125 results about "Product analysis" patented technology

The invention relates to the technical field of green product analysis, and discloses a green product full life cycle analysis system based on big data. The system comprises a data acquisition module, a preprocessing module, an environmental impact assessment module, a resource consumption optimization module, an association modeling and result generation module and a visual interaction module. The system collects data of all stages of a full life cycle and related element data of environment, resources, carbon emission and the like, after preprocessing of abnormal value elimination, entropy weight method weighting and the like, environment influence is dynamically evaluated through a fuzzy membership function, resource consumption is subjected to multi-objective optimization by utilizing a genetic algorithm, and the resource utilization rate is improved. A key stage is determined by means of grey relational degree, an analysis result is generated in combination with a multi-target decision model, and finally the analysis result is visually presented in the form of a three-dimensional map and a dynamic thermodynamic diagram. The system realizes efficient analysis and comprehensive evaluation of full-life-cycle data of green products, and provides scientific support for product environment performance optimization and decision making.

The invention provides a neutron dose evaluation method and system based on mobile phone neutron activation product analysis, and the method comprises the steps: constructing an equivalent medium model for replacing a real mobile phone, and carrying out the neutron energy spectrum solving through the mobile phone activation product. The neutron energy spectrum can be reconstructed on site in daily scenes without professional equipment, such as villages, streets and shopping malls, so that the uncertainty of individual dose is reduced to a level equivalent to that of a laboratory spectrometer, the dependence on a multi-ball spectrometer, a TOF spectrometer and professionals is thoroughly eliminated, rapid and accurate measurement of the neutron energy spectrum and large-scale population dose evaluation are realized, and the accuracy of the neutron energy spectrum is improved. And a basis is provided for delimiting the influence range of the nuclear event, judging the event level of the nuclear event and formulating a hierarchical medical rescue scheme.

The invention relates to the technical field of market analysis, in particular to a brand positioning optimization method based on big data, and the method comprises the steps: collecting multi-channel brand performance data, calculating a mean value, extracting a co-occurrence relation between emotion words and labels in comments, judging an emotion and image matching structure, and analyzing competing product label frequency difference and cognitive overlap. And identifying a user portrait and emotion offset, and merging expression gaps to generate an optimization suggestion scheme. According to the method, differentiated collection and unified coding are performed on multi-channel indexes, a brand expression structure capable of cross comparison is constructed, data definition is improved, comment words and brand labels form a co-occurrence matrix, an emotional expression structure under the value dimension is extracted, competitive product analysis locates a cognitive blank on the basis of label difference and coverage degree, and the competitive product analysis accuracy is improved. The emotion deviation value and the label acceptability are introduced as dynamic parameters by user division, and finally a fusion label missing and emotion space is output, expression reconstruction and crowd adaptation are completed, and dynamic linkage and positioning updating of a brand structure are realized.

The invention discloses an agricultural product quality safety full-chain tracing system based on multi-node cooperation, and relates to the technical field of agricultural product analysis. Comprising a history acquisition module, a map construction module, an analysis node module, an analysis uplink module, an analysis management and control module, a query display module and a comprehensive rectification module, wherein the history acquisition module is used for acquiring full-chain data of various fruits in recent 3-5 years and preprocessing the acquired data; the map construction module is used for carrying out feature extraction and correlation analysis on the preprocessed full-chain data of various fruits; according to the technical key points, technologies of knowledge graph, block chain link-by-link chaining, unique fruit coding, nodal quality evaluation and consumer feedback rectification are comprehensively used, so that full-process tracing is realized, data in each link is ensured to be real and traceable, production, logistics, supervision and consumer multi-node collaborative participation are promoted, and the system is suitable for large-scale popularization and application. The method provides support for follow-up exception cooperative processing and system iteration, and has a good use prospect.

The invention discloses an APP response time analysis method based on a deep neural network and distributed computing, and belongs to the technical field of software testing. The method comprises the following steps: loading a video by recording an APP page, and splitting and preprocessing the video frame by frame by using a distributed CPU server to generate reasoning data; and the central GPU server performs reasoning based on the trained deep network model, judges the state of each frame, determines accurate starting and ending frames of page loading through a distributed post-processing mechanism, and accurately calculates the loading time perceived by a user. According to the method, the loading time perceived by the user is accurately reflected, and the method is suitable for cross-platform competitive product analysis; resource utilization is optimized through intelligent distributed calculation, large-scale video processing time is greatly shortened, meanwhile, an automatic decision-making mechanism is introduced, manual intervention cost is reduced, and full-automatic efficient performance testing and analysis are achieved.

