72 results about "Real-time web" patented technology

The invention relates to the technical field of audio playing optimization, and discloses a low-delay multi-room audio playing optimization method and system, a storage medium and equipment, and the method comprises the steps: building a global time synchronization system based on a precision clock protocol in a playing equipment cluster, and enabling all playing equipment to operate based on a unified time reference; monitoring network state parameters in real time, dynamically calculating and adjusting the audio buffer depth of each playing device based on the monitored network quality, and obtaining audio data in advance according to the playing progress and the network state; generating a global playing timestamp according to the global time synchronization system, and controlling all playing devices to perform synchronous starting and progress control of audio playing based on the global playing timestamp; a transmission strategy of audio data is dynamically optimized based on real-time network state parameters, packet loss recovery and bandwidth adaptation are achieved, sub-millisecond multi-room audio synchronous playing is achieved, and meanwhile performance parameters can be automatically optimized according to different network environments and hardware configurations.

The invention provides a power distribution network evaluation method and system, and relates to the technical field of power system operation control, and the method comprises the steps: obtaining an extreme event index of a power distribution network in a current time period according to a measurement data flow, and judging whether an extreme event exists in the power distribution network or not according to the extreme event index; the measurement data streams are classified through a data quality grading mechanism, and then an observation weight matrix of the extreme events is constructed; supplementing missing data for the missing data segment according to the observation weight matrix, dynamically updating topological information of the power distribution network in combination with the supplemented missing data, and obtaining a real-time network model corresponding to the extreme event according to the topological information; and according to the real-time network model and the extreme event index, obtaining a state evaluation result of the power distribution network in the current time period. According to the invention, the evaluation precision of the power distribution network under extreme conditions is improved.

The invention relates to the technical field of multimedia data processing, and particularly discloses an interactive media intelligent preloading and seamless switching method and system based on a dynamic narrative engine, and the method comprises the steps: carrying out multi-step logic deduction according to a predefined narrative logic structure and real-time playing context data of interactive media, calculating the selected dynamic probability of the media segment corresponding to each subsequent narrative node, outputting a high-probability target media segment list arranged in a descending order according to the probability, and deciding the pre-loading content and the loading priority according to the high-probability target media segment list, the attributes of the segments and the real-time network state; the high-probability target media segment is preloaded to a local cache; in response to a user selection instruction, obtaining a target media segment from a local cache or a network; performing decoder management and / or timestamp alignment and / or visual transition processing on the target media segment to obtain a seamless playing switching result; and the narrative logic can be deeply understood, the user behavior can be intelligently predicted, and zero-perception switching can be realized.

The invention provides an ant colony algorithm initialization method and system based on an ISIS protocol, and the method comprises the steps: collecting network topology information in real time based on the ISIS protocol, including a node set, a link set and cost parameters of each link, the cost parameters including transmission time delay, bandwidth utilization rate and packet loss rate; constructing a comprehensive cost evaluation model based on weighted summation of the cost parameters of the links; a pheromone matrix of the ant colony algorithm is initialized based on the result of the comprehensive cost evaluation model, and the link comprehensive cost is inversely proportional to the initial pheromone value; constructing a heuristic information model according to the network topology information, wherein the heuristic information model is the reciprocal of the comprehensive cost; and based on the pheromone matrix and the heuristic information model, initializing a node selection probability function of an ant colony algorithm, and executing the ant colony algorithm to iteratively solve an optimal routing path. According to the method, the real-time network information obtained by the ISIS protocol is used for the initialization of the ant colony algorithm, so that the initialization precision can be improved.

This invention discloses a big data-based system for predicting and evaluating scientific and technological achievements, relating to the field of scientific and technological achievement prediction and evaluation technology. Specifically, it includes: a research and development process data collection module, an information technology achievement prediction module, and an information technology achievement comprehensive evaluation module. The research and development process data collection module collects historical research data, feature data, and network transmission performance data of scientific research projects in real time during the research and development process. The information technology achievement prediction module establishes a prediction model for the feature data of the research process of scientific and technological achievements, sets research process status indicators based on the feature data, and selects network transmission performance data within a stable time range for further training and optimization of the LSTM prediction model. The information technology achievement comprehensive evaluation module comprehensively evaluates the stability of the research process of information technology achievements by predicting real-time network transmission performance data and setting information research fluctuation indicators to predict the stability of the research process.

