671 results about "Database construction" patented technology

The invention discloses a polyethylene plastic hollow plate defect detection method and system, and relates to the technical field of nondestructive testing, the system is composed of a plurality of functional modules, and the system comprises: a multi-mode sensing module for collecting multi-source data including a hollow plate surface image, three-dimensional morphology data and an ultrasonic reflection signal; the historical database construction module is used for performing space-time alignment and feature level fusion on the multi-source data to generate a composite defect feature matrix; collecting ultrasonic signal waveforms of known defects, extracting characteristic parameters, and establishing a historical waveform library; calculating a characteristic parameter classification range of each type of defects based on a historical waveform library; judging whether the detection waveform parameter falls into a classification range corresponding to the processing noise or not, and if so, rejecting the signal; otherwise, keeping; and the defect area identification module is used for dividing the surface of the hollow plate into uniform grids based on the surface image of the hollow plate, and counting the density of the residual ultrasonic detection sources in each grid.

The invention provides a carbon database construction method and system based on regional energy carbon emission prediction, and the method comprises the steps: eliminating the space-time reference deviation of an original data set, and generating an energy activity hologram spectrum with a unified space-time label; inputting the energy activity holographic spectrum into a non-linear correlation program, extracting a carbon release intensity characteristic curve of each energy carrier through a self-adaptive weight distribution mechanism pre-stored in the non-linear correlation program, and constructing a spatial-temporal characteristic network in combination with industrial operation cycle parameters and climate response factors in a target area; the spatial-temporal characteristic network establishes a dynamic coupling relationship between an energy flow mode and a carbon emission hot area to form a carbon emission associated topological structure with a self-organizing characteristic; a three-dimensional carbon database is formed, and the three-dimensional representation and deduction capability of space-time evolution of carbon emission is realized. The system comprises an atlas generation module, a structure construction module and a content fusion module. According to the invention, normal form transformation from static carbon accounting to dynamic carbon metabolism simulation is realized.

The invention belongs to the technical field of aviation energy design, and particularly provides an aviation energy power device fault intelligent inquiry system and method based on a knowledge graph. The method comprises the following steps: firstly, showing a complex data structure and a knowledge relationship to a user in a visual and dynamic manner through knowledge extraction, knowledge graph database construction, knowledge graph visualization and other methods, and constructing a knowledge graph basic framework; according to the method, the depth information of the target object can be extracted from the images from different angles, the fault characteristics of the equipment can be intuitively displayed, and the fault state of the equipment can be visually represented by extracting the depth information of the target object from the images from different angles. The evolution of the equipment state can be tracked through the change of the three-dimensional space; a conversion algorithm of the knowledge graph and the Bayesian network is realized through the Bayesian network, and rapid reasoning of fault causes is realized in combination with a Bayesian network reasoning algorithm; and finally, based on an intelligent inquiry system of a large model, a deep learning technology and a large-scale training model are utilized, and previous fault data and professional knowledge of the aviation energy power device are combined to provide intelligent auxiliary diagnosis support.

The invention relates to the technical field of database construction, in particular to a construction method and system for a reproductive medicine database. The method comprises the following steps: acquiring a biological tissue sample of a patient; acquiring reproductive endocrine hormone data, embryo morphological parameter data, immune cell function data and genome variation data from the biological tissue sample of the patient; performing time sequence analysis processing on the hormone fluctuation mode according to the reproductive endocrine hormone data to obtain endocrine dynamic characteristic data; performing image recognition processing based on coherent superposition characteristics of light on the embryo morphological parameter data, and performing embryo development potential evaluation to obtain embryo development potential data; and performing hierarchical clustering processing on the individual heterogeneity of the patient according to the immune cell function data and the genome variation data to obtain immune-genetic typing data of the patient. By means of the quantum dot sensing technology and the multi-channel micro-fluidic chip, standardization of data acquisition is achieved, and the heterogeneity problem of a data source is solved.

The invention relates to the technical field of dredge pump performance analysis, and discloses a numerical simulation and model test-based dredge pump performance analysis method, which comprises the following steps of: planning an analysis process, and determining numerical simulation (dredge pump internal flow field simulation) and model test contents (actually measured performance data under different working conditions); determining working condition types according to design parameters and working conditions; generating a performance analysis process set and determining an execution sequence; generating a simulation parameter setting list and a test scheme list of each working condition; and associating the data to generate an overall scheme. The method further relates to working condition analysis boundary determination, working condition type subdivision, dynamic adjustment of the process, test rule optimization, database construction and the like. According to the method, comprehensive and accurate analysis of the dredge pump performance is achieved through multi-dimensional data integration and a dynamic mechanism, the analysis efficiency and reliability are improved, and the method is suitable for evaluation and optimization of the dredge pump performance.

