20 results about "System quality" patented technology

The invention discloses a method and device for comprehensively optimizing test resources, electronic equipment and a storage medium, and belongs to the technical field of software test.The method comprises the steps that a test case set is classified through a high-dimensional data clustering algorithm, and a plurality of test case classes are obtained; selecting representative test cases from each test case class based on an improved greedy algorithm to form a target test case subset; performing priority ranking on the target test case subset by adopting a firefly group optimization algorithm to obtain a ranking result; and optimizing distribution and scheduling of test resources according to the sorting result so as to preferentially execute high-priority test cases and realize resource load balancing. By combining high-dimensional data clustering, an improved greedy algorithm and a firefly group optimization algorithm, the problem of large-scale test case management in the interconnection and interworking test of heterogeneous AC and AP equipment is solved, comprehensive optimization management of test resources is realized, and the test efficiency and the system quality are remarkably improved.

The invention discloses a commercial vehicle accompanying production line tightening data binding method and system, relates to the technical field of commercial vehicle manufacturing, and is applied to an environment comprising a vehicle identification device, a tightening tool, a manual work reporting button, a data binding system, a quality andong system and an AGV control system. The method comprises the following steps: acquiring information when a vehicle enters a station; the system calls a matched tightening program and switches to a tool according to the tightening program; the personnel tightens according to a program, and a tool system synchronously collects and generates vehicle tightening data; after the data is complete, the staff reports the work; and the quality andong system automatically checks the tightening result based on the work reporting signal, judges the number of qualified point locations and outputs the result. If the AGV is qualified, the system binds and stores the data to a database, and controls the AGV to advance after success; and if not, triggering an alarm and controlling the AGV to stop. According to the method, the problem of data cross-station wrong binding is solved, and binding accuracy and quality controllability are ensured.

The purpose is to reduce the burden of ensuring system quality. [Solution] This is a program for causing a computer to execute a first acquisition step of acquiring test code that describes one or more logical elements 2 to be tested and the test content for the one or more logical elements 2, a second acquisition step of acquiring the results of the test using the test code, and a generation step of generating presentation information that indicates the correspondence between the test indicated by the test code and each of the one or more logical elements 2, and the results of the test using the test code.

The invention relates to the technical field of hang tag gun pins, and particularly discloses a hang tag gun pin production efficiency optimization method and system based on industrial big data, and the method comprises the steps: collecting production line dynamic parameters and process compliance parameters, and carrying out the calculation to obtain an efficiency deviation reflecting the beat stability; and determining dynamic standard process operation parameters by combining the quality coordination factor and the equipment health degree factor, calculating equipment operation deviation parameters by integrating the equipment instantaneous working condition, the adjustable performance, the vibration risk and the order time requirement, and then performing collaborative analysis on the efficiency deviation, the standard process parameters and the equipment operation deviation. A system quality risk coefficient is introduced, a comprehensive optimization parameter is generated, a target process parameter is obtained through mapping according to the comprehensive optimization parameter, finally, a cooperative control instruction subjected to environment interference compensation is generated based on the target parameter and issued to an execution unit, and dynamic cooperative optimization of the stamping efficiency and the process quality is achieved.

A big data job planner uses online machine learning to recommend algorithms for each job in a sequence to enhance various aspects of job execution. A job algorithm prediction server processes a job's pre-runtime metadata to create predictions of relevant big data job behavior characteristics based on previously learned models of the corresponding big data system's behavior and provides a recommended algorithm to the client big data system. After the big data job is executed, the job metadata coordinator persists pre-runtime metadata and corresponding post-runtime big data job behavioral metadata actually observed. Repeatedly through time, online machine learning is performed on this sequence of job behavior metadata so that machine learning models will learn difficult-to- recognize phenomena, as well as, changes in system behavior through time. Unlike statically coded rules, the system models changing patterns and behaviors, enabling the algorithm predictions to remain useful, thereby enhancing big data system quality.

The invention relates to a seamless steel tube quality full life cycle tracing system, and belongs to the technical field of seamless steel tube production quality management and control, and the system comprises a data collection module which is used for collecting quality detection data of each link of a seamless steel tube full life cycle; the ERP integration module is used for establishing a bidirectional data interaction channel with an ERP system, receiving the quality detection data and synchronizing the quality detection data to the ERP system; the quality tracing core module is used for reversely positioning problem procedures and associating batch products and corresponding raw materials through tracing codes; and the early warning module is used for giving out early warning when the quality detection data exceeds the control limit or presents an abnormal trend. Through the ERP integration module, bidirectional intercommunication between quality data and resource data of purchase, production, inventory, sales and the like in an ERP system is realized, quality management and control and enterprise resource plans are deeply fused, a resource-quality integrated management mode is formed, the problem that an existing traceability system is disjointed from ERP is solved, and the overall management efficiency of enterprises is improved.