The application discloses an aeronautical data conversion unit test system, which can complete complete parsing and import of an ICD in an XML source format, configuration and editing of the ICD, and test of an aeronautical data conversion unit; automatically realize ICD management test, that is, based on a complete ICD parsing and import configuration tool chain, automatic management of the ICD can be realized, and automatic test of the aeronautical data conversion unit can be realized; based on the editable configuration of the ICD management, management and editing of a signal interface in a test process can be realized, and various test configurations can be realized; based on a test tool chain composed of a digital simulation environment module and an integrated test environment module, data interaction based on a real-time network can be realized, and commands such as test issuing can be completed.

An embodiment of the present invention discloses an adaptive intrusion detection method and system for low-orbit satellites. The method includes: obtaining an area that a satellite is about to enter; identifying the network threat level of the area based on the network traffic characteristics of the area; predicting the network traffic volume of the satellite after entering the area based on the satellite's real-time network traffic and the network traffic characteristics of the area; invoking an adaptive detection container combination based on the prediction result and the network threat level; and distributing the real-time network traffic within the detection container combination in response to the real-time network traffic of the satellite after entering the area to facilitate intrusion risk detection. This embodiment can conserve intrusion detection resources and improve detection speed.

The invention discloses a router threat detection method, a router threat detection device and electronic equipment, relates to the technical field of network security, and is used for improving the anomaly detection accuracy of routing equipment. The method comprises the following steps: firstly, calculating a target feature matrix based on N pieces of real-time network flow data; then, calculating a dynamic adjustment parameter based on the target feature matrix, and performing parameter adjustment on the initial threat detection model according to the dynamic adjustment parameter to obtain a target threat detection model; and finally, detecting whether the N pieces of real-time network flow data are abnormal or not by adopting the target threat detection model. According to the method, four types of unique flow characteristics are adopted, whether the current routing equipment is abnormal or not can be obviously reflected, and the accuracy of detecting the threat of the routing equipment is improved. Besides, the dynamic adjustment parameters of the model are dynamically adjusted, so that the model can better adapt to the change of the traffic characteristics of the routing equipment, and the accuracy and adaptability of the threat detection of the routing equipment are improved.

The invention provides a false threat intelligence detection method and system based on dynamic graph comparative learning. Belongs to the technical field of network security. The method comprises the following steps: acquiring a CTI report to construct a CTI heterogeneous subgraph with semantic features; acquiring a communication network log to construct a real-time network behavior graph; fusing the two into a global heterogeneous time sequence diagram based on an IoC anchor point; respectively constructing feature codes of the CTI semantic view and the network behavior view by utilizing the GAT and the time sequence GNN; minimizing comparison loss through a graph contrast learning (GCL) framework, and learning a unified embedding space; and finally, the embedding distance of the CTI to be verified under the double views is calculated to serve as an abnormal score for detection. Through a semantic-behavior cross validation mechanism, the problems that in the prior art, external reputation is relied on, semantic forgery cannot be recognized and local fact validation is lacked are solved, the accuracy and robustness of threat intelligence detection are remarkably improved, and the method is particularly suitable for scenes such as communication operators with high requirements for data privacy.

An IoT-based weighing system to increase baby safety, consisting of: an intelligent cradle that has been specially designed and configured to meet the needs of an infant; a microcontroller configured to receive and process data from a variety of sensors and components integrated into the smart charging station; a variety of sensors integrated into the smart cradle and operationally connected to the microcontroller, the variety of sensors including: an infrared temperature sensor for non-contact detection of the infant's body temperature, a microphone sensor for detecting sounds from the infant, a moisture sensor for detecting wetness in a diaper, a gas sensor for detecting the presence of gases and smoke in the environment, and a pulse sensor for monitoring the infant's heart rate; a Wi-Fi module integrated into the microcontroller, configured to transmit the processed data to the cloud server via the internet; a servo motor that is operationally connected to the microcontroller and configured to generate a rocking motion in the cradle, the servo motor being activated by the microcontroller when the microphone sensor detects crying sounds from the infant; a buzzer that is functionally connected to the microcontroller and configured to trigger an audible alarm; a camera module with a webcam configured to capture a live video image of the infant and transmit this live video image via the WLAN module, wherein the camera module is further configured to enable facial recognition and facial identification for the purpose of identifying unauthorized persons, wherein the live webcam feed is retrieved by the microcontroller to perform facial recognition and facial identification, and the microcontroller sends a notification via the cloud server when the webcam detects an unknown face; and a cloud server configured to store the processed data and send notifications to a caregiver's mobile device.

