation trend of representation system;Based on the full life cycle management library, the corresponding resource degradation, isolation or expansion strategy is matched, and the adaptive operation and maintenance scheduling execution instruction set for directly intervening target system is generated.The application makes that when processing the full cycle long sequence data of mass node scale, the time axis resolution of operation and maintenance characteristics is significantly improved, especially in the correlation tracing of long-range latent fault.

The invention discloses an efficient and parallel autoregressive diffusion model hardware acceleration system based on an FPGA (Field Programmable Gate Array), and relates to the technical field of FPGA and machine learning. The system comprises a host end and an FPGA hardware end, the host end is responsible for preprocessing and post-processing of data, and the FPGA hardware end comprises a system control scheduling layer, a three-level storage structure layer and an autoregressive diffusion parallel architecture. According to the method, a collaborative pipeline design is adopted, deep parallelism of an autoregression Token generation process and a diffusion picture generation process is realized through a Token grouping adding mechanism, and a diffusion denoising process can be started without waiting for the completion of complete sequence generation. Besides, a universal attention processing hardware module is designed in the system, QKV projection and matrix multiplication are realized by using a systolic array, and calculation resources are optimized in cooperation with a pipelined Softmax calculation and delay normalization strategy. Through collaborative design of software and hardware, the problems of high reasoning delay and large resource overhead of the autoregression diffusion model in an edge computing scene are effectively solved, and the throughput and the energy efficiency ratio are remarkably improved while the generation quality is ensured.

The invention provides an automatic testing method and device based on test sequence generation, equipment and a medium, and relates to the technical field of server testing. The method comprises the following steps: acquiring natural language test requirement data, and generating a structured target test step sequence based on a test requirement; then resource state information of the environment to be tested is collected, the resource state information is combined with the target test step sequence, and a test task scheduling instruction used for indicating a step execution strategy is generated; and distributing the test task scheduling instruction to a plurality of distributed execution nodes in a to-be-tested environment, and executing test steps in the scheduling instruction by the distributed execution nodes to obtain a corresponding test execution result. According to the scheme, automatic generation from natural language requirements to executable test steps can be achieved, reasonable scheduling is carried out based on the environment resource condition, and the execution efficiency and accuracy of the test task in the distributed environment are improved.

A secure aggregation computation device 10 comprises: a sorting unit 1 that, by sorting rows of a table which includes a share {→g} of a group key column →g, a share {→o} of an order key column →o, and a share {→v} of a data column →v on the basis of the order key column →o and the group key column →g, generates a sorted table using the share {→g}, the share {→o}, and the share {→v}; a group boundary flag column generation unit (2) that uses a share {→g'} of a sorted group key column →g' included in the sorted table to generate a share [→b] of a boundary flag column →b which indicates a boundary between groups in the sorted table; and an aggregation computation unit 3 that uses the share [→b] and a share {→v'} of a sorted data column →v' included in the sorted table to perform, for each group, a prescribed aggregation computation using a prescribed binary operator.

The invention relates to the technical field of production management, and discloses an MES system intelligent production scheduling and tracing method and system, and the method comprises the steps: generating a batch index according to a loading list and a UDI column, executing parallel batch matching on the basis of the batch index to obtain a loading sequence, and forming a loading matrix through cavity filling under the constraint of carrier capacity. Then, time mapping is obtained through environment sequence sliding window alignment, fluctuation suppression is executed according to the time mapping to obtain smooth mapping, stable input is obtained in a corresponding section of the loading matrix, binding check is executed on the smooth mapping through a cyclic curve to generate a binding matrix, threshold comparison is executed on the release record according to the binding matrix to obtain a consistent vector, and the consistent vector is obtained; the continuous processing enables adjacent batches to form continuous loading at the same carrier number and level position, reduces parallel loading failure and temporary distribution change, reduces sterilization switching loss, inhibits short-time fluctuation in a time mapping limited section, and further inhibits capacity fluctuation of the clean room.

