189 results about "Big data visualization" patented technology

The invention provides a power regulation big data analysis mining-based index system establishment method. The method comprises the following steps of I, classifying indexes; II, establishing an index tree; III, establishing an initial index system; IV, constructing application integration under a Web portal of a big data platform; and V, perfecting the index system. According to the method, a calculation formula, a calculation rule and calculation data of the indexes are automatically generated and stored in semi-automatic and semi-manual modes according to the calculation formula, the calculation rule and the calculation data of the indexes, so that the workload is reduced and the precision is improved; and based on an existing index system, a big data visual analysis mining technology is adopted, so that advanced and macroscopic new indexes are formed for perfecting the index system.

The invention belongs to the technical field of integrated pipe gallery engineering. Disclosed is a big data visualization system and method for an underground comprehensive pipe corridor. The big data visualization system of the underground comprehensive pipe corridor comprises a video monitoring module, an environmental data detection module, a central control module, a cloud service module, a device management module, a risk assessment module, an alarm module and a display module. The big data visualization system comprises a video monitoring module, an environmental data detection module,a central control module, a cloud service module, a device management module, a risk assessment module, an alarm module and a display module. The invention establishes an Internet of Things communication framework between the security, ventilation, power supply, drainage, lighting and fire fighting equipment in the pipeline corridor and the cloud server platform through a management module, utilizes the Internet of Things technology, and greatly facilitates the management of the operation and maintenance equipment. At the same time, through the risk assessment module, the invention can construct a comprehensive pipe corridor disaster chain Bayesian network model according to the evolution law of a plurality of potential disasters in the comprehensive pipe corridor, predict the occurrence probability of each disaster in the pipe corridor and evaluate the loss degree of the pipe corridor, thereby proposing a scientific and effective comprehensive pipe corridor pregnant source chain broken disaster reduction mechanism and measures.

The invention discloses a data view copy iteration method in a Web visual environment. The method comprises the following steps of S1, establishing a dynamic evolution model which comprises a big data user layer, a big data visual layer and a big data source layer; and S2, providing the data view copy iteration method in the Web visual environment based on the model. According to the data view copy iteration method in the Web visual environment provided by the invention, a visual result is materialized and cached; the updating efficiency of data views is improved through the copy iteration method; the search performance is prevented from being influenced by frequent updating; and the search cost of the data views is reduced. According to the method, in the Web environment with a relatively big search set and a relatively frequently updated data source, massive data can be searched rapidly and displayed visually, and the user currently accessing the data views is not influenced when the cache is updated.

The invention provides an air pollution tracing and trend prediction method with visual big data. The method comprises the following steps: using air diffusion conditions as input factors, and establishing a feedforward model for air pollution tracing and trend prediction by using a multilayer feedforward neural network trained by an error back propagation algorithm; and executing a learning process of the feedforward model, wherein historical air pollution data are used as the input training factors of the feedforward model, and gradually adjusting the weight and the threshold of the feedforward model of the network via the error back propagation by using the steepest descent method of an error performance function, so that the output errors of the feedforward model of the network are reduced continuously.

The invention provides a big data visualization three-dimensional GIS cloud rendering project generation system comprising a display device which is divided into a WEB version and a client version andis used for displaying a visualization design effect on a large screen, connecting real-time messages and supporting action event interaction and Internet of Things equipment linkage; a designer which is an efficient productivity tool based on visual editing; a remote controller which supports remote control of the display device through a handheld terminal; and a tool set. The invention furtherprovides a big data visualization three-dimensional GIS cloud rendering project generation method. The big data visualization three-dimensional GIS cloud rendering project generation method has the beneficial effects that big data can be continuously and fully used for data mining and analysis; the reusability is high; the big data visualization three-dimensional GIS cloud rendering project generation method is extremely easy to combine with the three-dimensional GIS; the configurability is high; the installation and deployment are simple; the remote control operation is humanized and convenient; and a large amount of time, manpower, material resources and financial resources are saved for users, so that the big data visualization three-dimensional GIS cloud rendering project generation method is easier to apply and popularize.

