75results about How to "Increase influence" patented technology

The invention relates to the technical field of genomics, in particular to a gene detection data cleaning method and system based on artificial intelligence. The method comprises the following steps: acquiring gene detection data, and performing preliminary filtering on the gene detection data based on removal of low-quality reads to obtain preliminary filtering data; performing linker sequence identification and removal on the preliminarily filtered data, and performing sequencing error correction to generate gene sequence data; performing GC content analysis and repetitive sequence identification on the gene sequence data to obtain sequence feature data; performing dynamic quality threshold adjustment according to the sequence feature data, and performing secondary filtering on the gene sequence data to generate high-quality sequence data; and performing sequence pattern recognition on the high-quality sequence data to obtain sequence pattern feature data. According to the method, deep analysis is carried out by utilizing sequence characteristics such as GC content and nucleotide distribution, and the recognition capability on sequence complexity and variation modes is improved.

The invention provides a radiation source individual identification method based on multi-domain feature fusion, which mainly realizes radiation source individual identification through signal acquisition, signal preprocessing, signal pre-classification, feature extraction and model pre-training. Compared with a traditional method, the method has the advantages that the fused multi-domain features can better reflect subtle differences of radiation sources, and the recognition effect is obviously improved; by respectively extracting the features of each domain, the dimension of data can be effectively reduced, so that the complexity of calculation and storage is reduced; meanwhile, pertinent processing and fusion are allowed to be carried out on the features of different domains, and the classification precision is improved; the features of different domains can be selected and weighted, the influence of important features is enhanced, and the model is more flexible and accurate; common computer hardware is used for configuration, practicability is high, and economical efficiency is good.

The invention discloses a cultural ruin and image digital protection system and restoration method, and relates to the technical field of cultural heritage protection, and the system comprises a digital collection module, an intelligent restoration module, a diversified transmission module, and a safety protection and copyright protection module. And the digital acquisition module is used for carrying out all-directional and multi-angle digital acquisition on the cultural ruins by adopting high-precision three-dimensional scanning, unmanned aerial vehicle aerial photography and high-definition camera shooting technologies. According to the cultural ruin and image digital protection system and restoration method provided by the invention, through high-precision three-dimensional scanning, unmanned aerial vehicle aerial photography and high-definition camera shooting technologies, the cultural ruin can be digitally acquired in an omnibearing and multi-angle manner, and accurate three-dimensional models, high-definition texture images and video data are acquired; the public participation sense and interactivity are enhanced, the situation that resources are illegally obtained and used is effectively prevented, and powerful legal and technical guarantee is provided for digital protection of cultural heritage.

The invention discloses a multi-modal sentiment analysis method based on modal focusing, which takes text, visual and audio modals as centers, focuses on each modal one by one, aims to explore how to perform interactive fusion on information of a main modal and other two secondary modals, and provides a multi-modal sentiment analysis method based on modal focusing in a subsequent fusion process. The three main modes are connected in an effective mode to serve as fusion representation of guidance, and more comprehensive and effective multi-mode information is provided for sentiment analysis tasks. Comprising the following steps: (1) shared mask learning: obtaining a shared mask between a primary mode and a secondary mode by training a cross-modal prediction model; (2) a cross-modal interaction stage: performing interactive fusion on the characteristics of the primary and secondary modals by adopting a cross-modal attention mechanism with a shared mask to obtain fusion representation dominated by each modality; and (3) a subsequent fusion stage: endowing the three fusion expressions with respective weights by using a weighted attention mechanism for connection to obtain a final multi-modal fusion vector. According to the method, the feature relation and cross-modal interaction between the primary and secondary modals are fully mined and utilized, so that the condition of multi-modal information imbalance is processed, and a more accurate sentiment analysis result is achieved.

