22results about How to "Simple data structure" patented technology

The invention relates to the technical field of geological disaster intelligent monitoring, in particular to a geological disaster intelligent monitoring system and method based on multiple sensors. The method comprises the following steps: covering a monitoring area through multiple sensors, and collecting and summarizing environment data; separating effective signals and noise by adopting a space-time adaptive decomposition method, completing data denoising by combining a signal-to-noise ratio dynamic threshold and a local weighted regression smoothing trend residual error, then aligning time and dimensions through linear interpolation and standardization, and integrating multi-sensor data based on an adaptive weighted fusion method; the fused data is subjected to generation and review of a to-be-reviewed mark, so that the data integrity is ensured; key features are extracted, a mixed model based on LSTM and a random forest is constructed to evaluate disaster risks, and a risk grade division rule is set; and finally, outputting fusion data and an analysis result, and generating an early warning signal and a decision suggestion for potential geological disasters. According to the invention, accurate monitoring and risk assessment of geological environment changes are realized.

The invention provides an intelligent garden environment monitoring data analysis method and system. Sensors are deployed to collect temperature, humidity and other data in real time to form a data set. Analyzing an environment parameter change mode of each region by adopting a time sequence clustering algorithm, and determining characteristics and trends; and carrying out dimension reduction on the data by using a multi-dimensional scale transformation algorithm to a three-dimensional space for visualization, and generating an environment state map. And evaluating the plant fitness in combination with a plant physiological ecology knowledge base, and generating a scoring matrix to guide the preliminary layout scheme. And dynamically adjusting the layout by applying reinforcement learning, selecting an optimal scheme, and predicting a future environmental evolution path based on the optimal scheme and historical data. An automatic control system framework is constructed, a self-adaptive control algorithm is designed, intelligent regulation and control of plant layout are realized, garden management efficiency is improved, and ecological protection and sustainable development are promoted. Therefore, full-chain intelligent management from environment monitoring to plant layout optimization is realized, and the intelligent level of garden environment monitoring and management is remarkably improved.

The invention relates to the technical field of charging load prediction, in particular to an electric vehicle charging load prediction method and system combining sequence decomposition and feature extraction and a storage medium. Comprising the steps of performing variational mode decomposition on time sequence load data to obtain a plurality of intrinsic mode functions; performing zero padding expansion on each intrinsic mode function, and then converting the intrinsic mode function to a frequency domain; enhancing the frequency domain data through a multi-layer perceptron based on complex domain calculation; constructing a prediction model based on a complex field attention module and a residual module, inputting the enhanced spectrum data into the prediction model, extracting a data characteristic frequency combination through the complex field attention module and the residual module, and carrying out weighted summation on all intrinsic mode functions as the output of the prediction model; and calculating a difference value between real data and prediction data according to a mean square error of a time sequence and an average absolute value error of a frequency spectrum to obtain time domain and frequency domain mixed loss, and updating prediction model parameters. According to the invention, the problem of large prediction error under the influence of random load fluctuation is solved.

The invention relates to the technical field of cable safety, in particular to a cable repairing method based on hierarchical path planning and related equipment, and the method comprises the steps: obtaining an original point cloud of a target cable, carrying out the preprocessing of the original point cloud, and obtaining a damaged region point cloud; according to the method, the damaged area point cloud is subjected to voxelization processing, the damaged area point cloud subjected to voxelization processing is subjected to internal voxel filling, the zigzag path of the target cable is generated according to the voxelization damaged point cloud, the target cable is repaired based on the zigzag path, the method can adapt to the complex form of the damaged area, and the repairing integrity and the repairing quality are improved.

The invention relates to a business data processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of obtaining a fission sharing path and initial user information of service data, wherein the fission sharing path comprises multiple pieces of fission user information and a data sharing mode between users; constructing a graph network model of the service data according to the information of the multiple fission users and the data sharing mode; screening fission user nodes of the graph network model according to the initial user information to obtain an initial node; constructing a directed propagation path of service data according to the out-degree of the initial node and a node connection relationship between fission user nodes; and if the number of the nodes in the directed propagation path is not less than a preset fission threshold, generating fission sharing information of the service data according to the directed propagation path. By adopting the method, the data structure can be simplified, and the data volume can be compressed, so that the fission sharing information generation efficiency is improved.