The invention relates to a smart city planning monitoring system, which comprises a multi-source data acquisition module, a database construction and management module, a planning analysis and monitoring module, a communication cooperation module and an interactive decision support module, the database construction and management module is used for constructing and managing a database of urban planning and monitoring data, the planning analysis and monitoring module is used for planning scheme evaluation and progress tracking, the communication cooperation module is used for data communication and module cooperation, and the interactive decision support module is used for data interaction, monitoring visualization and decision support. According to the smart city planning monitoring system, a city planning multi-source data fusion algorithm based on kernel density analysis is put forward to fuse multi-source data, and a smart city planning monitoring algorithm based on analytic hierarchy process and fuzzy comprehensive evaluation is put forward to monitor and evaluate smart city planning.

The invention provides a traditional Chinese medicine intelligent health diagnosis system and method based on multi-source data fusion, and relates to the technical field of health diagnosis. The system comprises a database construction module which is used for collecting condition data and historical disease data of a patient and constructing a traditional Chinese medicine holographic health database. And the multi-dimensional classification module is used for establishing a multi-source data classification standard and adding category fields to the multi-source data in the traditional Chinese medicine holographic health database from multiple dimensions to obtain associated field data. The importance classification module is used for constructing an importance degree judgment standard and judging the importance degree of different associated field data to obtain importance labels, and the exclusive customization module is used for classifying health states according to different importance labels to obtain current health data and formulating exclusive treatment strategies. According to the method, the data are classified and associated from multiple dimensions, the organization and utilization efficiency of the data is improved, and the importance degree judgment method can provide a basis for priority processing and analysis of the data.

The invention relates to a knowledge graph question-answering method and system based on a large language model. The method comprises the following steps: constructing a large language model framework and finely adjusting training data; finely adjusting the large language model based on LoRA; sub-graph retrieval and knowledge graph database construction; and large language model reasoning and answer generation. By using an innovative scheme of combining the large language model and the knowledge graph, the accuracy, flexibility and reasoning ability of the system can be remarkably improved by combining the strong semantic understanding ability of the large language model and the structured knowledge of the knowledge graph, the limitation of the intelligent question-answering system in processing complex and changeable problems is solved, and the intelligent question-answering system is more intelligent. Especially in scenes needing cross-domain reasoning and background knowledge support, the method can adapt to wider fields and application scenes.

The invention discloses an MES (Manufacturing Execution System) login authentication method based on a face recognition technology, which relates to the technical field of industrial information security, and comprises the following steps of: constructing an authentication data acquiring a face image of an authorized user of an MES, extracting a reference face feature template after preprocessing, and constructing the authentication database; performing associated storage on the reference feature template, user identity information, preset operation authority and affiliated production station information to form an authentication database; according to the method, spoofing attacks are prevented through multi-mode living body detection, and the problem that a traditional password / key is easy to leak and borrow is solved in combination with uniqueness of human face biological characteristics; a person-post-terminal binding mechanism further limits permission abuse, and internal operation risks are reduced; the non-contact authentication does not need to memorize a password or carry a physical key, and is suitable for a working scene that a workshop operator wears gloves and holds tools; and the recognition passing rate in a complex industrial environment is improved through dynamic threshold optimization.

The invention relates to the technical field of data information extraction, in particular to a bidding document qualification information intelligent extraction method based on a knowledge graph and hybrid retrieval, which comprises the following steps: a document preprocessing and partitioning step: preprocessing and partitioning a bidding document to obtain a plurality of document blocks; a vector database construction step: vectorizing the document blocks, storing the vectorized document blocks into a vector database, and constructing an index; a knowledge graph construction step: extracting triads from the document blocks, writing the extracted triads into a graph database to construct a knowledge graph, and constructing an index; a mixed retrieval step: carrying out mixed retrieval in combination with the knowledge graph and the vector database; a qualification information extraction step: taking the plurality of document blocks returned by mixed retrieval and the corresponding knowledge graph sub-graphs as contexts, and enabling an Agent agent to perform extraction based on the contexts and an extraction template; and finally, structured qualification item information is output. According to the method, high-quality structured extraction of the qualification information in the bidding document can be realized.