A marine observation big data visualization analysis method based on a complex network comprises the steps of performing grid division on original marine observation big data, constructing daily average data in a grid into a single Gaussian model and a mixed Gaussian model, and obtaining nodes represented by probability feature vectors; Determining the similarity between any two nodes in the single Gaussian network and the multi-Gaussian network to obtain a similarity matrix; And setting a threshold value to obtain an adjacent matrix, calculating the degree, the clustering coefficient and thenode betweenness of each node according to the adjacent matrix, and visualizing or drawing the degree, the clustering coefficient and the node betweenness on double logarithm coordinates or on a map.According to the invention, the Gaussian mixture model is combined with the complex network theory for the first time; The invention provides a marine observation big data analysis and visualization method, the fluctuation of ocean motion reflected on the data is restored to the maximum extent, and model parameters are used for expressing high-dimensional ocean data, so that the defect that a network model constructed on the basis of Pearson similarity can only measure time sequence data is overcome, and the calculation speed is also improved.

The invention discloses a visual method and system of social security big data. The technical scheme comprises the following steps: generating a pattern file through a feedback type interactive mechanism to improve the interactive instantaneity and friendliness; and meanwhile, improving the visualization efficiency through the predefinition of a chart and map template, a cache mechanism and an asynchronous transmission mechanism; furthermore, electing an idle server through a cloud server cluster to process a client request, thereby guaranteeing that the client request can be immediately and efficiently processed. The processing performance of a visual cloud server is sufficiently developed, and the performance bottle neck of the single server is overcome; and meanwhile, the repeated generation and redundant data transmission of the same visual results are avoided through the cache mechanism, the efficiency to the client representation from the visual generation is improved, thereby improving the visual efficiency of the data.

The invention discloses a big-data visualized analysis method and system based on an airline ticket booking platform. The method comprises the following steps of S1, integrating a data source of the airplane booking platform, and storing the integrated data to a data warehouse; S2, extracting data used for being analyzed from the data warehouse, and integrating the data into a wide table; S3, generating a dimensionality table according to the wide table; S4, conducting relevance on different dimensionalities to generate a displaying table in the wide table according to dimensionality information of the dimensionality table; S5, outputting the displaying table in a visualized graphics mode. According to the big-data visualized analysis method and system based on the airline ticket booking platform, the insufficiencies in the prior art are overcome that a data displaying scheme is simple and the data dimensionality is monotonous, which is to the disadvantages of integral analysis and finding of abnormalities of the airplane booking platform. Through the big-data visualized analysis method, massive complicated airplane booking platform data is sorted starting with different analysis topics, and is displayed in a concise, efficient and visual mode.

The invention discloses a big data visualization interaction system. The invention discloses a big data visualization interaction system which comprises a data visualization and administrator module,a big data storage, analysis and processing module, a structured data storage module and an SSM module. The big data visualization interaction system has the advantages that the big data visualizationinteraction system is the webpage big data visualization interaction system which mainly has the following beneficial effects that (1) the page is of a response type layout style, is automatically adapted to screens of various sizes, and is suitable for various large screen display scenes; and (2) the display mode can be dynamically modified according to the data change, and the method has a theme customizing function, is suitable for data visualization under various scenes, does not customize a design drawing for a specific service scene, and has relatively high expansibility.

The invention provides a graphical processing method for a visualized big data association relationship. The method and the device are characterized in that a simple, convenient and intuitive graphical operation interface is provided and enables a user to perform graphic association processing on existing data without programming foundation; the method and the device can be widely applied to data visual display and analyzing of each industry and help user to build own data self-service analyzing system. The method comprises the following steps: (1) acquiring data files which are selected by the user and are to be imported, wherein the data files are worksheets; (2) concretizing the worksheets into a plurality of entity graphs through the graphics technology of a web side, and marking the names of service objects on the entity graphs; (3) prompting the user whether to build data association while detecting that the entity graphs are directly impacted and overlapped; if so, carrying out step (4), and otherwise, carrying out step (5); (4) performing data association on fields, selected by the user, of each worksheet, storing, and then displaying an association link through an interface; and (5) finishing. The invention also provides a device.

