17 results about "Integrative data analysis" patented technology

The invention discloses a juicy peach yield prediction method based on comprehensive data analysis, and particularly relates to the technical field of agricultural intelligent perception. The method comprises the following steps: collecting multi-source data of an orchard, and constructing a data set containing meteorological, physiological, remote sensing and soil information; fruit tree physiological response parameters are extracted, and a bimodal diagram structure fusing the spatial adjacency relation and the physiological state similarity is established in combination with the dynamic climate anomaly index; inputting the graph structure into a graph neural network model, extracting spatial-temporal characteristics, dynamically adjusting an edge weight and a propagation layer number, and constructing an adaptive model; performing region division and weighted summarization according to a model output result, and finally obtaining a predicted value of the total yield of the orchard; the method improves the prediction accuracy under the conditions of complex climate and unstable data, and is suitable for refined orchard management.

The invention discloses a cable trench fireproof cover plate performance detection device and method based on multi-band electromagnetic waves. The device comprises a microwave detection module, a terahertz imaging module, a high-precision two-dimensional mechanical scanning platform, a synchronous control and data fusion unit and a comprehensive data analysis platform. The microwave module is used for transmitting and receiving 1-10GHz electromagnetic waves to realize deep structure detection; the terahertz module works at a frequency band of 0.1-3 THz and is used for acquiring near-surface time-domain spectral information. And the scanning platform drives the modules to perform two-dimensional rasterization scanning on the surface of the cover plate. And the synchronous control and data fusion unit coordinates the time sequence action of each module to ensure the time-space consistency of data acquisition. And the comprehensive data analysis platform performs fusion processing on the multi-source data through an inversion and imaging algorithm to generate a comprehensive evaluation report covering internal macroscopic defects, near-surface microdefects and coating thickness. According to the invention, through collaborative integration of microwave and terahertz technologies, multi-scale and integrated nondestructive testing and performance evaluation of the fireproof cover plate from a deep layer to a surface layer are realized.

The invention relates to a method for detecting microcracks on the inner wall of a wall enclosure superheater of a boiler. The method comprises the following steps: macroscopically identifying and preliminarily screening a high-risk area; creating an endoscope channel based on the primary suspicious area list and performing primary peeping on the inner wall; carrying out detection surface preparation and acoustic coupling optimization; data acquisition is carried out through accurate arrangement of the small-sound-velocity self-coupling phased array ultrasonic probe; extracting defect signal features and carrying out three-dimensional digital modeling; performing crack depth accurate quantization based on a time of flight diffraction mode; carrying out comprehensive data analysis and evaluating a security level; and integrating detection results, and generating a digital file based on the results. According to the invention, standardization of the detection process and systematization of data management can be realized, the detection efficiency and accuracy are greatly improved, a scientific basis is provided for equipment life prediction and maintenance decision, and the safe operation level of the boiler is effectively improved.

The application discloses a kind of comprehensive data analysis system and method applied to intelligent audit, it is related to big data analysis technical field, the present application is by obtaining audit object whole-link business data, constructs full audit data set by standardization processing;Extract static and dynamic risk characteristics, build the comprehensive rule system containing static and dynamic required verification data type library;Analysis single risk and associated business link causality, generate audit associated link mapping table and ordered risk set;Calculate corresponding risk determination threshold;Real-time monitoring audit business based on threshold, data characteristics are intercepted by sliding window, after audit cycle ends, iteration updates threshold.The system includes data full collection, audit rule construction, associated link analysis, determination threshold calculation, audit threshold iteration module and subordinate unit.The present application realizes full data coverage and real-time monitoring, accurately traces risk transmission, improves the confidence and timeliness of audit compliance judgment.

This invention discloses an automated inspection system for semiconductor packaging wire bonding quality, relating to the field of semiconductor packaging technology. It includes: a multi-frequency signal transmitting module for sequentially transmitting high-frequency, mid-frequency, and low-frequency electrical signals to the wire bonding; a receiving module for receiving the multi-frequency electrical signals transmitted by the wire bonding and acquiring the signal strength of each frequency band in real time; a thermal noise detection module for detecting the thermal noise level in the wire bonding; a time-domain reflectometry module for transmitting high-frequency pulse signals to the wire bonding, detecting the reflection time and waveform characteristics of the signals in the wire bonding, and identifying physical defects in the wire bonding; and a data analysis module for comprehensively analyzing the multi-frequency signal strength, thermal noise level, and time-domain reflectometry waveform characteristics after temperature compensation to determine the wire bonding quality. In the comprehensive data analysis, all detection data are integrated and analyzed to achieve comprehensive inspection of wire bonding quality, significantly improving the accuracy and reliability of the inspection.