The invention relates to the technical field of big data and is applied to the fields of finance and medical health. The invention discloses a visual data integration method and device, computer equipment and a storage medium. The method comprises the following steps: determining entities, attributes and relationships based on business requirements, and forming document metadata; on the basis of the document metadata, generating an interface prototype according to user demand research and competitive product analysis results; generating a graphic component for operating the interface prototype and realizing a dragging function to obtain a data model; and storing the data model in a selected storage medium, and recording version information for a terminal to backtrack and compare historical version information. By implementing the method provided by the invention, the development efficiency can be remarkably improved, and meanwhile, the consistency of data and the expansibility of the system are ensured, so that non-professional developers can also efficiently participate in the development and maintenance of the application program, the technical threshold is greatly reduced, and complex business requirements are met.

Ensure that promotional content for products recommended for sale is provided appropriately. [Solution] A program that causes a computer to perform the following operations: acquire product analysis information associated with each of a plurality of products and used to analyze the sales of the plurality of products; extract target products from the plurality of products whose product analysis information satisfies specified conditions based on the product analysis information; and send proposal information associated with the target products and proposing the creation of content using the target products to a target sales representative.

The present invention discloses a smart marketing management method and system based on AI artificial intelligence. The smart marketing management system includes a data collection and preprocessing module, a market dynamics prediction module, a competitive product analysis module, an advertising strategy generation module, and a strategy execution and feedback module. The smart marketing management system collects relevant data on marketing advertisements in the market, collects market dynamics data, monitors and updates the advertising strategies and market performance of competitive products in real time, and automatically adjusts advertising delivery strategies through AI artificial intelligence technology based on competitive product analysis results and real-time advertising effect data. Through the introduction of AI technology, market and competitive product data can be analyzed in real time, advertising strategies can be automatically adjusted, advertising content and delivery channels can be optimized, and advertising budgets and time frequencies can be dynamically adjusted. This system is not only highly intelligent and automated in advertising decision-making, but also achieves a reasonable allocation of marketing resources through multi-dimensional optimization strategies, significantly improving the overall effectiveness of advertising and the rate of return on investment.

The invention discloses a corrosion analysis method and system for a heat exchanger, and the method comprises the steps: data collection, nondestructive testing, corrosion product analysis, building of a corrosion prediction model, and comprehensive analysis, and combines the nondestructive testing result, the corrosion product analysis result and the output of the corrosion prediction model. The corrosion condition of the heat exchanger is comprehensively analyzed, and the corrosion type, the corrosion reason and the corrosion development trend are determined. The system comprises a data acquisition unit, a nondestructive testing unit, a corrosion product analysis unit, a corrosion prediction model establishment unit and a comprehensive analysis unit. According to the invention, the formation characteristics of granular dirt in the heat exchanger and the harm to heat transfer in the prior art are solved.

The invention provides an equipment control method based on sludge anaerobic fermentation product analysis, and relates to the technical field of sludge treatment.The method comprises the steps that initial feature information of current sludge before fermentation is obtained, and the initial feature information comprises the moisture content, volatile solids and / or the carbon-nitrogen ratio; acquiring the actual content of a fermentation product at a first time node according to preset key time nodes in the anaerobic fermentation process; inputting the sludge initial feature information into a preset machine learning model to obtain the predicted content of the fermentation product corresponding to the first time node; calculating a content difference value between the actual content and the predicted content of the product, and when the content difference value exceeds a preset threshold value, inputting the content difference value into a preset parameter adjustment model to obtain a corresponding parameter adjustment quantity; and adjusting the current fermentation parameters according to the parameter adjusting quantity. The problem that in the prior art, the fermentation state is difficult to monitor according to product information of sludge with different characteristics in the fermentation process, and consequently the parameter control precision of fermentation equipment is low is solved.