The invention belongs to the technical field of medical imaging and digital twinning, and discloses a thoracic cavity whole organ system level lung four-dimensional EIT detection digital motif and a library building method, and the method comprises the following steps: S1) segmenting multiple organs such as double lungs, heart, sternum, rib and thoracic vertebra central axis skeleton, main bronchus and esophagus based on an individual CT image, and building a three-dimensional geometric model integrated with an EIT electrode array; s2) simulating breathing dynamic deformation by using a solid mechanical model; s3) establishing a coupling relationship between deformation and conductivity, and generating dynamic three-dimensional conductivity distribution; s4) solving an electromagnetic field positive problem, and generating a virtual EIT voltage database synchronous with respiration; the invention also covers pathological model integration and data enhancement strategies. According to the method, a high-fidelity, large-scale and diversified EIT virtual data set can be generated, core data support is provided for training and verifying an AI intelligent reconstruction algorithm, and a model foundation is laid for developing a lung function dynamic digital twinning system.

The invention discloses a sewage data management system and method based on kitchen garbage treatment, and relates to the technical field of data management. The system comprises a data acquisition and historical database construction module, a correlation analysis and dynamic response rule construction module, a sewage data trend pre-judgment module and an operation regulation and data updating module. The data acquisition and historical database construction module is used for acquiring garbage treatment load and sewage data and constructing a historical database covering time period fluctuation and seasonal periods; the correlation analysis and dynamic response rule construction module constructs a dynamic response rule and determines the time delay duration; the sewage data trend pre-judging module is used for acquiring load data in real time and pre-judging a future sewage change trend; and the operation regulation and data updating module adjusts parameters of the sewage treatment system, collects effluent data to construct a new sample, supplements a database and updates a dynamic response rule. According to the invention, accurate sewage data management is realized, and the operation efficiency and stability of the sewage treatment system are improved.

The invention belongs to the technical field of composite material design, and discloses a polyimide-based composite material design method and system based on experiment-machine learning collaborative optimization. The method comprises the following steps: S1, experimental database construction and machine learning performance modeling; S2, machine learning model construction and training; S3, model evaluation and performance index output; and S4, intelligent design of the polyimide-based composite material. The multi-objective performance collaborative optimization design and preparation of the polyimide-based ternary carbon heterostructure composite material are carried out by taking experimental data as a main material and machine learning as an auxiliary material. According to the method, an experiment-model-optimization closed-loop iterative design system is constructed based on an experiment-machine learning collaborative optimization method, the method has the advantages of high prediction precision, high optimization efficiency, good multi-target adaptability and the like, the development efficiency of the polyimide-based composite material is remarkably improved, and the development cost of the polyimide-based composite material is reduced. The method is suitable for intelligent design and large-scale application and popularization of the high-performance heat-conducting electromagnetic shielding material.

The invention relates to a knowledge graph-based teaching resource database construction method and system, and belongs to the technical field of data resource processing, and the method comprises the following steps: S1, obtaining and preprocessing a multi-source heterogeneous teaching resource: carrying out the natural language processing of an unstructured text to recognize the association of an entity and a key concept, analyzing the user behavior log to extract hidden knowledge point association; s2, defining a multi-dimensional teaching knowledge graph mode layer: constructing a multi-dimensional graph mode layer; s3, collaborative extraction and fusion of graph entities and relationships: collaborative extraction of core teaching entities and specific relationship types from the preprocessed teaching resources to construct a knowledge graph; s4, adaptive graph updating and teaching path generation: taking the constructed knowledge graph as an underlying database, and responding to knowledge state query of a user; the method has the beneficial effects that massive and heterogeneous teaching resources and the knowledge graph are effectively fused.

The invention relates to the technical field of commodity visual identification, in particular to a vending cabinet commodity visual identification system based on a machine learning model, which comprises a feature extraction module used for determining position information of a target identification commodity, shooting a picture of the position of the target identification commodity to obtain a commodity image, and performing feature extraction on the commodity image to obtain a feature extraction result; constructing a target identification commodity feature network; the database construction module is used for collecting the feature information and the mutual relation of each commodity in the vending cabinet, processing the feature information and the mutual relation of each commodity, and storing the processed feature information and the mutual relation to a feature database; the matching identification module is used for establishing an association relationship between the image feature information association network and the standard feature information association network, determining feature information matched with the target commodity feature information from the feature database, and determining an identification result of the target commodity based on the commodity corresponding to the feature information, the method can achieve the accurate and efficient recognition of the commodities in the vending cabinet.