A custom system data stream stitches together aspects of data streams from source systems. In one implementation, an analytics circuit extracts from a first data stream received from a system quality assurance (QA) management system, test case data. The analytics circuit parses metadata, such as a user story identifier, from the test case data. Based on the metadata, the analytics circuit parses, from a second data stream received from a system development lifecycle (SDLC) management computing system, SDLC item data, such as a project identifier. Based on the SDLC item data, the analytics circuit determines at least one impacted computer application. The custom system data stream is bound to a graphical user interface. In some implementations, the interface includes a plurality of side-by-side smart dials.

The invention provides a baked food intelligent dynamic production allocation system based on multi-source heterogeneous data fusion, belongs to the technical field of baking production allocation, and solves the technical problems that existing baked food production information is independent, global optimization is lacked and the like. The invention discloses an intelligent dynamic production allocation system for baked food based on multi-source heterogeneous data fusion. Comprising a multi-source heterogeneous data acquisition subsystem, a data fusion engine processing subsystem, an intelligent decision subsystem, a dynamic execution subsystem, a store management subsystem, a visual management subsystem, a factory MES subsystem, a warehouse management subsystem, a quality feedback subsystem and a supply chain subsystem. The system further comprises a store end Appp / applet, a production allocation platform end and a production board end. Through multi-source heterogeneous data fusion, the decision is obtained based on global real-time data, the method is more accurate and perfect, enterprise and intelligent global resource collaborative optimization dynamic production allocation can be performed in a variable environment, and the method has a tracing self-learning function and continuously strengthens the overall decision ability.

This application discloses a method and system for binding tightening data on a commercial vehicle production line, relating to the field of commercial vehicle manufacturing technology. It is applied in an environment including a vehicle identification device, tightening tools, a manual reporting button, a data binding system, a quality control system, and an AGV control system. The method includes: acquiring vehicle information upon entry; the system retrieving a matching tightening program and switching to the tool accordingly; personnel tightening according to the program, with the tool system simultaneously collecting and generating vehicle tightening data; personnel reporting the work after data completion; and the quality control system automatically verifying the tightening results based on the reporting signal, determining the number of qualified points, and outputting the results. If qualified, the system binds and stores the data in the database, and controls the AGV to move forward upon success; if unqualified, an alarm is triggered and the AGV is stopped. This method solves the problem of misbinding data across workstations, ensuring binding accuracy and quality controllability.

The embodiment of the invention provides a system quality evaluation method and device, a storage medium and a program product. The method comprises the steps of obtaining a plurality of query statements and standard reply statements corresponding to the query statements respectively, inputting the query statements into a to-be-evaluated system, obtaining to-be-evaluated reply statements corresponding to the query statements respectively, and aiming at each query statement, obtaining a to-be-evaluated reply statement corresponding to the to-be-evaluated reply statement corresponding to the to-be-evaluated reply statement; inputting a standard reply statement corresponding to the query statement and the to-be-evaluated reply statement into a first model to obtain a corresponding target evaluation result, the target evaluation result being used for indicating a quality change condition between the to-be-evaluated reply statement and the standard reply statement, and determining a system quality evaluation result according to the target evaluation results corresponding to the plurality of query statements. According to the method provided by the embodiment of the invention, the effectiveness of system evaluation can be improved.

This invention discloses a business development method, apparatus, electronic device, and storage medium. The method includes: encapsulating system code corresponding to underlying resources into a system component with overall functionality; configuring a JSON interface for the system component; and accessing the system component via the JSON interface in business code, so that the business code can call the overall functionality. This invention decouples business code and system code, requiring only the writing of business code, thus ensuring system quality and improving development efficiency. Furthermore, this invention improves the reusability of system code, achieving stable and efficient system operation.

The application discloses a test-oriented software quality evaluation method and device, which is used for rapid, automatic and multiple quantitative evaluation of a quality state of a software or system under test in a software test process. The method and device are used in the software test process, and only test data such as software problem scale can drive the evaluation model to automatically operate, so that the cost of carrying out a software quality evaluation activity in the software test process can be reduced, and the efficiency and feasibility of the software quality evaluation can be improved. The extended comprehensive evaluation set vector used can be customized and adjusted by a user, so that flexibility of the evaluation model is ensured.