The application discloses an automatic zinc oxide solid waste extraction rotary kiln production line control system, and particularly relates to the technical field of automation, which comprises a monitoring area division module, a data monitoring and collecting module, a data preprocessing module, a data analysis module, a comprehensive data analysis module, a judgment and early warning module and a man-machine interaction module. The monitoring area division module is used for arranging monitoring points; the data monitoring and collecting module is used for collecting solid waste extraction first key information values, and the data preprocessing module is used for obtaining solid waste extraction second key information values; the data analysis module is used for obtaining solid waste extraction third key information values; the comprehensive data analysis module is used for obtaining solid waste extraction fourth key information values, i.e. solid waste extraction evaluation indexes; the judgment and early warning module is used for constructing solid waste extraction comprehensive evaluation standard values, judging whether the zinc oxide solid waste extraction meets the standards or not; and the man-machine interaction module is used for providing a visual interface. The state of the zinc oxide solid waste extraction is comprehensively and effectively fed back.

The application discloses a kind of based on comprehensive data analysis's software user experience evaluation method and system, it is related to human-computer interaction technical field, this method is by embedding behavior perception engine in software operation interface, collect the use frequency of user in task path, jump operation frequency, process standard step number and access user total number, and further unified normalization processing is carried out in background server, constructs normalized behavior dataset, calculates path deviation joint index PDI.In based on path deviation joint index PDI joint consideration path selection information entropy and path jump rate mean two dimensions, whether the use of user path exists concentrated deviation or process jump behavior can be effectively identified, and then whether there is forced guidance, process hidden shortcut in system path design is judged.Compared with the evaluation mode of traditional only relying on click heat map or jump rate, the present method realizes higher dimensional path behavior modeling and deviation identification ability.

The present application belongs to the technical field of underground ore body monitoring, and particularly relates to a dynamic monitoring method and system for cross-border mining in underground mines. The method comprises: (1) constructing a digital twin base map of the mine; (2) laying a seismic source monitoring network on the basis of the digital twin base map of the mine, and performing microseismic monitoring and three-dimensional micro-motion exploration; (3) building a multi-dimensional intelligent dynamic monitoring and early warning platform through the data obtained from the digital twin base map of the mine and the seismic source monitoring network, wherein the multi-dimensional intelligent dynamic monitoring and early warning platform is used for realizing real-time pushing of monitoring data and three-dimensional visual display, and performing cross-border analysis and judgment based on the comprehensive data analysis results, and timely issuing early warning information for suspected cross-border mining events.

The application discloses an intelligent diagnosis auxiliary system based on a medical knowledge graph and belongs to the medical diagnosis field. In order to solve the problem that a traditional medical diagnosis system is difficult to integrate information, a large amount of medical information is wasted, effective auxiliary diagnosis cannot be performed, the diagnosis efficiency is low, effective intelligent triage prediction cannot be performed, the patients are easily caused to have a burden of diagnosis, the hospital is easily caused to have a burden of operation, the work efficiency is low, corresponding diagnosis results cannot be given in time and quickly, and the diagnosis accuracy is influenced. The existing medical data island problem is overcome, the intelligent auxiliary diagnosis of common diseases is realized, the diagnosis efficiency is improved, the doctors are provided with high-credibility auxiliary diagnosis, the intelligent triage prediction is realized, the probability of wrong triage is reduced, the patients are provided with efficient and convenient pre-diagnosis consultation, the burden of the patients and the operation load of the hospital are reduced, the diagnosis accuracy of the diagnosis auxiliary system for comprehensive data analysis of patient information is gradually improved through human error correction.

The invention provides a polar region low-temperature valve sealing performance testing system and method based on multi-physics field coupling, and belongs to the technical field of polar region environment equipment reliability testing. According to the invention, the sealing performance of the valve in a low-temperature environment is quantitatively evaluated by simulating polar extreme climate conditions and combining a multi-physical field coupling test technology. According to the invention, multiple environmental stresses such as polar region low temperature, temperature circulation, pressure fluctuation and surface icing can be accurately simulated, and a high-precision sensing technology and comprehensive data analysis are integrated, so that comprehensive and quantitative evaluation and life prediction of the sealing performance of the valve from a static boundary to dynamic degradation and from a macroscopic phenomenon to a micromechanism are realized; and an effective technical means is provided for reliability design and verification of key valves of polar equipment.

The invention relates to the field of medical detection, and provides a microbial marker combination for predicting esophageal cancer prognosis and application thereof. According to the present invention, the significant correlation between the microbial spectrum and the esophageal cancer prognosis is found, the comprehensive data analysis of the microbiome abundance, the clinical information and the transcriptome data is performed on the patient to determine the specific 15 microbial markers related to the esophageal cancer prognosis, and the risk scoring model for predicting the esophageal cancer prognosis is established; the microbial model is used for predicting the immunotherapy curative effect and response of esophageal cancer patients and can help a doctor to more accurately judge which patients are more likely to benefit from immunotherapy before treatment, so that a more personalized and effective treatment scheme is formulated for the patients.

