7 results about "Human error probability" patented technology

The invention relates to the technical field of computer software, in particular to a human factor reliability analysis method and device based on a cognitive mechanism, and the method comprises the steps: refining a target nuclear power plant operation instruction text into executable operation behavior units; modeling the executable operation behavior unit according to the cognitive psychology model to obtain an operation cognitive model; repeatedly running different preset operation tasks for multiple times by using the operation cognition model so as to quantify and estimate human factor event occurrence time parameters; and inputting the human factor event occurrence time parameter and a preset cognitive failure probability into a pre-constructed human factor reliability analysis model to calculate a human factor error probability. Therefore, the problems that in an existing IDHEAS-ECA method, human factor event occurrence time mainly depends on subjective expert judgment, cognitive mechanism support is lacked, result precision is limited and the like are solved, and the method is suitable for operator behavior modeling and human factor error probability estimation in high-risk industries such as nuclear power plants and the like.

The invention relates to the technical field of data analysis, in particular to an early stage automatic analysis method and device of a human error probability analysis system.The method comprises the steps that an early stage task of the human error probability analysis system is disassembled into a plurality of analysis subtasks; embedding expert knowledge on the basis of a prompt project, establishing an agent for each analysis subtask on a large language model, and realizing information transmission among a plurality of agents through a shared memory or an API (Application Program Interface) calling mechanism; early stage analysis of the human error probability analysis system is achieved through the multiple agents, and the multiple agents analyze the early stage task and the multiple analysis sub-tasks according to the analysis sequence. Therefore, the problems that in the prior art, the early stage of a human error probability analysis system depends on a large amount of manual judgment, and when the human error probability analysis system faces complex and changeable operation scenes, the analysis process is tedious and takes a long time are solved.

The invention discloses a software upgrading method and device and a related product. The jig for software upgrading is disclosed, the jig supports connection of a plurality of mobile storage devices and an entertainment host set comprising a plurality of entertainment hosts, automatic upgrading scripts in the mobile storage devices can be executed through the jig, and software to be upgraded is installed in the entertainment hosts at a time. The jig is convenient to carry and use, and software can be automatically and rapidly upgraded. And meanwhile, the installation state of each entertainment host can be obtained, and the successfully installed entertainment host is prompted to be replaced, or the entertainment host which fails to be installed is reinstalled. According to the method, manual intervention is reduced, the labor cost and the human error probability are reduced, and the harsh requirement for plugging and unplugging of the power wire harness when the entertainment host is replaced is avoided. Efficient and accurate software upgrading is achieved, the purposes of reducing cost and increasing efficiency are achieved, and meanwhile the method is suitable for the scene that software in the entertainment host is frequently upgraded.

The invention discloses a method for predicting the human error probability of each operation in the civil aircraft traction departure process, and the method comprises the steps: calculating the risk coefficient of each historical risk event type, screening a target risk event type, and screening a behavior formation factor according to the mapping relation with human error factors; obtaining a manual task and a general operation condition in an aircraft traction departure scene; and evaluating each behavior formation factor when each manual task is executed under the general operation condition through the expert group, obtaining the weight and the grade of each behavior formation factor, and calculating the human error probability of each manual task. The behavior formation factors are screened according to the mapping relation between the risk event types and the human error factors, and the human error probability of each human task is calculated through the expert group construction weight and level, so that the subjectivity problem can be avoided, the behaviors causing human errors are effectively identified, the risk assessment accuracy and management level are improved, and the risk assessment efficiency is improved. And the human reliability of the staff in the aspect of aircraft traction departure is improved.

The present application relates to the technical field of data analysis, in particular to a basic human error probability evaluation method and apparatus, a device, a medium and a product. The method comprises: acquiring target case information that needs to be analyzed; inputting the target case information into a pre-constructed multi-agent analysis framework, the multi-agent analysis framework outputting a multi-agent analysis result of the target case information; and, on the basis of a pre-constructed knowledge graph database and the multi-agent analysis result, generating values of a plurality of indicator parameters of a basic human error probability, and, on the basis of the knowledge graph database and the values of the plurality of indicator parameters, evaluating the basic human error probability for the target case information. Thus, the present application solves the problems of high dependence on expert knowledge, long evaluation time, low evaluation efficiency, etc. in the prior art.

A human-computer interaction system safety evaluation method oriented to a group collaborative task comprises the steps that the collaborative task is decomposed into a subtask sequence according to group collaborative task description, and the nominal task probability of each subtask is determined; according to the external performance formation factor and the nominal task probability, the basic human error probability of each subtask is obtained by referring to the behavior influence factor and the common performance condition weight table; judging the relevance level of the sub-task and the preorder task, and calculating a conditional human error probability based on the relevance level and the basic human error probability; integrating the conditional human error probabilities of all the sub-tasks, and calculating to obtain an initial joint human error probability of the whole task; quantizing and generating a time pressure intensity index, and correcting the basic person error probability and the conditional person error probability according to the time pressure intensity index; and based on the corrected basic human error probability and the corrected condition human error probability, recalculating the final joint human error probability of the whole task after time pressure correction, and evaluating the safety of the human and interaction system.

The application relates to a dynamic decision support method and device for human error in emergency response of high-risk industries, wherein the method comprises the following steps: identifying and classifying human errors in the execution process of emergency operation regulations; obtaining probabilities of different types of human errors; establishing a dynamic Bayesian network model of human factors in the emergency response process; obtaining a case database of human errors in the emergency response process according to the human error probabilities; and learning and updating parameters of the established dynamic Bayesian network model of human factors in the emergency response process. Thus, decision support is provided for preventing and controlling the skipping and execution errors of operators.