The invention discloses an over-path traffic solving method for a completely-crowded large-scale public transportation network, and the method comprises the steps: obtaining a getting-on arc and a corresponding effective departure frequency through a first algorithm; the second algorithm calculates the use probability of passing through all the upper turning arcs under the super path, so that the complete upper turning arc flow distribution of the super path, the use probability vector of the upper turning arcs and the use probability vector upper turning arcs of the nodes are obtained; then, adopting column generation to construct an OD pair sub-problem, and determining the optimal transfer amount from a non-reference super path to a reference super path in the OD pair sub-problem through binary search; and the fourth algorithm obtains an over-path traffic equilibrium solution under the public transportation network equilibrium condition. Therefore, by setting the first algorithm, the second algorithm and the like, a complete algorithm capable of processing large-scale public transportation network distribution is constructed, so that the super path is constructed based on the effective departure frequency, and the method is suitable for practical application of the city-level large-scale public transportation network.

A secure aggregation computational device 10 comprises: a sorting unit 1 that generates a sorted table in which rows of a table are sorted on the basis of an order key column →o and a group key column →g; a group boundary flag column generation unit 2 that generates a share [→b1] of a boundary flag column →b1 representing boundaries of groups in the sorted table; an intermediate aggregation result column generation unit 4 that generates a share {→p} of an intermediate aggregation result column →p, an i-th element of which is the value obtained by calculation using some or all of the elements included in a group to which the i-th element belongs; a subgroup boundary flag column generation unit 5 that generates a share [→b2] of a boundary flag column →b2 representing boundaries of subgroups within each group in the sorted table, a subgroup being a portion within each group where the value of an order key is the same value consecutively; and a final aggregation result column generation unit 6 that generates a share {→s} of a final aggregation result column →s in which values aggregated from elements belonging to respective subgroups within the intermediate aggregation result column →p are the respective elements belonging to each subgroup.

This invention relates to a two-stage robust planning method for demand-side capacity that considers both cost and flexibility resources, belonging to the field of power system operation and maintenance technology. By introducing an uncertainty adjustment parameter, this invention constructs a box-shaped uncertainty set with flexibly adjustable conservatism, effectively mitigating the inherent drawbacks of overly conservative traditional robust optimization methods. This allows the model to dynamically adjust the boundary of the uncertainty set according to the different risk tolerances of the actual system, thus achieving a refined trade-off between economy and reliability during the planning stage. The two-stage robust optimization model constructed in this invention, considering the electricity-carbon coupling mechanism, incorporates carbon trading costs as an important component of operating costs into the objective function, effectively responding to the needs of the national green and low-carbon energy strategy. The improved column generation and interior point hybrid algorithm designed in this invention proposes an adaptive scenario selection mechanism and a gradient-guided initialization strategy, significantly shortening the solution time while ensuring the global optimality of the solution.

The invention relates to the technical field of equipment operation evaluation, and discloses a stable operation limit evaluation method and system for power electronic equipment under a weak power grid condition. Comprising the steps of multi-source heterogeneous parameter fusion acquisition, dynamic adaptive coupling modeling, full-scene disturbance sequence generation, real-time simulation scheduling operation, multi-dimensional time sequence feature mining and stability margin quantitative judgment. Multi-source heterogeneous parameter fusion acquisition synchronously covers a power grid side impedance spectrum, voltage transient characteristics and equipment side switch transient parameters, and an effective parameter set is constructed through heterogeneous data calibration and redundancy suppression processing; according to the method, the problems of single parameter acquisition and insufficient data validity in traditional evaluation are solved, evaluation one-sidedness caused by single parameter acquisition is avoided, invalid data are eliminated through redundancy suppression, and data precision is guaranteed through calibration processing; the technical problem that parameters in a weak power grid and power electronic equipment interaction scene are complex and diverse and are difficult to effectively collect is solved.

The invention provides a self-adaptive scheduling and resource optimization method and system for an autonomous mobile robot group in a hospital scene. The method comprises the steps that tasks issued by a hospital HIS / ERP are coded into multi-dimensional constraint vectors; performing constraint matching on the task demand and the AMR to generate a feasible set; constructing a candidate path set meeting conditions on the topological graph of the clean partitions; constructing a plurality of uncertain scenes to calculate scenarized risk indexes and CVaR robust constraints for each task to obtain a risk index set; obtaining task-robot-path initial allocation by adopting column generation / mixed integer programming; obtaining an executable queue by adopting a cloud-edge-end layering technology; through online learning, travel time-varying distribution, people flow density and risk parameters are updated, and self-adaptive convergence is carried out through feedback operation; the whole process is in bidirectional butt joint with HIS / ERP of a hospital, an auditable event tracing chain is formed, and an abnormal closed loop and compliance report is output.

