10 results about "Expert analysis" patented technology

The invention discloses a power generation equipment operation and maintenance large model fine tuning method and system based on non-stop analysis process restoration. The stepwise analysis process of'premise conclusion-contextual information-reasoning judgment 'is completely restored. Constructing a question-answer pair generation mechanism based on process restoration, and enabling the fine tuning data set to contain expert reasoning logic instead of fragmented knowledge; a LoRA fine tuning technology is combined, so that the big model simulates a thinking path of an expert to analyze a problem while learning professional knowledge, and the interpretability and migration ability of model reasoning are improved; the construction cost of professional question and answer pairs is reduced, existing operation and maintenance document resources are fully utilized, and the fine adjustment efficiency and practicability are improved.

The invention relates to the technical field of computer science and technology, and discloses a karst metal underground mine hidden disaster-caused water disaster risk evaluation method comprising the following steps: constructing a three-level evaluation index system of a karst metal underground mine comprising a target layer, a criterion layer and an index layer; analyzing the expert analysis risk level of the second-level index; correcting expert analysis risk levels to obtain membership degrees of the second-level indexes relative to different risk levels so as to construct a fuzzy relation matrix of the karst metal underground mine; calculating a first-level index weight of a first-level index corresponding to the criterion layer and a second-level index weight of a second-level index corresponding to the criterion layer, and performing fuzzy synthesis operation on the fuzzy relation matrix and the second-level index weight to obtain a first index risk probability of the first-level index; and performing fuzzy synthesis operation on the first index risk probability and the first-level index weight to obtain a comprehensive risk level corresponding to the target layer. According to the invention, the monitoring accuracy of major safety accidents caused by hidden water disasters can be improved.

The invention discloses an intelligent operation and maintenance monitoring system and method for a transformer, relates to the field of transformer monitoring, and aims to solve the problem that existing transformer matched monitoring equipment cannot perform comprehensive intelligent analysis and suggestion. The system comprises a real-time monitoring module and an intelligent safety evaluation module connected with the real-time monitoring module; the intelligent safety evaluation module is connected with an expert analysis module and a spatial digital twinborn construction module, and the real-time monitoring module and the expert analysis module are connected with a periodic management and control module. The cycle management and control module comprises an archive recording unit for recording the full life cycle of the transformer and an information construction unit for constructing full life cycle information according to the recorded archive; the invention further comprises a corresponding system. The transformer operation data and health state can be dynamically displayed and analyzed through the spatial dimension digital twinborn model, operation and maintenance personnel can find problems in time, and intelligent diagnosis and active operation and maintenance analysis of the transformer operation state are achieved.

This application relates to a method, apparatus, electronic device, and storage medium for detecting abnormal server behavior, applied in the field of network security technology. The method includes: real-time acquisition of system call sequences during server process execution; dividing the system call sequence into N runtime phase subsequences, and further dividing the runtime phase subsequences corresponding to the target process's runtime phases into process activity subsequences; segmenting the system call sequence into multiple unidentified subsequences; inputting each unidentified subsequence into a process semantic abstraction model to obtain the named entity recognition result corresponding to each system call in the unidentified subsequence; aggregating and overwriting the named entity recognition results of multiple unidentified subsequences to obtain the named entity recognition result corresponding to each system call in the system call sequence; if unidentified named entities are included, determining that the system call sequence is abnormal, and sending an alarm message. This application can extract process behavior, facilitating expert analysis of abnormal events.

This application discloses an event evolution reasoning and prediction method based on cognitive-driven intelligent generation. First, it utilizes a domain-wide language model to extract expert knowledge points, analysis processes, analytical perspectives, and logical reasoning from event research reports, constructing an interactive thought chain. It then extracts causal reasoning and constructs a causal reasoning network structure. Cognitive logical knowledge is integrated with relevant facts of the event to be predicted and embedded into a prompt template to construct a prompt model. This allows the domain-wide language model to generate event evolution reasoning and prediction results based on expert analysis dimensions and processes. Finally, conflict detection is performed on event elements through closed-loop evidence chain analysis, and credible conclusions are selected to obtain credible prediction conclusions. By constructing prompt templates to guide the large model through cognitive logical learning and combining multi-level credible verification and screening, the technical problem of excessive prediction errors caused by illusions generated by the large model is solved, improving the accuracy and credibility of event evolution prediction.

The application discloses a geomorphology professional question answering service method and system based on geomorphology features. The method acquires geomorphology documents through multiple channels and preprocesses to construct a standardized corpus, encodes text semantics into high-dimensional vectors using vector embedding technology, and then realizes semantic similarity calculation and retrieval based on vector distance measurement to construct a geomorphology knowledge vector database. The LangChain framework is combined to configure a geology expert system prompt template, simulate expert analysis thinking process, form a geomorphology large model, and provide geomorphology professional question answering services covering geomorphology feature, cause process and evolution mechanism interpretation for users. The application significantly improves the accuracy of geomorphology professional knowledge retrieval and the quality of question answering, and provides intelligent professional technical support for geomorphology research and education.

The invention provides a task template generation method and device based on reverse engineering, equipment and a medium. The method comprises the steps of obtaining an example document, analyzing the example document, extracting a plurality of text blocks, and associating visual layout metadata for each text block; constructing a document tree based on content semantics and visual layout metadata of the text blocks, and performing hierarchical clustering on text contents in the document tree to generate a logic step sequence; identifying named entities in the full text of the example document, replacing the named entities with parameterized variables, and generating a parameter mapping table based on the corresponding relationship between the parameterized variables and the named entities; according to the method, the logic step sequence is associated with the parameter mapping table, the task template is generated, the expert analysis normal form can be extracted from diversified documents in a robust mode, the highly reusable and parameterized task template is generated, the efficiency, the normalization and the intelligent level of research work are remarkably improved, and the method has wide application prospects in the field of knowledge automation.

The invention relates to an intelligent procurement risk prediction and abnormal behavior detection method. The method comprises the following steps: constructing a multi-dimensional procurement risk index system; the indexes are classified, and a quantitative scoring model and a Boolean judgment model are included; screening the indexes based on a feature importance algorithm; and based on a dynamic weighted aggregation model, fusing objective data and expert analysis suggestions, carrying out weight distribution and risk value calculation on the simplified index set, and outputting a comprehensive risk value of the purchase project. The bid invitation risk dynamic prediction method has the beneficial effects that the bid invitation risk dynamic prediction is realized by constructing a comprehensive algorithm, the actual benefits are reflected in multiple dimensions of risk prevention and control, efficiency improvement, cost saving, management optimization and the like, and a remarkable business value closed loop is formed.