The invention relates to the technical field of electric drive NVH of new energy vehicles, and discloses a method and system for formulating an electric drive NVH order noise target value. The system comprises a vehicle performance positioning analysis module, a competing vehicle noise analysis module, an acoustic simulation analysis module, a rack sound attenuation calculation module, an electric drive NVH noise target value making module and a verification and optimization module. The method comprises the following steps: determining positioning of a vehicle type carrying an electric drive; nVH related data of competitive vehicle models are collected; setting an in-vehicle NVH noise target value; analyzing sound attenuation characteristics of the whole vehicle; calculating the sound attenuation of the rack; an NVH order noise target value of the electric drive rack is formulated; and verifying and optimizing. The scientific and systematic method for formulating the electric drive NVH order noise target value is provided, the factors such as market positioning, competitive product analysis and whole vehicle sound attenuation of the whole vehicle can be comprehensively considered, the reasonable noise target value is formulated for electric drive, and the driving comfort and market competitiveness of a new energy vehicle are improved.

The invention discloses an intelligent marketing platform based on an AIGC technology, which belongs to the technical field of marketing and comprises a modeling module, a product analysis module, a marketing processing module and an effect analysis module. The modeling module is used for establishing a marketing copywriting model according to a marketing demand of a user; the product analysis module is used for analyzing a target product, obtaining marketing input data and sending the marketing input data to the marketing processing module; the marketing processing module is used for performing marketing processing, acquiring marketing input data, and analyzing the marketing input data through a marketing copywriting model to obtain a preset number of marketing copywriting; screening the marketing copywriting to determine a target copywriting; setting marketing content according to the target copywriting, and matching a corresponding delivery platform for delivery according to the marketing content; and the effect analysis module is used for evaluating the putting effect of the marketing content to obtain corresponding marketing effect data, and displaying the marketing effect data to the user.

The invention provides a method and a kit for detecting genotypes of SNP (single nucleotide polymorphism) sites in target genes by cascade amplification, and the method comprises the following steps: designing a first primer, a second primer and a medium probe aiming at the target genes containing to-be-detected SNP sites, and designing an amplification probe according to a medium sequence of the medium probe, and designing a detection probe according to the single-chain report sequence of the amplification probe, and carrying out PCR amplification and amplification product analysis in a reaction system containing the upstream first primer, the second primer, the medium probe, the amplification probe, the detection probe, a nucleic acid sample containing the target gene and DNA polymerase. The method is a non-target-dependent detection method, a melting peak with a melting point of a certain duplex body is detected in melting curve analysis, the target gene SNP typing corresponding to the duplex body can be judged, and by means of the advantages of PCR amplification and two times of PCR index amplification by combining the medium primer and the amplification probe, the SNP typing of the target gene corresponding to the duplex body can be judged. A large amount of target nucleic acid can be enriched, and the detection sensitivity is improved.

This invention relates to the field of detection technology and provides a liquid chromatograph for product analysis. The open-top box has a shock-absorbing support at its bottom, on which the liquid chromatograph body is mounted. An exhaust pipe is connected to the liquid chromatograph body, with one end extending outside the open-top box and connected to a condensing mechanism. The condensing mechanism is connected to the open-top box. A cylindrical body is connected to one side of the open-top box via a second fixing plate, and a housing is fixedly connected to one side of the cylindrical body. The bottom of the housing is connected to the cylindrical body via a connecting pipe, and a filtration mechanism is connected to the housing. The bottom of the cylindrical body is connected to the liquid inlet of the liquid chromatograph body via a flexible hose. This invention filters out debris from the extract using several filter screens. The filtered extract is then introduced into the cylindrical body through the connecting pipe and passes through several filter screens to filter out debris from the test solution, preventing debris from clogging the internal pipes of the liquid chromatograph body.

The present invention provides a primer combination, a kit, a detection system, a detection method and an application for detecting pathogenic gene mutations of familial Alzheimer's disease and APOE genotypes by means of constant temperature multiplex rapid detection. The method of the present invention uses the amplification refractory mutation system technology combined with the nicking endonuclease nucleic acid detection reaction isothermal amplification system to perform multiplex amplification on 14 sites including 12 hot spot mutations and 2 risk sites of the Alzheimer's disease pathogenic gene, and at the same time combines capillary electrophoresis for product analysis to perform genotyping detection.