The invention relates to the technical field of power system quality monitoring, in particular to an S-level power quality event annular recording method. Comprising the following steps: initializing a timer in a metering module; creating an event data annular buffer area in the application module, defining a data processing callback function, and injecting the data processing callback function into the metering module for storage through a registration interface; the metering module periodically collects power data based on timer interruption and calls a data processing callback function to transmit the power data to the application module; the application module judges S-level electric energy quality event conditions, enqueues an event data annular buffer area if the electric power data meet event triggering conditions, and directly returns if the electric power data do not meet the event triggering conditions; and when the application module checks that the event data annular buffer area is not empty, reading the electric power data from the position of the read pointer, writing the electric power data into the nonvolatile memory, and directly returning the electric power data if the electric power data is empty. According to the method, high-precision detection of the S-level electric energy quality event can be realized, and the high-quality electric power monitoring requirement is met.

The present application relates to the technical field of data transaction, in particular to a data transaction intelligent quality evaluation method and system based on multi-dimensional cooperation. The quality evaluation method comprises the following steps: S1, a data transaction platform receives a data product to be traded submitted by a data seller, and matches a corresponding data buyer according to the information of the data product; S2, quality detection is performed on the data product to identify data with quality problems. By identifying the behavior information of the data buyer, the preferred quality demand of multiple different data buyers is obtained, and according to the behavior information of multiple different data buyers, mutual cross verification is performed to obtain the basic demand (i.e. implicit quality demand) of the scene where the data product is located. The basic demand and the preferred quality demand jointly divide the scoring weight proportion of different data buyers in the scene where the data product is located, so as to realize the scene quality score evaluation for the scene where the data product is located, and reduce the generation of value mismatch phenomenon.

The embodiment of the invention relates to the field of artificial intelligence, medical health and financial science and technology, and discloses a quality evaluation method and device based on a business system, equipment and a storage medium. The method comprises the following steps: extracting service information and service defects from a service event; analyzing the service information and the service defects, and determining key information corresponding to the service information and the service defects; generating corresponding ternary vector labels for the service information and the service defects according to the key information; generating a service system quality map according to the ternary vector labels under each service system; traversing the business system quality map according to the to-be-retrieved business category to obtain a corresponding quality-effect index of the to-be-retrieved business category under each business system; and generating a quality evaluation result of the to-be-retrieved service category according to the corresponding quality-effect indexes of the to-be-retrieved service category under each service system. The objective of the invention is to solve the problems of low accuracy and low efficiency of quality evaluation in the prior art.

The invention relates to the technical field of artificial intelligence recommendation and data screening, in particular to a commodity recommendation screening method and model, and the method comprises the steps: collecting commodity detection, sales volume and user scene data, and constructing a multi-source data set; desensitizing the sensitive field by using a differential privacy algorithm to generate a privacy protection data set; establishing a three-dimensional dynamic collaborative scoring model, and calculating a commodity comprehensive fitness score; establishing a deviation analysis model in combination with the score and the sales volume, and identifying an overestimated / underestimated commodity; and updating the model based on the abnormal commodity data. The model comprises a multi-modal data acquisition and storage module, a differential privacy desensitization module, a three-dimensional dynamic collaborative scoring module, an abnormal associated commodity identification module and a model dynamic updating module, and collaborative landing of the method and the modules is realized. The problems that in the prior art, there is no system for commodity classification, the quality scoring dimension is single and is disjointed with the sales volume, the scoring is not dynamically adjusted, and data support is insufficient are solved.

The application provides a large model service quality three-system joint detection method and system, comprising: obtaining a model service instance of a to-be-detected large model, and based on a model type of the model service instance, loading applicable authenticity detection items, capability detection items and performance detection items from a versioned three-system detection directory; creating a one-time detection operation record, and under the constraint of the detection operation record, based on the authenticity detection items, the capability detection items and the performance detection items, synchronously executing authenticity detection procedures, capability detection procedures and performance detection procedures; based on a preset fusion strategy snapshot, fusing detection results of the authenticity detection procedures, the capability detection procedures and the performance detection procedures to generate a service quality evidence package. The application reduces audit misjudgment and judgment distortion caused by inconsistency of cross-reporting caliber.

The invention relates to the technical field of mechanical engineering and intelligent detection, discloses a data acquisition and quality management and control system for railway wagon axle detection, and aims to solve the problems that in the prior art, manual recording is prone to mistakes and omissions, data acquisition and quality judgment are disjointed, and closed-loop management and control cannot be achieved. The system comprises a commercial digimatic micrometer additionally provided with an external Bluetooth device, a portable small flat plate and a quality management system, a wireless transmission link is constructed through Bluetooth, and static size data is transmitted to the small tablet computer in real time and uploaded to the system; the quality system is additionally provided with a data receiving, checking and storing module, process standards are automatically compared, and abnormal data are visually identified. According to the technical scheme, automatic collection, real-time verification and abnormity early warning of high-precision static size data can be achieved, and the detection accuracy, efficiency and quality tracing ability are remarkably improved.