The invention discloses a method for predicting the gelation activity of alkali-activated tailings and the strength of concrete prepared from the alkali-activated tailings based on machine learning, and the method comprises the following steps: collecting heat flow data of typical alkali-activated tailings, and converting the heat flow data by using Fourier transform and discrete cosine transform functions; and establishing a prediction model of the gelling activity of the alkali-activated tailings and the strength of the tailings-based concrete based on a machine learning model. Compared with a traditional concrete strength prediction model, the method has the advantages that the hydration dynamic data of the alkali-activated tailings are converted, nonlinear features can be remarkably reduced, a data structure is simplified, and a machine learning model can traverse all data, so that the prediction model has higher prediction precision and reliability.

The invention belongs to the field of software simulation, and particularly discloses a CAE software construction method, system and equipment, and the method comprises the steps: determining a simulation scene which needs to be supported by the current version of CAE software, so as to determine a function which needs to be supported by the current version of CAE software; determining a plurality of sub-function modules needing to be added in the CAE software according to the functions needing to be supported; constructing at least one sub-function module in the plurality of sub-function modules by adopting a data-oriented software design architecture; after the plurality of sub-function modules are constructed, completing iteration of the CAE software of the current version to obtain CAE software of an updated version; the CAE software of the updated version supports the simulation scene. Through the method and the device, the problems of software complexity and performance caused by coupling of a plurality of functional modules in a CAE software architecture are solved, so that the development efficiency of CAE software is improved, the software quality and the execution performance are improved, and the simulation experience of a user is improved.

The embodiment of the invention provides a table data processing method and device, equipment, a medium and a product. The method comprises the steps of displaying at least part of records of a target table in a target interface of a client in response to a data access request which is input by the client and aims at the target table; the record refers to a row of data in the target table; receiving a sub-record editing operation for the target table through the target interface, determining hierarchical description data corresponding to the edited sub-record according to the sub-record editing operation, and updating display data of the target table in the target interface according to the hierarchical description data; the hierarchical description data is used for describing child records in the target table and father-child relation data corresponding to father records containing the child records. According to the technical scheme provided by the embodiment of the invention, the records of the table can be loaded as required, the changed records can be quickly and effectively updated in a targeted manner, and the processing efficiency and the use experience of the table are improved.

The invention discloses a CityMaker-based Revit model batch integration method and device, a storage medium and equipment. The CityMaker-based Revit model batch integration method comprises the following steps of S1, creating a target model; s2, combining element classes of single source models; s3, establishing a configuration file for batch integration of the models; and S4, integrating the source model into a target model. According to the method, data structure simplification from the Revit model to the FDB model, directional automatic replacement and integration from the source FDB model to the target FDB model, optimization of the integrated FDB model, batch conversion from the attributes of the Revit model to the attributes of the FDB model, and batch automatic calculation of the spatial index and the spatial range of the FDB model can be realized. According to the method, idle computer resources can be fully utilized, the model integration time is greatly shortened, and the model integration efficiency is effectively improved.

The invention discloses a webpage content structured processing method, device and system and a storage medium, and relates to the technical field of webpage content processing. The method comprises the following steps: acquiring a template URL, and requesting a URL address to obtain a first HTML tag; the method comprises the following steps of: analyzing and converting a Document object into a Document object, and extracting an Elements object set; removing non-analytic labels to obtain a filtered Elements object set, performing circulation, and setting a CurrentId value; a Tag object is defined, and Listlt is assembled; taggt is carried out; gathering: constructing a tree structure object; through an optimization method of reducing node depth and integrating nodes, the tree structure is further simplified, and the target of extracting the structured data from the webpage and storing the structured data into the database is achieved. According to the embodiment of the invention, the complexity of data extraction is simplified, the efficiency of data extraction is improved, the occupation of a storage space is reduced, and the learning cost and the use threshold of a user are reduced.

The present invention provides a method, device, system and storage medium for processing unstructured data, the method comprising: reading unstructured data to be processed and paragraph configuration information; segmenting the unstructured data to obtain paragraph data; calling corresponding verification rules to verify the paragraph data according to the paragraph configuration information to obtain parsed target data; storing the target data in a database. Thus, the unstructured data can be segmented, simplifying the parsing process of the unstructured data to form a simple and unified data structure, facilitating the editing of the unstructured data, thereby improving the reusability and extensibility of the code.