The invention discloses an electrocatalyst high-throughput screening platform for an electrocatalytic reaction system and a method thereof. According to the platform, a flowing electrolytic tank and a high-flux pipetting workstation are taken as cores, and gas chromatography (GC) and nuclear magnetic resonance (NMR) rapid product analysis are integrated. The platform adopts an aluminum alloy gantry type four-axis (XYZ1Z2) moving mechanism to realize space positioning of clamping and pipetting; the high-flux pipetting workstation is provided with a gun head storage module, a reagent bottle storage module, a rotary bottle cap module and an electrocatalyst preparation module, so that accurate liquid proportioning and electrocatalyst preparation are realized; a flowing electrolytic tank and the like are arranged in the electrochemical test workstation, so that continuous flowing electrolysis, automatic sample loading and electrolyte circulation are realized; the GC / NMR module is used for rapidly detecting a product on line. The platform realizes whole-process unmanned and repeatable catalyst preparation and high-throughput screening through a unified control circuit and an upper computer. The electrocatalytic reaction system is a carbon dioxide reduction reaction system.

The invention relates to the technical field of advertisement management, in particular to a cross-border e-commerce advertisement management system based on big data, which comprises a behavior data acquisition module, an associated commodity analysis module, a consumption amount management module and a consumption period and advertisement putting module. According to the fact that all users still browse other commodities when browsing the commodity, associated commodities corresponding to the current commodity are determined to serve as commodities for advertising, a consumption amount management module calculates and determines commodity prices in the advertising, and then a consumption cycle and advertisement advertising module analyzes consumption cycles corresponding to specific types of commodities; and if the current time interval is in a certain specific commodity consumption period in the specific types of commodities, calling out the associated commodities corresponding to the specific commodities after the user logs in the cross-border e-commerce system, generating an advertisement and putting the advertisement to the user, and accurately pushing the associated commodity advertisement when the user is in the commodity consumption period.

The invention provides a trimming die shearing fault analysis early warning method and device based on product analysis, and relates to the technical field of fault early warning, and the method comprises the steps: continuously collecting shearing product features outputted by a trimming die, and generating a product feature time sequence; carrying out product abnormal modal positioning; when the abnormal modality of the product is instantaneous abnormity or no abnormity, performing qualified characteristic fluctuation rule analysis, and generating qualified characteristic fluctuation rule information; performing product feature one-way trend verification to generate a one-way trend verification result; and generating first reminding information for fault early warning. The technical problems that in the prior art, due to the fact that quality fluctuation analysis of qualified products is lacked, shearing fault early warning is not timely, and production quality is affected can be solved, potential fault early warning is carried out through qualified characteristic fluctuation rule analysis and one-way trend verification under the condition of instantaneous abnormity or no abnormity, and the production quality is improved. The technical effects that the timeliness of shearing fault early warning is guaranteed, and then the production quality is guaranteed are achieved.

The invention discloses a detection device for chemical oil product analysis, and relates to the technical field of chemical oil product analysis, the detection device comprises an oil drum conveying mechanism and a detection mechanism, the detection mechanism is arranged on one side of the oil drum conveying mechanism, the detection mechanism comprises a machine shell and a detection assembly arranged in the machine shell, and a liquid pumping assembly is installed at the bottom of the detection assembly; the liquid pumping assembly is arranged above the oil drum conveying mechanism, the machine shell is connected with a touch display controller, and the touch display controller is electrically connected with the detection assembly. According to the chemical oil sampling device, accurate position adjustment and positioning can be conducted on oil barrels through the guide fence, the protection frame, the longitudinal adjustment assembly and the position detection assembly, the liquid pumping assembly can rapidly and accurately sample each barrel of chemical oil, then samples are sent to the detection assembly to be detected, the delivery quality is guaranteed, unqualified products can be removed from an assembly line, and the production efficiency is improved. And workers can quickly process unqualified products.

The application discloses a product analysis method and system based on a life cycle-system level data chain model, realizes transparent recording and tracing of product life cycle data through a decentralized data storage platform of a block chain, applies smart contract technology, accurately cooperates global and local decisions, and breaks the collaboration bottleneck of a traditional manufacturing system. Meanwhile, the problem of small sample data imbalance is solved by using a distributed sharing mechanism of the block chain, and the data credibility and the overall availability of the system are improved. On the basis of the decentralized data storage platform, a product life cycle and system level double digital main line block chain data model is established, an intelligent manufacturing data analysis and knowledge learning model is established in a method domain, the block chain is combined with edge computing, data processing is more efficient and intelligent, the intelligent level of the manufacturing system is further improved, and a comprehensive, efficient and intelligent solution is provided for digital transformation.