The invention discloses a corn ear quality detection method based on comprehensive data analysis, and relates to the technical field of agricultural product quality detection. The method comprises the following steps: pre-selecting a forward sample and a reverse sample from a plurality of corn ear samples to be detected; according to the obtained feature parameters of the forward sample and the reverse sample, utilizing a classification model to obtain a preliminary classification result of the cluster sample; selecting a final classification result from the preliminary classification results of the classification model according to a preset selection condition; in the classification process, pre-selected forward samples and reverse samples are dynamically updated according to feature parameters of the classified samples; retraining the first classification model and the second classification model according to the updated forward sample and reverse sample; according to the method, under the condition of no prior knowledge, various characteristic parameters are integrated, and efficient and accurate detection of the quality of the corn ears is realized.

The invention relates to the field of medical detection, and provides a microbial marker combination for predicting breast cancer prognosis and application thereof. According to the present invention, the significant correlation between the microbial spectrum and the breast cancer prognosis is found, the comprehensive data analysis of the microbiome abundance, the clinical information and the transcriptome data is performed on the patient to determine the specific 22 microbial markers related to the breast cancer prognosis, and the risk scoring model for predicting the breast cancer prognosis is established; the microbial model is used for predicting the immunotherapy curative effect and response of breast cancer patients, and can help a doctor to more accurately judge which patients are more likely to benefit from immunotherapy before treatment, so that a more personalized and effective treatment scheme is formulated for the patients.

The invention discloses a lunar surface low-gravity environment complex task exoskeleton auxiliary efficiency evaluation method. Comprising the following steps: 1) acquiring monitoring signals that a user finishes a task in a low-gravity environment when wearing an exoskeleton and not wearing the exoskeleton, preprocessing the monitoring signals, and drawing a fitting curve of the preprocessed monitoring signals and time to obtain a fitting curve of the wearable exoskeleton and a fitting curve of the non-wearable exoskeleton; 2) comparing the fitting curve of the wearable exoskeleton with the fitting curve of the non-wearable exoskeleton to obtain a comprehensive objective evaluation result; 3) obtaining a subjective evaluation result perceived by the user through the questionnaire; and 4) determining weights of the comprehensive objective evaluation result and the subjective evaluation result through an ant colony optimization algorithm to obtain a final evaluation result. The method includes performing integrated data analysis based on the monitored characterization parameters. Finally, the auxiliary performance of the exoskeleton in the low-gravity environment is evaluated, and reliable support is provided for optimizing the design of the low-gravity exoskeleton.

This invention discloses an assessment and measurement method for evaluating the backlash risk of longline fishing feeder lines. The method includes: preparing several test feeder lines; conducting a sudden shear test on each feeder line to obtain motion trace data of the backlash motion; and then performing comprehensive data analysis on the motion trace data and force condition data of all test feeder lines to derive the correspondence between feeder line backlash motion and changes in feeder line force. Using this assessment and measurement method to evaluate longline fishing feeder lines enables the acquisition of the correspondence between feeder line backlash motion and changes in feeder line force, achieving visualized recording and quantitative assessment of feeder line backlash behavior. This overcomes the limitations of existing technologies that rely solely on qualitative descriptions or empirical judgments, providing objective data support for the safety optimization of feeder line weighting and reducing operational risks for crew members.

The invention discloses a pear tree ecological index assessment method based on comprehensive data analysis, and relates to the technical field of smart agriculture. The method comprises the following steps: acquiring tree body physiological data, environmental stress data and resource input data in real time, dividing a pear tree physiological system into a fruit growth subsystem, a root development subsystem, a disease and pest resistance defense subsystem and a symbiosis support subsystem, constructing a resource allocation game optimization model by taking each subsystem as a game participant, and establishing a resource allocation game optimization model based on acquired multi-dimensional data. And dynamically calculating the current capital state and the environmental stress index of each game participant, taking the total resource budget of the pear tree as a constraint condition, solving by adopting a reinforcement learning algorithm to obtain an optimal resource allocation vector, and calculating the ecological coordination index of the pear tree by comparing the optimal resource allocation vector with the actually measured allocation vector. And generating and outputting a corresponding ecological management strategy based on the calculated ecological coordination index, the optimal resource allocation vector and the current capital state of each game participant.

The invention relates to the technical field of data processing, and discloses an image comprehensive data analysis processing method and system based on a knowledge graph. The method comprises the following steps: acquiring a mobile terminal image, a carrier passing record and equipment positioning data, establishing space-time correlation through a triangulation positioning algorithm, executing frequency domain transformation on the image to extract a steganography entropy value and a face feature vector, calculating a product of cosine similarity and a spatial overlapping degree as a confidence coefficient to construct a knowledge graph triple, performing statistics on historical behavior distribution to construct a baseline vector and calculate KL divergence, performing weighting with steganography entropy to obtain anomaly, performing graph traversal on behaviors exceeding a threshold, replacing a word frequency item of the improved BM25 algorithm with a spatio-temporal proximity product, and replacing a document length item with a behavior link length to perform divulging mode matching. The problems that in the prior art, multi-source data are isolated, hidden secret stealing is difficult to detect, and the cross-scene association analysis capacity is insufficient are solved.