The present invention discloses a rule-based automated data governance system and method, and relates to the technical field of data management. The system of the present invention includes: a historical data analysis and rule base construction module, a real-time demand analysis and demand determination module, a data governance simulation and effect evaluation module, and a data governance rule adjustment and application module; the historical data analysis and rule base construction module collects and analyzes historical business demand information and historical data, and constructs a data governance rule base; the real-time demand analysis and demand determination module obtains real-time business demand information and data to be governed, and determines whether it is new business demand information; the data governance simulation and effect evaluation module performs data governance simulation on new demands based on historical data governance rules, and evaluates the data governance effect; the data governance rule adjustment and application module outputs adjustment suggestions according to the evaluation results, supports personnel to adjust and apply real-time data governance rules, and optimizes the data governance process.

The invention discloses a Chinese character structure and geometric space interactive writing method, which relates to the technical field of interactive writing methods, and comprises the following steps: carrying out geometric classification processing on Chinese characters by adopting a structural analysis method to obtain a Chinese character type set comprising a left-right structure, an up-down structure and a surrounding structure; carrying out geometric rule definition processing on the obtained Chinese character type set to obtain a geometric constraint rule base containing component proportion, gravity center alignment and stroke topological relation; performing structured storage processing on the obtained geometric constraint rule base by adopting a database construction method to obtain a dynamically-called Chinese character writing template database; the writing process of the user is monitored in real time, and a writing feature data set containing stroke coordinates, writing speed and pressure data is obtained; performing matching processing on the obtained writing feature data by adopting a dynamic grid generation method to obtain a self-adaptive reference grid corresponding to the currently written Chinese character; and carrying out deviation detection processing on the obtained self-adaptive reference grid by adopting a computer vision method.

The invention relates to a product carbon footprint basic database construction method. According to the method, government supervision data, enterprise live-action data and industry standard data are integrated, a carbon footprint model of a production stage and a full life cycle is constructed in combination with a life cycle evaluation method, data cleaning is performed on original data, carbon footprint factors are graded and dynamically updated based on an energy efficiency level, and a carbon footprint model is obtained. Accurate calculation of industrial chain carbon footprint factors, effective integration of multi-source heterogeneous data and dynamic iteration of a database are achieved, the problems that an existing database is insufficient in regional representativeness, poor in timeliness and low in technical transparency are solved, and finally a localized carbon footprint basic database which is comprehensive in coverage, traceable and compatible with international standards is established. And reliable data support is provided for carbon accounting and international trade barrier coping.

The invention discloses a CKD special disease database construction method and system, and relates to the technical field of database construction, and the method comprises the steps: obtaining and predicating a multi-source heterogeneous atomic fact; constructing and fusing three sets of ontology models; verifying and deducing facts in a layered manner according to a multi-layer priority rule base; calling a constraint completion engine to generate inference facts for missing or conflicting fields; streaming follow-up visit, test and intervention logs into events and triggering graded alarms; an anti-fact intervention scene is simulated for the high-risk patient, and pilot groups are screened; dynamically evaluating and adjusting the rule priority; and based on a causal chain and an event mode, clustering patients and constructing a generality map, and recording a whole-process operation chain. Semantic management is realized through fusion of ontology, anti-fact intervention simulation is performed on high-risk patients by means of multi-layer rule verification, and database semantic consistency, reasoning depth, decision support and traceability are improved through causal atlas driven clustering.

An indoor fire source positioning method based on an infrared thermogram of the outer surface of a glass curtain wall comprises the following steps: database construction, which mainly comprises construction of a fire data set, temperature distribution of the outer surface of the glass curtain wall, and image extraction and processing; a Resnet deep learning model is constructed and trained; and carrying out fire source positioning by using a Resnet deep learning model. In the early stage of fire disaster development, when fire behavior reconnaissance of a super high-rise building fire disaster is carried out, a reconnaissance unmanned aerial vehicle carrying an infrared thermal imager is controlled to fly out of a glass curtain wall of a fire floor, and the position of the reconnaissance unmanned aerial vehicle is adjusted to obtain a complete glass curtain wall outer surface infrared thermal image of the fire floor; an infrared thermal image of the outer surface of the glass curtain wall acquired by the thermal infrared imager is input into the trained Resnet-50 deep learning model, the model analyzes the infrared thermal image to give a position number of a fire source, the position of the fire source can be accurately recognized in the early stage of fire development, the real-time performance and reliability are high, and the fire early warning capacity and rescue efficiency of the super high-rise building are improved.