The application provides a lightweight satellite network security management system and method. The system realizes unified management of the satellite network security control plane through a centralized network controller. The system has functions such as security authentication of satellite nodes, dynamic security policy generation and distribution, real-time network monitoring, and rapid security event response. The network controller includes multiple modules such as authentication, policy generation, monitoring, and event response, and can customize security policies according to satellite characteristics and adjust them in real time to respond to security threats. The application also includes lightweight design, especially suitable for resource-constrained satellite environments, and a method for continuously optimizing security policies based on monitoring data and event records. In addition, the provided user interface allows satellite network administrators to easily configure policies and handle events. Through centralized management and dynamic adjustment, the system significantly improves the security and efficiency of satellite networks, has advantages such as lightweight, flexibility, and real-time, and meets the security management needs of modern satellite networks.

The invention belongs to the technical field of industrial network performance optimization, and particularly provides a DDS-5G network collaborative optimization method based on fuzzy logic, through a set static mapping rule, a QoS Policy parameter of a DDS is mapped to a QoS flow identifier of a QoS flow of a 5G network, so that preliminary collaboration of DDS-5G is realized, and meanwhile, through establishing a fuzzy logic reasoning system, the QoS flow identifier of the QoS flow of the 5G network is mapped to the QoS flow identifier of the QoS flow of the 5G network. According to the method, the QoS Policy parameter and the real-time network state parameter serve as input variables, the 5QI serves as an output variable, the QoS Policy parameter of the DDS is optimized and adjusted through the DQN, the fuzzy logic parameter of the fuzzy logic reasoning system is updated, DDS-5G network collaborative optimization is further achieved, efficient collaboration between an application layer and the 5G network is achieved through a cross-layer adaptation mechanism, and the optimization efficiency of the DDS-5G network is improved. The method is suitable for industrial automation, intelligent manufacturing and other scenes with high requirements for low time delay and high reliability.

The invention discloses a method and device for achieving screen projection control based on a WIFI-Display protocol, and relates to the technical field of wireless communication and multimedia transmission, and the method comprises the steps: firstly, building a WIFI-Display connection session between a source device and a receiving end; secondly, a dynamic updating area of the screen is intelligently captured by monitoring a graphic buffer area and using a difference block detection algorithm, and an original screen data stream is only generated for a changing area so as to improve the efficiency; then, dynamically generating coding control parameters by analyzing image motion complexity and real-time network state parameters; and finally, carrying out real-time coding and adaptive network packaging on the data stream based on the parameter to form a screen projection data stream, and sending the screen projection data stream to a receiving end. Through the above mode, the method effectively reduces the bandwidth consumption and the coding calculation amount, and remarkably improves the transmission fluency and the image quality stability of the dynamic screen content in a complex network environment through the adaptive code rate and the packaging strategy.

The invention discloses a real-time network security protection system based on big data analysis. The real-time network security protection system comprises the following steps: collecting real-time network data and constructing a dynamic network diagram data set; constructing a graph state space model based on the dynamic network graph and completing state space initialization; a parallel selective state scheduling mechanism is introduced into the state updating path, parallel analysis is carried out on network node states, and state importance parameters are generated; reconstructing a state updating process according to the state importance parameters, and only executing state updating on the network nodes meeting conditions; performing security judgment on the corresponding communication behavior based on the updated state space representation, and generating a security risk identifier; and generating and issuing a network security protection control instruction according to the security risk identifier, and updating a state scheduling parameter based on execution feedback. According to the invention, through parallel selective state scheduling and state updating reconstruction, the real-time performance and scheduling efficiency of security protection in a large-scale network environment are improved.

The application provides a multi-protocol file transmission state visualization method and system of an intelligent conference terminal, relates to the technical field of data transmission, and through innovative design of protocol identification and priority ordering, in combination with an electrostatic fluctuation correlation coefficient and a buffer influence factor adjustment strategy, can not only dynamically optimize a transmission protocol path, improve transmission efficiency and stability, but also effectively reduce the negative influence of electrostatic disturbance on the transmission process, guarantee the transmission stability of the system in a complex environment; a distributed buffer adjustment strategy is adopted, the optimal file transmission protocol path is selected according to real-time network environment evaluation, the efficient and stable transmission process is ensured, and a visualization interface convenient for users to quickly obtain information is provided, so that the user experience and the actual operation effect of the conference are significantly improved.