This paper relates to an intelligent packing method, device, and system for heterogeneous items considering segmentation constraints. First, it obtains the item dimensions, box dimensions, and a segmentation constraint matrix defining item conflict relationships. Then, it constructs a hybrid integer programming model that simultaneously incorporates geometric and segmentation logic constraints. A hybrid branch-and-price algorithm is used to solve the model. This algorithm iteratively optimizes through a column generation framework, where the pricing subproblem integrates particle swarm optimization and spatial heuristic decoding to efficiently generate new single-box loading patterns. Finally, a branch-and-bound strategy is combined to obtain the integer optimal solution. The system includes modules for data acquisition, optimization calculation, and solution output, achieving a closed loop from perception and decision-making to execution. This invention solves the problem that existing technologies cannot collaboratively optimize space utilization and complex business rule constraints. It can minimize the number of packaging boxes used and improve the feasibility and execution efficiency of packing schemes while strictly meeting segmentation requirements such as the isolation of fragile items.

The invention relates to the technical field of computers, in particular to an e-commerce data integration analysis method and system, and the method comprises the steps: obtaining and associating structured business data and unstructured text data of an e-commerce platform; performing cleaning, word segmentation and word form normalization on the unstructured text data to obtain a lexical item sequence; lexical item weight features and semantic embedding features are generated based on the lexical item sequence, the lexical item weight features are jointly determined by the occurrence degree of a single text and corpus distinction degree, and the semantic embedding features are obtained by predicting context word training through head words; inputting the lexical item weight features, the semantic embedding features and the structured business data into a deep learning semantic model, outputting probability distribution and confidence of emotion or intention, and constructing physiological signal features according to the probability distribution, based on the time sequence information, the message direction information and the interaction event sequence, constructing an interaction state feature to represent a change trend of the message quantity along with time, a dialogue dominant relationship and an upgrading moment; standardizing and fusing multi-source features into a feature matrix, and establishing a perception-context matrix to realize dimension mapping from key terms to service quality; training an isolation forest algorithm tree set for each service quality dimension, randomly selecting features and segmentation points of each isolation tree, performing recursive division until a sample is isolated or meets a preset termination condition, and obtaining an expected path length; and calculating an abnormal score according to an expected path length, generating an abnormal mark and an abnormal explanation in combination with a decision path, and outputting a disposal suggestion, and using an execution result to update a perception-context matrix and a deep learning semantic model parameter. According to the method, the problems that the structured business data and the unstructured text data in the e-commerce platform are difficult to effectively associate and fuse, the service quality abnormity in the dialogue process is difficult to identify in time, and the abnormity source and the key trigger factor are difficult to explain can be solved.

A secure aggregation computational device 10 comprises: a sorting unit 1 that uses a share {→g} and a share {→o} to generate a sorted table in which rows of a table are sorted on the basis of an order key column →o and a group key column →g; a group boundary flag column generation unit 2 that generates a share [→b1] of a boundary flag column →b1 representing boundaries of groups in the sorted table; an intermediate aggregation result column generation unit 4 that generates a share {→p} of an intermediate aggregation result column →p representing an ordinal row position within each group; a subgroup boundary flag column generation unit 5 that generates a share [→b2] of a boundary flag column →b2 representing boundaries of subgroups within each group in the sorted table, a subgroup being a portion within each group where the value of an order key is the same value consecutively; and a final aggregation result column generation unit 6 that generates a share {→s} of a final aggregation result column →s representing an ordinal position of the value of each order key within each group.