The invention relates to the technical field of battery manufacturing, in particular to a QMS defective product analysis and tracing method based on the battery manufacturing industry, which comprises the following steps of: according to battery product performance requirements and safety standards, quantifying a defective product rate target, defining a standard of deviation between the purity of a positive electrode material and the capacity of a battery cell, and obtaining coating thickness deviation and welding strength parameters; equipment operation state information input by an operator and a raw material batch number provided by a supplier are fused, acquisition parameters are compared with a preset standard in real time, data exceeding a threshold value are marked, and a multi-dimensional quality feature data set is established. According to the invention, multiple dimensions of quality planning, quality control, defective product analysis, tracing, quality improvement and the like are integrated, and a set of systematized and standardized QMS defective product analysis and tracing method in the battery manufacturing industry is formed. A supplier management and control system is established by formulating clear targets and standards in the quality planning stage, and defective products are prevented from being generated from the source.

The invention provides a method for determining the form of a silver mineral, and belongs to the technical field of process mineralogy. The method comprises the following steps of silver ore sample preparation, first-time automatic mineralogy analysis, layer-by-layer stripping and repeated analysis, substance composition measurement and coefficient calculation, comprehensive morphological parameter calculation and morphological statistics. According to the method, through a strategy of combining'surface layer-by-layer analysis-three-dimensional parameter reconstruction 'and'process product analysis-distribution behavior analysis', accurate quantification of two-dimensional / three-dimensional forms (such as length-width ratio, thickness and complexity) of the silver minerals is realized, and the process mineralogy characteristics of different types of silver minerals are disclosed synchronously; comprehensive and accurate data support is provided for silver ore crushing particle size optimization, sorting process selection and process evaluation, and the defects that a traditional method is single in form information and insufficient in correlation with process behaviors are overcome.

The invention discloses a vehicle product analysis decision method, device and equipment. The method comprises the following steps: calling a pre-constructed knowledge search tool based on a pre-constructed large model for vehicle product analysis and decision, searching first vehicle use scene information, first vehicle product project information and first vehicle product constraint information associated with the vehicle product demand analysis data from a pre-constructed vehicle knowledge base; based on the first vehicle product constraint information, determining a plurality of vehicle product decision factors matched with the vehicle product demand analysis data, calling a pre-constructed constraint and risk assessment tool, and based on the plurality of vehicle product decision factors, determining a vehicle product risk assessment result; and generating a vehicle product analysis decision result corresponding to the vehicle product demand analysis data based on the first vehicle use scene information, the first vehicle product project information and the vehicle product risk assessment result. Therefore, the accuracy of vehicle product analysis decision can be improved.

The invention discloses a precise pyrolysis regulation and control and product analysis system and method for urban biomass solid waste, and relates to the technical field of solid waste treatment. Comprising a material characteristic prediction module which is used for carrying out pyrolysis behavior characteristic prediction through a machine learning prediction model after preprocessing urban biomass solid wastes, and obtaining a corresponding pyrolysis behavior characteristic report; the process pyrolysis regulation and control module is used for constructing a feature target vector according to the pyrolysis behavior feature report and a user product quality target, acquiring a corresponding candidate process track through a deep learning prediction model, and adjusting the candidate process track in real time according to product quality data in a pyrolysis reaction treatment process; and the product collection module is used for collecting and analyzing products obtained after the pyrolytic reaction is carried out according to the candidate process tracks. According to the method, the problem of unstable product quality caused by raw material fluctuation in a traditional method can be solved, and the reliability of pyrolysis behavior prediction is improved.