The application discloses a CC attack intelligent defense method, device and equipment based on a large language model, comprising: performing traffic semantic translation on captured real-time network traffic to generate a semantic description object including a time sequence behavior sequence and context features; inputting the semantic description object into a domain fine-tuned large language model to perform attack intention reasoning to obtain a threat judgment result, generating a corresponding dynamic defense strategy description based on the threat judgment result; compiling the dynamic defense strategy description into an executable instruction sequence, and issuing the executable instruction sequence to a downstream security device to drive execution to obtain an execution result; based on the execution result, monitoring network traffic situation and business indicators after the downstream security device executes the strategy to generate strategy effect evaluation data; and optimizing the large language model based on whole-link data including the semantic description object, the threat judgment result, the dynamic defense strategy description and the strategy effect evaluation data.

To provide an environment in which a user can safely perform online activities by providing a real-time phishing fraud detection and warning system using a generative model.SOLUTION: The phishing fraud detection system includes means for analyzing the received digital information using a generative model trained using knowledge of security experts and training data obtained from specialized information sources to detect characteristics of the fraudulent activity, means for generating an alert based on the analysis, and means for providing specific safety action advice to the user.SELECTED DRAWING: Figure 1

The application discloses a self-adaptive video stream coding optimization method and device, equipment and product, and relates to the technical field of multimedia communication. The method comprises the following steps: inputting image basic data of a video stream into a video feature extraction model; calculating image feature differences between video frames by the video feature extraction model to obtain target image features; determining user viewing preferences by using a pre-trained binary classifier according to the image basic data and the target image features; and performing coding optimization on a current video by a video stream coding model based on a current network state and the user viewing preferences. The pre-trained binary classifier is used to determine the user viewing preferences, the viewing preferences of different users for different video contents are determined, the viewing preferences of the users and real-time network conditions are combined, the optimization points are considered from multiple angles, the best coding configuration is selected for real-time interactive video streams, and the self-adaptability of the interactive video streams in different scenes is improved, and the user experience is improved.

The application discloses a digital twin data synchronization method and system fusing deep learning and Internet of Things, and relates to the technical field of data synchronization. The method comprises the following steps: based on the digital twin information of the Internet of Things equipment, calling the time stamp and data sequence identifier through a sliding window, collecting the time span, calculating the characteristic value change amplitude of adjacent time slices in the data sequence, and performing transmission data sparsification processing to reduce the communication burden and obtain a sparse feature set. In the application, the sliding window technology and time series analysis are adopted to efficiently extract and compress data features, significantly reduce the redundancy in data transmission, improve the transmission rate and efficiency, the dynamic segmented decoding and feature mapping structure application enable stronger response capability and prediction accuracy to data fluctuations, intelligently adjust the data flow direction and node connection weight, optimize the data synchronization path according to the real-time network state and bandwidth allocation, and ensure the efficient synchronization of data among multiple nodes and multiple platforms.

This invention proposes a method and system for detecting false threat intelligence based on dynamic graph contrastive learning, belonging to the field of network security technology. The method includes: acquiring CTI reports to construct a heterogeneous CTI subgraph with semantic features; acquiring communication network logs to construct a real-time network behavior graph; fusing the two into a global heterogeneous temporal graph based on IoC anchors; constructing feature encodings for the CTI semantic view and network behavior view using GAT and temporal GNN respectively; minimizing the contrastive loss through a graph contrastive learning (GCL) framework to learn a unified embedding space; and finally calculating the embedding distance of the CTI to be verified under the dual views as an anomaly score for detection. This invention, through a "semantic-behavioral" cross-validation mechanism, solves the problems of existing technologies relying on external reputation, being unable to identify semantic forgery, and lacking local fact verification, significantly improving the accuracy and robustness of threat intelligence detection, and is particularly suitable for scenarios with high data privacy requirements, such as telecommunications operators.