The invention relates to the technical field of intelligent recruitment management, and discloses an intelligent matching recruitment management system based on a large model. The system comprises a talent database construction module which collects multi-dimensional ability characteristics of job seekers and enterprise post demand data and generates a three-dimensional recruitment data set containing ability, post and time dimensions; the personnel post adaptation field modeling module performs dynamic integrating degree analysis on the data set, constructs a three-dimensional personnel post adaptation field, and identifies adaptation field critical point distribution and a flowing path; the key feature screening module extracts core adaptive features meeting a threshold value; the large model matching engine module inputs the core adaptive features into a pre-training large model generator, introduces adaptive field topology and feature continuity constraints, and outputs optimized dynamic adaptive field distribution; the environment variable compensation module fuses the dynamic indexes of the labor market to generate compensation parameters, and corrects the core adaptation features; and the strategy generation module generates a post matching strategy set and a talent optimization path to adapt to the requirements of the recruitment market.

The invention discloses a high-speed rail vehicle body aluminum alloy material corrosion fatigue performance simulation method and system, and belongs to the technical field of material corrosion fatigue testing. The method comprises the following steps: acquiring multi-source data of a high-speed rail body aluminum alloy material on an actual service route; establishing a material corrosion conversion coefficient database; obtaining an equivalent mapping relation based on the service environment and the load input set; generating a laboratory equivalent accelerated environment spectrum; and executing the laboratory equivalent accelerated environment spectrum, obtaining material failure data, and if the comparison difference is not less than a preset threshold value, correcting the calculation parameters of the equivalent mapping relation and regenerating the spectrum system. Through synchronous acquisition and fusion analysis of the multi-source environmental data and the mechanical load and in combination with the corrosion conversion coefficient database construction and closed-loop verification optimization method, the problem of test result distortion caused by separation of a laboratory simulation environment and an actual service condition in the prior art is solved.

The invention belongs to the technical field of composite material design, and discloses a polymer composite material design method based on LLM knowledge database construction and reasoning optimization, and the method comprises the following steps: S1, target performance setting; s2, constructing a knowledge database; s3, constructing a reverse design model; s4, constructing a performance verification module; and S5, performing multi-round test-verification design loop optimization. According to the method, an intelligent design method integrating target setting, semantic knowledge database construction, a design assistant, a performance verifier, a prompt engineering module and a language model material knowledge system is provided, closed-loop reasoning and feedback of structure-mechanism-performance are achieved through multiple rounds of DA-VM collaborative optimization, and the design efficiency is improved. The method has the advantages of high design efficiency, strong structure generation rationality, accurate performance prediction, knowledge evolvable and the like, and is suitable for intelligent rapid development of the high thermal conductivity-wave absorbing-shielding-mechanical integrated functional polymer composite material.

The invention relates to a diabetes management system, equipment and a medium. The method comprises the steps that a data processing module collects multi-modal medical data, dynamic time sequence features are extracted through a graph neural network to label semantic tags, and a structured patient information data set is formed; in the database construction module, a data fusion unit performs cross-modal feature alignment, redundancy elimination and feature enhancement on the structured data set, and establishes a dynamic and unified health record database; and the risk assessment unit extracts individual features by adopting an improved random forest algorithm based on the database, and generates a personalized health risk assessment report. And the health management module customizes a health management scheme through a generative adversarial network according to the evaluation report, and dynamically updates intervention measures according to real-time monitoring data. By adopting the system, the accuracy and individuation degree of risk prediction can be improved, accurate and dynamic whole-cycle health management service is provided for diabetics, and the management efficiency and the medical quality are effectively improved.

The invention relates to the technical field of electronic component data processing, in particular to a database construction method and system based on electronic components. The method comprises the following steps: carrying out component information acquisition through an electronic component transaction platform to obtain an original component data set; performing component relation mapping construction according to the original component data set to obtain a component association graph; performing multi-dimensional attribute extraction on the component association map to obtain component attribute vectors; performing component similarity calculation and clustering analysis according to the component attribute vector to obtain a component cluster; and extracting pin information according to the component cluster to obtain a cluster pin data set. According to the method, multi-dimensional condition screening, sorting and result explanation are realized, an accurate, reliable and easily understood component replacement recommendation scheme is provided for a user, the user is helped to quickly find a proper component, and the electronic design efficiency is improved.