The invention discloses an intelligent live video marketing system based on big data analysis and artificial intelligence decision, which comprises a marketing product analysis unit, a self-adaptive processing analysis unit and a marketing information management output unit, relates to the technical field of intelligent live video, and solves the problem that the number of real-time bullet screens is large and cannot be answered one by one. In order to solve the technical problem that the marketing effect of live broadcast is reduced due to the fact that an appropriate marketing mode cannot be adopted according to user requirements in the prior art, marketing products are classified, the marketing conditions of the marketing products are analyzed in combination with historical data, and calculation is carried out by utilizing artificial intelligence in combination with real-time bullet screens in a live broadcast process, so that the marketing effect of the live broadcast is improved. According to the method, the current marketing mode is adjusted according to the calculation result, meanwhile, the adjusted marketing mode is monitored, the overall marketing efficiency is improved by increasing marketing activities, then, the requirements of users can be met by analyzing the real-time bullet screen, and the overall live marketing effect is further improved.

The invention discloses an industrial product surface defect rapid detection and classification method, and relates to the technical field of product defect detection.The method comprises the steps that industrial product surface data are collected and preprocessed, and product analysis data are generated; comparing the product analysis data with a set product analysis standard to output product analysis labels, the product analysis labels including a product detection defect label, a product detection abnormity label and a product detection normal label; re-detecting the product with the generated product detection abnormal label to obtain a re-detected product analysis label; performing data calling on the generated product detection defect label to obtain analysis data of the product with the defect, and performing defect reason tracking based on the analysis data of the product with the defect; according to the method, the threshold value of the number of times of abnormal reinspection is set for the generated abnormal detection label, the product detection label is dynamically updated according to the threshold value of the number of times according to the reinspection result, and false detection or missing detection caused by accidental factors is avoided.

The invention discloses a gene detection platform based on a micro-fluidic chip, which integrates an operation platform, the micro-fluidic chip, a control system, an automatic pipetting device and the like, and is characterized in that a plurality of independent detection channels are arranged on the micro-fluidic chip; each detection channel is provided with a PCR amplification chamber, an amplification product analysis chamber, a two-way pump, a waste liquid collection chamber, a three-way electromagnetic valve and the like, and the detection platform can realize full-automatic liquid preparation, nucleic acid extraction (whole blood mode, omitting the step), PCR amplification, denaturation, molecular hybridization and the like on the basis of the micro-fluidic chip. And the whole process of the steps of result storage, interpretation and the like is automatic, so that the integrated detection requirement of'sample feeding and result outputting 'is met. Meanwhile, the kit is applied to the detection of thalassemia genes, and specific primers and probes are designed and screened to obtain the thalassemia detection kit, and the kit has the advantages of being convenient to operate, high in detection precision, low in cost, visual in result interpretation and the like.

The application discloses an experimental platform for microwave plasma assisted metal and water reaction, which comprises a combustion adjusting system, a fuel comprehensive supply system, a microwave plasma generating system, a diagnosis system and a comprehensive control system; wherein the combustion adjusting system comprises a premixing chamber and a combustion chamber which are sequentially communicated from bottom to top, a rectifier and an igniter are arranged in the premixing chamber, and the rectifier is used for controlling the uniformity of mixed gas; the combustion chamber comprises a microwave combustion assisting zone, an observation and diagnosis zone and a product analysis zone which are sequentially distributed from bottom to top, a back pressure valve is arranged at the top of the product analysis zone, and the back pressure valve is used for regulating and controlling the reaction pressure in the combustion chamber. The application constructs a stable and accurate comprehensive experimental platform, can better observe and study the influence of microwave on the combustion of metal and water reaction and analyze specific influencing factors, and powerfully promotes the research on judging the combustion dominant mechanism and the like.

The invention belongs to the technical field of mineral product analysis, and discloses a mineral product component detection device and method.The mineral product component detection device comprises a mounting ring, and the rear end of the outer wall of the mounting ring is fixedly connected with a fixing plate; a sampling assembly for sampling and drilling a rock core, a crushing assembly for crushing an ore rock sample and a detection mechanism for detecting the sample are distributed on the front side of the outer surface of the mounting ring in an annular array manner by taking the circle center of the mounting ring as an axis; and a driving assembly used for driving the sampling assembly, the crushing assembly and the detection mechanism to work is mounted at the rear end of the outer surface of the mounting ring, and the driving assembly comprises a motor. Through the driving assembly, a single motor drives the multiple assemblies to work cooperatively, power input is provided by a single driving source while the multiple assemblies achieve different effects, and it is ensured that depth detection can be conducted on the rock core.