The invention relates to the field of network security, in particular to a network anomaly detection method, system and device based on two-dimensional space-time prediction and behavior flow compression and a storage medium. The method comprises the following steps: collecting and preprocessing historical access data in a network to obtain a historical behavior data sequence; based on the historical behavior data sequence, constructing a two-dimensional space-time behavior model including space path prediction and time dynamics prediction; performing behavior flow compression on the collected real-time network access data to generate a real-time behavior fingerprint; extracting an abnormal mode from the historical behavior data based on a normal behavior benchmark defined by the two-dimensional space-time behavior model, and generating an abnormal feature library; constructing and maintaining a dynamic behavior baseline based on a sliding window mechanism by taking the two-dimensional space-time behavior model as a reference; comparing the real-time behavior fingerprint with the dynamic behavior baseline, and matching the real-time behavior fingerprint with an abnormal feature library to obtain a deviation degree; according to the method and the device, the accuracy of a detection result can be improved.

The invention relates to the technical field of video transmission, in particular to a video secure transmission method, device and system in a low-bandwidth scene, and aims to improve the video secure transmission efficiency by defining the influence weight of a historical frame image on a current frame image and combining the characteristic that each motion area is in a continuous high ROI state in the historical frame image. Determining a code rate increasing factor of each motion area of the current frame image; constructing the weight of each motion area of the current frame image in a smooth matrix by using the code rate increasing factor and the space center position of each motion area, constructing the smooth matrix in combination with a Gaussian kernel function, and performing smooth processing on the code rate increasing factor, thereby effectively inhibiting the visual discontinuity phenomenon between the frame images; determining a code rate relative weight of each motion region of the current frame image by jumping maximization of the visual quality of the key region and minimization of the quality between the regions into a target design target function; and in combination with the real-time network bandwidth and the dynamic scaling code rate allocation result, the optimal balance of quality and smoothness is realized under the bandwidth constraint.

This invention discloses a real-time data security monitoring system based on online data modeling, specifically relating to the field of network security technology. The system includes a data acquisition module for collecting real-time network stream data and extracting feature sequences of behavioral patterns; a feature space module for constructing a feature space and generating feature drift mapping sequences and abnormal behavior recognition sensitivity change trend sequences; a shift analysis module for identifying feature variation trends caused by low-intensity probing attack samples; a decay detection module for identifying the degradation characteristics of the real-time security monitoring classifier's ability to recognize real attack events; a risk assessment module for evaluating the risk level of induced drift in the real-time security monitoring classifier based on feature variation trends and recognition ability degradation characteristics; and a reconstruction trigger module for determining the risk level of the real-time data security monitoring system based on the risk level and triggering a security reconstruction mechanism for the real-time security monitoring classifier, thereby improving the stability of the security monitoring system in recognizing persistent induced attack behaviors.

The invention relates to the technical field of multi-screen display, in particular to an information data processing method based on the industrial internet. According to the technical scheme, efficient information data processing is achieved through the industrial internet, the data acquisition module automatically identifies and converts heterogeneous protocols such as Modibus, OPC UA and MQTT into a unified JSON or XML format, and data compatibility and consistency are improved. Data processing is carried out in a layered mode, the edge nodes rapidly process real-time data, anomaly detection and filtering are included, and low-delay response is ensured; the cloud computing platform carries out deep analysis and trend prediction, and a machine learning model is used to enhance insight. The communication module adopts a dynamic path optimization algorithm, adaptively selects an optimal transmission path based on real-time network parameters, improves the reliability and efficiency of data transmission, and supports a standby mode to cope with network faults. The modular interface design allows hot plug and standardized interaction, and the expandability and maintainability of the system are improved.

The embodiment of the invention relates to a processing method and device for planning a short message retransmission strategy based on a network awareness state. The method comprises the following steps: carding a state type set S, defining a cost index C, and configuring a strategy parameter set and a strategy parameter value domain DP corresponding to the strategy parameter set; constructing an index prediction model and a strategy prediction model; constructing a first data set; training an index prediction model based on the first data set; optimizing the optimal strategy configuration corresponding to each state sample by taking the minimum cost index as an optimization target, and constructing a second data set based on all the state samples and the corresponding optimal strategies; training a strategy prediction model based on the second data set; and the strategy prediction model and the index prediction model dynamically plan the short message retransmission strategy of the server according to the real-time network state of the short message sending server and predict the cost index of the planning strategy. According to the invention, the configuration flexibility of the short message retransmission strategy can be improved, and the cost control can be optimized.