The invention discloses a digital human live broadcast strategy generation method and device, computer equipment and a storage medium. According to the specific implementation scheme, the method comprises the following steps: calculating the association degree of an associated live video and a current live video in a preset time interval based on a multi-modal association degree calculation mode, and obtaining an association degree calculation result; determining a dynamic digital human model corresponding to the associated live video according to a predetermined basic digital human model and the association degree calculation result; and determining a fusion live broadcast strategy according to the basic digital human model, the personalized digital human model and the dynamic digital human model. According to the method, the fusion live broadcast strategy is determined according to the digital human models corresponding to the multi-dimensional data, dynamic changes in a live broadcast scene can be well adapted, a comprehensive live broadcast decision is made in time, and differentiation of the digital human models is further considered through multi-modal correlation degree calculation, so that the live broadcast effect is improved.

The invention relates to the technical field of digital human systems, and discloses an enterprise propaganda virtual digital human system based on a block chain and deep learning, and the system ensures the safety and non-tampering of enterprise propaganda data and user interaction data through a block chain storage unit; the intelligent level of the virtual digital human is improved by utilizing a deep learning model construction unit, and the functions of language understanding, dialogue generation, image rendering and the like are realized; the enterprise information extraction unit and the user request processing unit are respectively responsible for data updating and request analysis; the dialogue management unit and the image rendering unit generate proper replies and dynamic images according to user requirements and scenes; the block chain verification unit guarantees the authenticity of the data; the feedback optimization unit realizes continuous optimization of the model; and the multi-channel publishing and managing unit ensures multi-platform synchronization and consistency of contents. According to the system, the personalized, interactive and efficient levels of enterprise propaganda are greatly improved.

The invention relates to the field of artificial intelligence shopping, in particular to a shopping mall system of an intelligent search interest recommendation algorithm, which comprises a registration and login module used for selecting a login identity and a login mode and inputting login information; the factory cloud supply module is used for updating and deploying the commodity supply information in real time; the merchant service module is used for managing commodity orders, counting service of buyers and analyzing sold commodities; the promotion and distribution module is used for carrying out advertisement putting and promotion activity promotion based on a digital transmission channel, and is also used for helping merchants to carry out management setting on distributors and formulate distribution levels, regional distribution and shareholder bonuses; the financial module is used for providing balance and points of shop members for merchant users and providing commission calculation and commission withdrawal; according to the invention, the enterprise operation efficiency is improved, the cost is reduced, the brand influence and market competitiveness are improved, and an efficient, intelligent and integrated business management system is realized.

The invention provides a network ideological and political education personalized guiding method based on emotional tendency recognition, and aims to perform emotional analysis on network speech of college students through a natural language processing technology so as to recognize emotional tendencies of the college students. According to the method, speaking data of students in social media, forums and comment areas are collected in real time through web crawlers, and then emotional polarity judgment and emotional tendency recognition are conducted through a deep learning model such as LSTM. According to an analysis result, a personalized ideological and political education scheme is formulated in combination with personal backgrounds and requirements of students, and personalized customization of education contents and methods is realized through steps of emotional civilization cultivation, special group attention, education innovation in a new media environment, theory and practice combination and the like. The application of the method can improve the pertinence and effectiveness of ideological and political education, promote the cultivation of emotional civilization of students, and help cultivate new-age college students with positive emotional attitudes and correct values.

The invention discloses a block chain social network opinion leader identification method and device, a medium and a product, and relates to the field of data processing. The method comprises the following steps: constructing a directed network based on user data of a block chain social network; obtaining a network structure characteristic index of the directed network; determining key nodes in the plurality of nodes according to the network structure characteristic indexes; obtaining a contribution behavior characteristic index of the user in the block chain social network; based on an entropy weight method and a standard correlation weight method, determining index weights of the network structure characteristic indexes and the contribution behavior characteristic indexes; determining an influence score of the user according to the network structure feature index, the contribution behavior feature index and the index weight; and determining an opinion leader of the block chain social network from the users according to the influence score. According to the method, the opinion leader in the block chain social network is accurately identified by combining the entropy weight method and the standard correlation weight method and utilizing the network structure characteristic index and the contribution behavior characteristic index.

The invention relates to the technical field of artificial intelligence questions, in particular to an analysis report generation method based on a question result of a large language model, which comprises a question system for obtaining the question result according to a question input by a user, and further comprises the step of constructing a report template database. The method comprises the following steps: S1, vectorizing a natural language; s2, in the Weaviate vector database, selecting a cue word with the maximum similarity value to match a cue word template; and S3, if the matching is successful, performing secondary calculation on the question number result according to the cue word template, combining the question number result and the secondary calculation result to form report data, filling the report data into a report template associated with the current cue word template, and generating a complete analysis report. According to the method, the data processing efficiency and reliability are greatly improved, meanwhile, the labor cost is reduced, and optimization and innovation of a data analysis process are promoted.