The invention discloses an unknown pathogenic microorganism identification and analysis system and method based on nanopore sequencing. Comprising the steps of microorganism database construction and updating, microorganism information standardization labeling, nanopore sequencing analysis, sequencing data quality control, host sequencing read segment removal, microorganism database comparison annotation, congeneric sequencing read segment assembly and microorganism database comparison calculation. For each representative sequencing read segment, calculating and comparing the representative sequencing read segment with any genome sequence in the microorganism database, when a first calculation and comparison condition is met, outputting that the representative sequencing read segment is consistent with the species to which the genome sequence meeting the first calculation and comparison condition belongs, and when a second calculation and comparison condition is met, outputting that the representative sequencing read segment is consistent with the species to which the genome sequence meeting the first calculation and comparison condition belongs. And outputting that the representative sequencing read and the species to which the sequence meeting the second calculation comparison condition belongs are in a homologous relationship, and when the representative sequencing read and each sequence in the microorganism database do not meet the two conditions, outputting that the representative sequencing read is not compared in the microorganism database.

The invention provides an information compression and pruning RAG database construction method. The method comprises the implementation steps that node objects and a hierarchical clustering tree are constructed; compressing the node object text information in the clustering tree; and pruning the clustering tree after the partial node object text information is compressed based on a QR-like decomposition method. According to the method, the sentence unit text information in the sub-nodes in the clustering tree is compressed, the embedded vectors of the compressed sub-nodes are updated, and the most valuable external information can be screened and stored according to the actual requirements of the large language model, so that invalid data storage in an RAG database is reduced, and the reliability of the RAG database is improved. According to the method, text information stored in the RAG database is guaranteed to have gain all the time, meanwhile, pruning is carried out on a clustering tree obtained after partial node object text information is compressed based on a QR-like decomposition method, redundant child node objects with high semantic similarity are effectively recognized and deleted, and the storage overhead of the node objects in the RAG database is reduced.

The invention relates to the technical field of data processing, and discloses an HTAP database construction method and device, equipment and a medium, which can select a plurality of interested target column names and a plurality of target row records from a plurality of column names and a plurality of row records stored in an initial row storage table. And creating a proxy key index column in the initial row storage table, and in the proxy key index column, starting from a preset initial proxy key index identifier, allocating progressive increasing and continuous proxy key index identifiers to each target row record to obtain a target row storage table. And for any target column name, creating column data corresponding to the target column name according to the target column name and each proxy key index identifier. And creating a target column storage table according to each target column name and the corresponding column data. A hybrid transactional processing and analytic processing HTAP database is created that includes a target row store table and a target column store table. According to the database created by the method, the column data query efficiency can be improved based on the target column storage table.

The invention discloses a compound structure identification database construction method, system and device and a medium, and the method comprises the steps: inputting a model training data set into a plurality of retention time prediction models for training, and obtaining a plurality of trained retention time prediction models; verifying the plurality of trained retention time prediction models by adopting a model verification data set, and selecting an optimal retention time prediction model; inputting the migration training data set and the migration verification data set into the optimal retention time prediction model for migration learning to obtain a target retention time prediction model; inputting to-be-predicted compound structure data into the target retention time prediction model for prediction to obtain predicted retention time; and constructing a compound structure identification database according to the predicted retention time. The data in the compound structure identification database can be perfected, and the accuracy of the compound structure identification database is improved, so that the database performance is improved.

The invention discloses a database construction method for identifying cunninghamia lanceolata germplasm resources and application, and belongs to the technical field of biological breeding. The invention discloses a database construction method for identifying cunninghamia lanceolata germplasm resources. The method comprises the following steps: 1) collecting data; 2) data standardization processing; 3) designing a database; 4) creating a database; 5) algorithm integration; 6) establishing a database website; and 7) inputting, updating and maintaining data. The database for identifying the cedarwood germplasm resources comprises a cedarwood germplasm resource data management module, a picture management module, a data analysis module and a user management module. The result of the embodiment shows that the database is suitable for genetic diversity analysis, principal component analysis and comprehensive evaluation of the cunninghamia lanceolata germplasm resources.