The invention discloses an automatic search engine method and system based on network public opinion analysis, the system comprises a platform positioning analysis module, a public opinion analysis module, a theme screening module and a content pushing module, and the system can capture hotspot content according to customized keywords of a platform to complete content analysis of the system and anexternal platform; meanwhile, curves of propagation paths, operation data, emotional trends and the like of the content are displayed, and complete and scientific propagation analysis is displayed; by tracing the captured content, the source of the content is accurately tracked to realize accurate traceability analysis, and copyright protection is facilitated; through professional and intuitive big data visual display, a statistical report of the system is made according to large-screen display, so that a manager can perform data operation conveniently.

The invention discloses a Tableau-based synchronous line loss anomaly analysis method and system. with basic data information relates to power grid line losses as data input, Tableau visual analysis software is used, a cluster analysis method is applied to big data analysis, abnormal causes are analyzed, an abnormal point position is positioned, the line loss conditions of different units are compared transversely and analyzed, problem discovery is thus assisted, the problem law is found out, a line loss management process is optimized, and the efficiency is enhanced. Through mining the line loss anomaly data from the power grid basic information data, a line loss anomaly node is searched, a Tableau-based big data visual display mode is applied, transverse and longitudinal visual analysisis carried out on a synchronous quarter line loss condition, and auxiliary reference is provided for improving the management level of the power line losses.

The invention discloses a rapid application method and system of data visualization graphs. The rapid application method of data visualization graphs includes the following steps that visualization open-source components and visualization open-source tools are created in an open-source visualization technology; unified function and interface encapsulation is conducted on the open-source components to form a standard visualization graph library, wherein standard visualization graphs are stored in the visualization graph library; visualization analysis graphs are created according to the visualization open-source tools, and standardized encapsulation is conducted to obtain standard visualization graphs; unified encapsulation is conducted on all the standard visualization graphs to form a visualization graph component template library; capacity encapsulation is conducted on the visualization graph component template library to achieve rapid application of the visualization graphs. By means of the technical scheme, the difficulty of implementation of big data visualization graphs is greatly lowered, the application efficiency and effect of visualization graphs are improved, and the threshold of applying big data visualization by enterprises is lowered.

Some embodiments are associated with a big data non-relational database storing a substantial number of electronic files, including a set of values for a first parameter. A server may receive information from the big data non-relational database, and an initial transformation may be applied to the set of values for the first parameter resulting in a set of bucket containers, each bucket container storing information consolidating a plurality of values for the first parameter. A visualization transformation may then be applied to the bucket containers to create a set of pixel information to be transmitted to and rendered by a client platform.

The invention discloses a big data-based method and system for predicting the variable sliding time and relates to the field of civil aviation information. The method comprises the following steps: analyzing historical data in an airport collaborative decision-making system database, extracting flight departure operation data from the historical data, determining main influence parameters of flight departure, setting a weight value and dynamically adjusting a weight proportion; modeling by adopting a gradient boosting tree model to obtain a variable sliding time dynamic estimation model, inputting actual data of main influence parameters into the variable sliding time dynamic estimation model, estimating probability distribution of variable sliding time, and calculating an expected value;performing visual display on the variable sliding time. According to the method, the variable sliding time is intelligently predicted through manual prediction based on the constructed A-CDM system. The large-area flight delay is prevented and relieved through big data visualization auxiliary decision making.

The invention discloses a visualized topology platform layout method for big data ofan intelligent power grid. The method comprises the steps of acquiring the voltage level and routing characteristicsof preset equipment in the power grid; performing region division according to the voltage level and the routing characteristics, wherein divided regions include but are not confined to a main transformer region, a plurality of bus connection regions and a bus-free region; topological connection and feature abstraction and tailoring of various bus connection areas are divided into various types of components; and based on a multi-way tree algorithm, a main transformer area, arranging a bus-free area and various types of components. The power grid is constructed into a through interconnected big data visual topology platform, and a connection relationship is established among power grid equipment, regions, transformer substations and the like. By integrating operation data, power grid data, power market data and the like, big data analysis is carried out by utilizing a topological network, the operation efficiency of energy production and energy consumption terminals is improved and optimized, and requirements and supply can be dynamically adjusted at any time.