The invention provides a general bypass reconciliation and early warning system based on big data, which belongs to the technical field of information, adopts a layered architecture design and comprises a data acquisition layer, a data processing layer, an intelligent reconciliation layer, an early warning decision-making layer and a user interaction layer. All the layers carry out efficient data exchange and instruction transmission through standardized interfaces, it is ensured that all function modules of the system can work cooperatively, and automatic account checking and abnormal early warning of cross-system and cross-platform transaction data are achieved.

The invention relates to the field of material evaluation, in particular to an automobile seat material performance evaluation method based on an AHP-entropy weight method, and aims to solve the problem of non-objective evaluation of comprehensive performance of an automobile seat material in the prior art. The automobile seat material is weighted from subjective and objective angles according to the AHP method and the entropy weight method; and then the subjective evaluation result and the objective evaluation result are combined to obtain a combined weight, so that the coupling relationship between different materials can be better processed, and the comprehensive performance of each material can be more accurately evaluated. And the preference degree of the decision maker for the subjective evaluation method and the objective evaluation method is taken as a reference, so that the participation degree and the influence of the decision maker in the evaluation process are improved, and the evaluation result is more persuasive and representative.

The invention belongs to the technical field of internet application, and particularly relates to a key user discovery method oriented to subdivided fields and wide-area social contact, which comprises the following steps: acquiring user basic information, user historical behaviors and user social contact contents under a current topic, and extracting field information and social contact information from the user basic information, the user historical behaviors and the user social contact contents; calculating the domain recognition degree of one user to another user according to the domain information and the social information, and establishing a topic propagation network by taking the user as a node and the domain recognition degree as an edge weight; in the topic propagation network, walking based on a bias sampling strategy to obtain structural features of nodes; a two-layer graph convolutional neural network is established, the network is composed of a first graph convolutional layer, a Dropout layer and a second graph convolutional layer which are cascaded, and structural features of nodes are input into the network to predict whether the nodes have influence or not; according to the method, key users can be found in specific fields, key users with more influence are selected for customers to carry out product popularization, and the effectiveness of advertisement putting is improved.

The invention relates to a recommendation information click probability prediction method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: converting data in a recommendation information click data table into feature elements to obtain an embedded matrix; performing different pooling processing on the embedded matrix, and performing cross fusion on feature vectors obtained after different pooling processing to obtain pooling feature vectors; converting the pooling feature vector into an attention weight feature vector through a first activation function, and fusing the attention weight feature vector and the embedded matrix to obtain a first feature representation; converting the embedded matrix into a second feature representation through a preset projection weight and a second activation function; and fusing the first feature representation and the second feature representation to obtain a combined feature representation, and determining the probability that the target object clicks the recommendation information according to the combined feature representation. By adopting the method, the prediction accuracy of the recommendation information click rate can be improved.

The invention belongs to the field of bidding and tendering, relates to a data analysis technology, is used for solving the problem that various requirements of enterprise users cannot be met due to the fact that bidding project recommendation is provided for the enterprise users according to a single standard or basis in the prior art, and particularly relates to an enterprise competition management method and system based on bidding and tendering big data. The enterprise management platform is in communication connection with a document screening module, a user analysis module, a recommendation output module and a bidding database; the document screening module is used for performing preliminary screening analysis on the bid invitation documents: marking enterprise users performing bid invitation analysis as analysis objects, and extracting preliminary screening items from the bid invitation database through the analysis objects; according to different target tendency and operation tendency combinations selected by the enterprise user, secondary screening is carried out on the primarily screened items, the matching degree of the recommended items obtained through secondary screening and the requirements of the enterprise user is high, and therefore the auditing efficiency of the enterprise user and the selection probability of the recommendation result are improved.

