5 results about "Decomposition problem" patented technology

The invention provides a complex question and answer method and system based on adaptive task deconstruction and multi-modal evidence aggregation, belongs to the technical field of natural language processing, and designs a dynamic Few-shot prompt construction method based on dependency syntax fingerprints to ensure that a prompt template is matched with a question structure; the invention discloses a dynamic problem deconstruction method based on confidence evaluation and auto-reflection. The method comprises the following steps: recursively decomposing a problem tree by using a large language model; converting the problem tree into a standardized linear task execution sequence by a problem tree context dependence specification and task sequence generation method; obtaining a high-correlation evidence set of each task based on an evidence generation method of two-way recall and cross encoder rearrangement; and the task sequence is reasoned and dynamically optimized by a question answer extraction method based on double-strategy aggregation reasoning. According to the method, the accurate complex question and answer result can be provided on the premise of ensuring the question disassembling quality, restraining error propagation and comprehensively recalling evidences.

Quantum optimization with Rydberg atom arrays is provided. In particular, methods are provided for solving combinatorial graph optimization problems, constraint satisfaction problems, maximum independent set problems, algebraic problems, and factoring.

The invention discloses a multi-table fine-grained retrieval method and device based on large model decomposition reasoning. The method comprises the following steps: firstly, prompting a table cell value and field description of each field of a table to a large model to obtain a field-level semantic annotation; then, relevant table fields are positioned through an analysis-mapping-filling strategy, a large model is used for understanding and decomposing problems, and key information such as entities and conditions is extracted; a field set required by the question is screened out in combination with table structure information; then, based on a field retrieval result, analyzing a value range of the field and further positioning related cells; and finally, integrating the retrieved fields and cells to generate a fine-grained target sub-table which is used for answering user questions. Compared with whole-table-level retrieval, the method only captures required information like human reading, significantly reduces redundant interference, improves precision ratio and response speed, and can be widely applied to medical treatment, finance, complex database management and other scenes with strict requirements for accurate structured data retrieval.

The embodiment of the invention provides a multiphase pipe flow multi-parameter optimization method and system based on a genetic algorithm, and belongs to the field of multiphase fluid mechanics and oil and gas pipeline engineering. The method comprises the following steps: constructing a corresponding multi-objective function model based on a decomposition problem of a target multi-phase pipe flow problem; wherein the decomposition problem comprises any one or more of a liquid holdup accuracy problem, a friction resistance coefficient accuracy problem and an on-way length accuracy problem; calling a genetic algorithm based on a multi-objective function model, and carrying out individual coding and group initialization operation; executing the genetic algorithm, and executing optimization solution on the multi-objective function model; and repeating iteration until the optimized multiphase pipe flow calculation model meets the target precision, and outputting an individual with the highest fitness as a final optimization result. According to the scheme, the problems that a traditional method cannot give consideration to multi-objective optimization and the global search capability is insufficient are solved, and reliable technical support is provided for simulation and control of oil and gas field multiphase flow.

The application provides an anomaly detection method, device and storage medium for image data, and relates to the technical field of image processing. The method comprises the following steps: performing feature extraction on image data, fusing spectral and spatial features to obtain a joint feature matrix, and inputting the joint feature matrix into an anomaly detection model; the model uses an alternating direction multiplier algorithm to solve a low-rank sparse decomposition problem, and a target function comprises a data fidelity term, a regularization term and a band weight term; the regularization term comprises a low-rank constraint and a sparse constraint, and the band weight term acts on the low-rank constraint in a weighted form; in the solving process, an iteration method is used to update a background low-rank tensor, an anomaly sparse tensor and a Lagrange multiplier, as well as a sparse constraint weight, a band weight term and a penalty parameter of the algorithm; the iteration is repeated until a preset termination condition is reached, an anomaly score map is calculated based on the anomaly sparse tensor, and an anomaly target is determined by comparison. The application can solve the problem that it is difficult to accurately identify an anomaly target in a complex scene, and improve detection accuracy and efficiency.