72 results about "Quantitative classification" patented technology

The invention discloses a reservoir classification method based on rock electricity parameters, and belongs to the field of hydrocarbon reservoir evaluation. The method is based on rock electricity experiment theoretical model deduction, a theoretical value range and a value trend of rock electricity experiment data of reservoirs under different pore structures are formed, and reservoir pore structure subareas on a rock electricity data F-phi plate are formed; and corresponding electrical logging data are utilized in combination with rock electricity experiment data and mercury injection capillary pressure curve data to determine rock electricity method quantitative classifications, and the method at least includes: Step 1) establishing a rock electricity method classification bases; Step 2) forming a classification plate; Step 3) establishing a quantitative classification evaluation basis; and Step 4) determining classification grades of the reservoirs. According to the reservoir classification method based on rock electricity parameters in the invention, by checking distribution of the rock electricity data on the F-phi plate and discovering that rock samples of reservoirs of different classes fall on distinguishable different subareas on the F-phi plate, continuous evaluation knowledge can be provided, and a verification effect is good.

A wearable device is disclosed. From one or more sensors sensing health information of a user, a wearable device automatically obtains at least one health related measurement. The wearable device computes at least one of a vitality index and a health index based on at least one health related measurement and classifies, based on the vitality and health indices, the health of the user into some predetermined health condition classes. The wearable device then transmits the classified health condition class(es), via network connection, to a health service engine and receives health assistance information that is adaptively determined in accordance with the health condition class(es).

A real time health monitor deployed on a mobile device is disclosed. From one or more sensors sensing health information of a user, the real time health monitor automatically obtains at least one health related measurement. The real time health monitor computes at least one of a vitality index and a health index based on at least one health related measurement and classifies, based on the vitality and health indices, the health of the user into some predetermined health condition classes. The real time health monitor then transmits the classified health condition class(es), via network connection, to a health service engine and receives health assistance information that is adaptively determined in accordance with the health condition class(es).

The invention discloses a user data processing system which comprises a user data capture module, a data integration processing module, a quantitative classification statistics module, a residence track analysis module, a store resource database, a store resource updating module, a management server and a guide push initiation module. The user data capturing terminal is respectively connected withthe quantitative classification statistics module and the data integration processing module; wherein the quantitative classification statistics module is connected with the comprehensive quantitative evaluation module through the resident trajectory analysis module, the commodity resource database is connected with the comprehensive quantitative evaluation module, and the management server is respectively connected with the data integration processing module, the comprehensive quantitative evaluation module, the store resource database and the guide push initiation module. According to the invention, the user position information and the consumption record are analyzed to determine the preference and interest of the user, so that the guidance information can be accurately pushed to guidethe user to shop, the satisfaction degree of the user is greatly improved, and the sales of commodities in the shopping mall is promoted.

The invention discloses a health insurance risk evaluation system based on biological information. The health-insurance risk evaluation system comprises a risk evaluation database system, a database search engine and a biological underwriting and examination risk index analysis system, wherein the risk evaluation database system is connected to the biological underwriting and examination risk index analysis system by the database search engine. The risk evaluation database system comprises a historical risk evaluation database, a realistic risk evaluation database, a predictive risk evaluation database, a financial risk grade evaluation database, a biological recognition risk evaluation database, a health insurance underwriting index library and an actuarial rate index library. The biological underwriting and examination risk index analysis system comprises a biological gene detecting subsystem, a human health pre-warning subsystem and a biological underwriting and examination risk control subsystem. The health insurance risk evaluation system disclosed by the invention adopts a multi-dimensional information database set with quantitative classification of information, combines the biological information to evaluate the health insurance, and is beneficial to reducing the evaluation risk and reducing the underwriting cost.

Disclosed are a quantitative classification frame system of original cigarettes and a frame technology of the crude tobacco. The quantitative classification frame system comprises a double-line leaf distributing, cutting and releasing machine, a first leaf base conveyor and a first non-leaf base conveyor, wherein the double-line leaf distributing, cutting and releasing machine is used for cutting off the original cigarettes and classifying the same into leaf bases and non-leaf bases, and the first leaf base conveyor and the first non-leaf base conveyor are contrary in conveying direction. By the quantitative classification frame system, both quantitative classification frame and quantitative mixed frame can be performed upon leaf base parts and non-leaf base parts.