The invention provides an Internet hospital patient propaganda and education method based on a recommendation algorithm, and the method comprises the steps: collecting the historical browsing behaviors of real-name patients in the hospital Internet, and constructing a relation graph between the patients and propaganda and education articles; mining similarity of propaganda and education articles according to patient behaviors; recommending by utilizing the similarity between the propaganda and education articles; and recommending the first K propaganda and education articles with the highest interest to different patients on the home page of the Internet hospital. Personalized recommendation not only can improve the disease prevention and treatment ability of the patient, but also can guide the public to pay attention to more professional and valuable health propaganda and education knowledge to a certain extent, and has social education significance.

The invention relates to a stereoscopic vision fingerprint signature method and device, electronic equipment and a storage medium. The stereoscopic vision fingerprint signature method comprises the following steps: S1, acquiring a target image containing a hand and an image of signature handwriting; s2, inputting the target image into a plurality of pre-designed algorithms to obtain a normal graph of the target image; and S3, importing the normal graph into a 3D engine to realize stereoscopic vision fingerprint signature. According to the stereoscopic vision fingerprint signature method, multimedia stereoscopic vision fingerprint signature interaction experience is adopted, under the conditions that fingerprints and palmprint of a user are not collected and user privacy is protected, multimedia stereoscopic vision fingerprint signature can be well achieved, user experience is improved through fingerprint signature interaction, and user experience is improved. The attention of users is attracted in a unique and effective mode, the brand popularity and influence are improved, visitors can participate in exhibition or activities in a more visual mode, interactivity and interestingness are enhanced, and the experience feeling of participants is improved.

The present invention relates to the field of data processing technology, and in particular to a streaming data quality monitoring method based on Flink SQL, including: constraining data in a data table with preset field rule data; reading and parsing the field rule data in the database through a Flink application; analyzing the real-time data situation through Flink SQL in combination with a custom operator; the Flink application statistics and stores the data situation analysis results; and initially determining the streaming data quality when Flink SQL in combination with a custom operator analyzes the real-time data situation, and periodically analyzing the analysis results in the database to determine the streaming data quality again. The present invention can monitor streaming data through Flink's combined components and designed operators, ensure and monitor the streaming data quality to a certain extent, and can flexibly change through custom operators and custom rules according to current business conditions.

The invention belongs to the technical field of intelligent control, and particularly relates to a train driving safety guarantee method. The method comprises the following steps: step 1, acquiring a front image in real time when a train travels; judging whether an obstacle area invades or not according to the front image, and if yes, giving out an obstacle invasion alarm or carrying out emergency braking on the train; 2, screening out a lane image when the train travels from the front image, and analyzing the opening direction of a front turnout according to the lane image; and 3, according to the current preset running route of the train, whether the opening direction of the front turnout meets the preset passing requirement or not is judged, and if not, a turnout abnormity alarm is given out so as to prevent switch rail damage or derailment accidents caused by turnout abnormity. The invention provides an efficient, accurate and reliable driving safety guarantee method.

The invention provides an automatic testing method and device based on multiple intelligent algorithms and electronic equipment. The method comprises the following steps: arranging each single intelligent algorithm in a multi-intelligent algorithm into a plurality of test cases for testing the corresponding algorithm according to a preset protocol; according to a preset association degree table, determining the association degree between any two single intelligence algorithms in the multi-intelligence algorithm; according to the correlation degree, calculating the correlation degree quantity of each single intelligence algorithm in the multi-intelligence algorithm; the correlation degree quantity of any single intelligent algorithm is a comprehensive index obtained through comprehensive calculation based on the correlation degree between any single intelligent algorithm and other single intelligent algorithms except the single intelligent algorithm; and according to the association degree quantity, determining a scheduling sequence of cooperative work of each single intelligent algorithm in the multi-intelligent algorithm, and according to the scheduling sequence, scheduling the test case of each single intelligent algorithm to test the corresponding algorithm to obtain a test result of the cooperative work of the multi-intelligent algorithm.