A flag sequence generator (12) generates {x0}, . . . , {xλ−1} indicating a msb of a. A bit sequence generator (13) calculates {yi}:={x2i} XOR {x2i+1} to generate {y0}, . . . , {yλ′−1}. A flag calculator (14) calculates an exclusive logical sum of all {xj} to calculate [r] for each odd j. A public value multiplier setting-unit (16) sets r′ that becomes √2 when λ is an odd and 1 when λ is an even. A normalization multiplier generator (17) bit-connects {y0}, . . . to generate [c′]. A normalization multiplier generator (18) bit-connects {xλ−1}, . . . to generate [c]. A normalizer (19) calculates [b]:=[a][c]. A square root calculator (20) calculates [w]:=[√b]*(r′ / √2) when r=1, and [w′]:=[√b]*r′ when r=0. An inverse normalizer (21) calculates [w][c′] and performs λ′ bits right-shift.

The invention relates to a resource multi-dimensional response potential dynamic assessment method and system, and the method comprises the steps: obtaining multi-source data of a target assessment resource, the multi-source data at least comprising resource inherent attribute data, external dynamic factor data and real-time operation state data; fractal-dimension adjustable capability boundary calculation is carried out, specifically, based on the multi-source data, adjustable capability boundaries of the resources under at least two different dimensions are calculated respectively, and the adjustable capability boundaries are power boundaries; on the basis of external dynamic factor data in a future time period, the fractal-dimension adjustable capability boundary calculation is executed in a rolling mode, and a dynamic potential boundary sequence under all dimensions in the future time period is generated; and according to the dynamic potential boundary sequence, generating a constraint condition for the resource scheduling power, and outputting the priority of each dimension according to a predefined scene rule. According to the method, the accuracy and the real-time performance of the evaluation result can be improved, and the maximization and the optimal utilization of the resource potential are realized.

This invention relates to the field of production management technology and discloses a production scheduling plan generation method, system, electronic device, and readable storage medium. The method involves repeatedly sorting production order blocks corresponding to each product type to obtain multiple production order block sequences. The order of production orders for each product is constrained according to product type by set sorting constraints. Based on preset satisfaction values ​​corresponding to the sorting constraints, a sequence satisfaction value is determined for each production order block sequence. This allows for the determination of a target sequence from the production order block sequences, and the generation of a production schedule based on the target sequence. By fully considering the product type of the orders during production order scheduling, the utilization rate of production resources is improved, thereby increasing production efficiency.

The application discloses a quantum state-based program behavior intervention method, and particularly relates to the technical field of computer security protection, and is used for solving the resource conflict and stability decline caused by systematic mismatch when quantum randomness is directly introduced into a classical computing system; through real-time acquisition of a quantum random number sequence and synchronous monitoring of system state parameters of a target program, a cluster mode in the random sequence is identified, and the system state is coupled to determine an intervenable scheduling gap of the operating system; subsequently, the matching degree of the cluster mode and the scheduling gap is evaluated to determine a compatibility relationship; based on the relationship and the system state parameters, a Pareto frontier of intervention efficiency and system stability is constructed, and an optimized solution set is determined; through evaluation of the cumulative effect of the optimized solution and historical intervention, an adaptive operation point is selected; finally, an intervention instruction is generated according to the operation point by modulating the quantum random number sequence, and the intervention instruction is injected into the target program; and the adaptive cooperation of quantum randomness and system determinism is realized.

The invention relates to an electric power communication routing technology, in particular to a space-air-ground multi-source multicast routing method and system based on column generation, and the method comprises the steps: considering node, link and delay constraints in a satellite network, and constructing and solving an optimization problem of a multi-source multicast energy-saving multicast tree; decomposing an optimization problem into a main problem of selecting an optimal routing scheme for each multicast request under the constraint of nodes and links, and a pricing problem of iteratively generating available multicast routing schemes; decomposing a pricing problem into a plurality of sub-pricing problems by using a decomposition theory, and designing a delay-aware Viterbi path cost calculation algorithm to accelerate the solving process; and designing a multisource time delay sensing multicast algorithm to obtain an optimal solution of the main problem, namely an optimal multicast forest. The multi-source multicast routing problem in the power grid service can be effectively solved, the load pressure of the multi-source node is relieved, and the energy consumption of the satellite node for power communication is reduced.