The invention provides a 5G QoS intelligent configuration method and device based on natural language processing. The method comprises the following steps: receiving a natural language QoS configuration request of a user; analyzing the natural language QoS configuration request by using a natural language analysis model enhanced by domain knowledge, and outputting a structured QoS configuration parameter set conforming to a 3GPP (3rd Generation Partnership Project) protocol specification; verifying and processing the structured QoS configuration parameter set through cooperative interaction of a plurality of network elements in the 5G core network, and generating a final executable QoS strategy instruction; and generating a policy decision based on the finally executable QoS policy instruction and real-time network context information, and controlling a user plane function network element to execute the policy decision to complete QoS configuration. The method has the beneficial effects that the professional threshold and technical complexity of 5G QoS configuration are remarkably reduced, the configuration efficiency and accuracy are greatly improved, and network resources are allocated according to needs and dynamically optimized at the same time.

The invention relates to the technical field of network security, in particular to a self-adaptive network intrusion detection and response method and system, and the method comprises the steps: collecting real-time network flow data, and collecting the number of login failures of a user and user behavior data; calculating a traffic abnormity threat value according to the real-time network traffic data; calculating an abnormal behavior threat value according to the number of login failures of the user and the user behavior data; and calculating a comprehensive threat value according to the traffic anomaly threat value and the behavior anomaly threat value, and generating a response priority in combination with the asset value. And the comprehensiveness of threat detection is improved. Through multi-source data fusion, a dynamic weight mechanism and asset value association, the accuracy of intrusion detection and the rationality of a response strategy are significantly improved, and the method is suitable for a complex and changeable network security environment.

According to the authentication method and device, the equipment, the storage medium and the product provided by the embodiment of the invention, firstly, real-time state information, including real-time network environment parameters, of a client is acquired; according to the embodiment of the invention, the method comprises the following steps of: acquiring real-time state information of a server, then determining a target authentication strategy based on a pre-constructed authentication strategy selection rule according to the real-time state information, and finally initiating authentication to the server based on the target authentication strategy. According to the technical scheme, the dynamic authentication strategy adaptive to the real-time scene is used for replacing mechanical sequential attempts, invalid authentication attempts and switching are effectively avoided, and therefore authentication time consumption is reduced, and user experience is improved.

The invention discloses a VXLAN-GBP optimization method and system based on dynamic strategy collaboration, and the method comprises the following steps: receiving an original message, and extracting the message features of the original message; based on message features, the monitoring module performs real-time network state analysis, namely, multi-dimensional network indexes are collected in real time through the hardware detection unit; performing hash value calculation on the multi-dimensional network index to obtain a hash value; carrying out VXLAN-GBP packaging on the basis of the Hash value, and adding a VXLAN-GBP head containing a DPT field to form a VXLAN-GBP message; receiving a VXLAN-GBP message, analyzing the head of the VXLAN-GBP, extracting the 27th bit of a DPT field, and if the 27th bit of the DPT field is 0, expressing the 27th bit to be static, matching a basic strategy by using a static policy ID, and enabling the message to execute normal forwarding; and if the message is' 1 ', representing to be dynamic, extracting a hash value of the DPT field, and according to the range of the hash value, matching a basic strategy, a dynamic speed limiting strategy or a security processing strategy, so that the message is subjected to corresponding processing. According to the invention, manual intervention and network delay can be reduced.

The application relates to the technical field of Internet of Things, in particular to an Internet of Things device asynchronous reporting method and system for guaranteeing data integrity. The method comprises the following steps: obtaining a hydrological buoy group information set, balancing the contradiction between the timeliness and the integrity of hydrological data collected by the buoy based on the hydrological buoy group information set, and obtaining a data criticality evaluation information set; based on the data criticality evaluation information set, dynamically sorting the hydrological reporting data according to the real-time network state and the data context correlation, and obtaining a reporting priority information set; based on the reporting priority information set, generating an asynchronous reporting scheduling strategy, executing a reporting decision instruction, and outputting a hydrological buoy data reporting log. The method effectively solves the resource competition problem in the hydrological high-priority data reporting process, ensures the timely reporting of abnormal data and complementary data, and improves the integrity and timeliness of the hydrological data.