This invention relates to the field of social network analysis technology and proposes a social network sentiment evolution model that integrates user influence and activity. To address the shortcomings of existing technologies, such as inaccurate simulations and inflexible predictions in current network sentiment analysis and sentiment evolution processes, this invention provides a social network sentiment evolution model that integrates user influence and activity. The model analysis method involves: collecting text sentiment data from target users; collecting user influence data from each user; collecting the activity level of the target social network at time t; collecting the forgetting probability of each user at time t as a measure of sentiment evolution capability; establishing a dynamic model for the sentiment evolution of the social network; optimizing the evolution probability of the information propagation model based on text sentiment; and analyzing the evolution process of the dynamic model for the sentiment evolution of the social network based on the optimized information propagation model. This model is suitable for application in social network analysis.

The invention specifically relates to the technical field of computers and the technical field of biological information, and discloses a method and a system for constructing a multi-dimensional database for image recognition of foreign and local diseases and insect pests, and the method comprises the steps: obtaining basic information, hazard feature information and other information of foreign and local diseases and insect pests through self-sampling and public resource collection and processing; analyzing the collected original data set and the scanning image set, and carrying out image preprocessing, data set division, model evaluation and improved construction on the three-dimensional internal and external models and the image recognition model; a foreign and local pest and disease damage multi-dimensional information access rule is constructed, a foreign and local pest and disease damage image recognition multi-dimensional database is developed, data support can be provided for research and development of technologies such as rapid and accurate detection and one-time detection, and the system can become a port entry plant quarantine information support system. The method can certainly play an important role in improving port quarantine and extraneous potential pest control ability, effectively reducing extraneous quarantine pest introduction and protecting agricultural production and ecological safety.

The present invention provides an alkali-resistant and high-temperature-resistant methanogenic archaeon, a culture medium and a screening method. The alkali-resistant and high-temperature-resistant methanogenic archaeon is named MZD129, which has been deposited in the General Microbiological Center of China Microbiological Culture Collection Committee on May 14, 2024. The deposit address is: Institute of Microbiology, Chinese Academy of Sciences, No. 3, Yard 1, Beichen West Road, Chaoyang District, Beijing, with a deposit number of CGMCC No. 41192 and a classification name of Methanoculleus bourgensis The bacteria has the characteristics of high methane production, alkali resistance, high temperature resistance and can grow in a simple synthetic culture medium. The invention effectively overcomes the shortcomings of traditional methanogenic archaea that are difficult to cultivate and have harsh environmental conditions, while realizing the resource utilization of waste and solving the problem of the difficulty in cultivating methanogenic archaea.

The present disclosure relates to the technical field of air conditioners, and in particular to an air conditioner outdoor unit and an air conditioner having same. The present disclosure provides an air conditioner outdoor unit. The air conditioner outdoor unit comprises: a case, an air outlet being formed at the top of the case, and a compressor assembly being provided at the bottom of the case; a fan provided at the top of the case and located at the position of the air outlet; and an electric control box provided in the case, wherein the distance between the bottom of the electric control box and the bottom of the case is Z2, and Z2≥0.8×H, wherein H is the height of the compressor assembly. According to the air conditioner outdoor unit of the present disclosure, on the premise of ensuring normal operation and convenient maintenance of the air conditioner outdoor unit, by reasonably configuring the distance between the electric control box and the bottom of the case, the height direction of the electric control box can be flexibly adjusted, thereby reducing effects of the electric control box on ventilation and noise in the air conditioner outdoor unit.

The invention relates to the technical field of data processing, in particular to a state prediction method and system for power terminal equipment. The method comprises the steps of collecting output current data and output voltage data, and obtaining a first weight coefficient of each output current data according to an inverse proportion relation between the output current data and the output voltage data; acquiring a second weight coefficient of each piece of output current data according to the surrounding data segment of each piece of output voltage data and the first weight coefficient, and acquiring a prediction error of the current output current data according to the second weight coefficient of each piece of output current data; according to the method, the prediction value of the current output current data is obtained according to the prediction error of the current output current data, the abnormal condition of the current output current data is judged according to the prediction value of the current output current data, and then the abnormity of the transformer is judged, so that the accuracy of abnormity detection is improved, and the influence of noise data is avoided.

The invention provides a false data injection attack method for a multi-elastic-joint robot system, and belongs to the technical field of multi-agent network attacks based on computer data processing. Firstly, a multi-elastic joint robot nonlinear dynamic mathematical model is constructed and converted into a high-order all-drive quasi-linear multi-robot system dynamic model based on an all-drive system theory; and then designing a distributed consistency controller containing a linearization item and a neighbor error related item, establishing closed-loop global dynamics and deducing a state analytical solution in combination with equivalent conversion of the model. Designing a false data injection attack strategy, and constructing an attacked system dynamic model; a closed-loop terminal state error in the presence or absence of attacks is taken as a target function, an attack optimization problem is converted into a combinatorial optimization problem, a greedy algorithm is designed by applying a sub-module optimization theory, and a suboptimal solution in polynomial time is obtained and is taken as an optimal scheme of false data injection attacks of the system. According to the method, the applicability of the complex nonlinear multi-agent system is improved, and the calculation complexity is reduced.

The present invention provides a LED driver chip test system and method, and relates to the field of chip testing technology. The method includes: collecting first electrical data in a steady-state load test process and second electrical data in a transient load test process; extracting steady-state index parameters and transient index parameters of multiple load points and determining multiple target load points; constructing an electrical characteristic correlation matrix and an electrical fluctuation correlation matrix corresponding to multiple target load points; performing feature fusion on the electrical fluctuation correlation matrix and the electrical characteristic correlation matrix to generate a target correlation matrix, determining multiple electrical parameter linkage combinations based on the target key matrix, generating a first linkage test scheme for each electrical parameter linkage combination, and performing linkage testing on the LED driver chip based on multiple first linkage test schemes. The present invention achieves the improvement of the effectiveness and comprehensiveness of LED driver chip testing.

The invention provides an acoustic emission positioning method for monitoring a soil caking fracture source, and the method comprises the steps: synchronously collecting acoustic emission signals in a caking load fracture process from a plurality of directions, and removing noise through band-pass filtering; acquiring a main fracture signal time point of each probe and a fracture process signal energy value, and normalizing the energy values; distributing a positioning weight for each probe according to the magnitude of the energy value, and establishing a weighted least square objective function of the caking rupture source according to the deployment position of each probe and the time point of the main rupture signal; solving the target function of the caking rupture source by using a nonlinear least square method to obtain a convergence position of the caking rupture source; and selecting the caking with known fracture position and soil type as a sample for acoustic emission positioning to obtain an optimal acoustic emission positioning parameter for fracture positioning of the caking of the soil type. The method has the beneficial effects that the mechanical structure of soil caking is known, and high-precision positioning of a fracture source in a complex soil environment is achieved.

The invention discloses a commodity display method and device, a computer readable storage medium and a terminal. The method comprises the steps of obtaining search information; performing word segmentation on the search information to determine a search word set; determining the matching degree of each existing commodity by adopting the search word set; determining operation information of each existing commodity, wherein the operation information is at least used for representing whether the existing commodity has a preset operation attribute; weighting operation is carried out at least based on the matching degree and the operation information, display values of the existing commodities are obtained one by one, a preset first weight value is adopted as the weight of the matching degree of each existing commodity, and an adjustable second weight value is adopted as the weight of the operation information of each existing commodity; and sorting and displaying at least one part of the existing commodities based on the display values. According to the method, information of more dimensions can be combined, and the comprehensiveness and systematicness of commodity display are improved.

The application provides a multi-agent cooperative social network information propagation adaptive guidance method and system, which can be applied to the technical field of information propagation guidance. The method comprises the following steps: obtaining long-time characteristics and short-time characteristics of a plurality of users, the long-time characteristics comprising social behavior characteristics of the users in a predetermined historical time period, and the short-time characteristics representing personal views of the users on a predetermined event; constructing a user network according to the long-time characteristics and the short-time characteristics; performing a first structure adjustment process on the user network to generate a first test network; calculating a first difference value between a complexity of the first test network and a complexity of the user network, and determining a first influence representing a first influence generated by information propagation of a target user in the user network based on the first difference value; determining a propagation leading crowd from the plurality of users based on the first influence; obtaining a propagation guidance strategy; and guiding the propagation leading crowd by using the propagation guidance strategy. The scheme provided by the application can improve the effect of information propagation guidance.