The invention relates to a reservoir compressibility evaluation method based on cluster analysis of logging petrophysical facies division. The method includes the steps: acquiring the brittleness index profile of a target block according to the rock mechanics parameter test result of coring data and interval transit time data; acquiring petrophysical response characteristic data of the target block, acquiring reservoir physical property parameter logging data of the target block, and according to the brittleness index profile, the petrophysical response characteristic data and the reservoir physical property parameter logging data of the target block, dividing reservoir petrophysical facies classes based on a cluster analysis method by using a K-nearest neighbor algorithm and a core representative index; and evaluating the compressibility of a target well according to the petrophysical facies classification result. The method solves the technical problem that a single compressibility evaluation result of the prior art is not representative, and the reservoir compressibility quantitative classification result can be obtained based on the cluster analysis method.

The invention relates to a prior knowledge-based multi-modal ethnic identity sense quantitative measurement method and belongs to the intelligent pattern recognition and ethnology research crossing filed. According to the measurement method, ethnic minority emotion pictures are adopted as basic materials; ethnic minority identity sense survey questionnaire questions are converted into the induction materials of electrophysiological signals; after the EEG information of subjects is acquired, the EEG information implying identity senses is classified through a fuzzy neural network learning-basedEEG emotion feature extraction and classification algorithm; questionnaire survey results and EEG classification results are fused, so that ethnic identity sense quantitative measurement is realized;and the objective feeling of the subjects for the ethnic identity sense and national identity sense can be automatically analyzed. With the method of the invention adopted, the subjective influence of questionnaire surveys can be decreased, the objectivity of identity sense classification can be enhanced, and ethnic identity sense quantitative classification is more accurate and more efficient.

The invention belongs to the technical field of traffic engineering, and relates to a bus stop optimization setting method in view of quantitative classification. The method comprises the following steps of 1, setting improvement on traffic capacities of a bus stop and adjacent roads as an optimization target; 2, building a bus stop comprehensive service level assessment model, and determining a quantitative classification standard; 3, building a bus stop optimization measure set; and 4, quantitatively classifying the bus stop comprehensive service levels under different optimization measures,and selecting the optimal optimization measure. According to the method provided by the invention, the optimized bus stop setting method is systematically quantized, the traffic capacity of the bus stop and the traffic capacities of the adjacent roads are integrated to form the bus stop comprehensive service level, the assessment model and the quantitative classification standard are built, the optimization measure set is built by using berth numbers and stop types as basic elements, and the optimal optimization measure of the bus stop is finally acquired through quantitatively classifying the bus stop comprehensive service level under the different optimization measures.

The invention, which belongs to the power grid field, relates to a risk assessment and assistant decision-making method and system for the regional grid operation. The method comprises: S1, acquiringrelated information of a grid as an input condition; S2, searching for a weak point of the grid and providing a possible accident analysis result and a corresponding processing measure and advice based on quantitative classification of a risk evaluation index; and S3, generating a risk assessment report to assist in the analysis of a grid operation risk, carrying out visual displaying, and carrying out a graphical simulation operation. According to the invention, the weak point of the grid is searched quickly by using the related information of the grid mode as the input condition, the possible accident analysis result as well as the corresponding processing measure and advice is provided, and the risk assessment report is generated to help the dispatcher analyze the grid operation risk. Therefore, quasi-synchronous safety assessment of the grid operation mode is realized; the workload of the operation dispatcher is reduced substantially; the risk assessment integrity and accuracy areimproved; and the power supply reliability of the grid is enhanced.

The invention discloses a classification evaluation method for a complex fault block reservoir. The method includes the following steps: (1) performing fine reservoir description on a target complex fault block reservoir and establishing a fine geological model; (2) performing numerical reservoir simulation to modify and improve the fine geological model; (3) utilizing the modified and improved fine geological model to obtain geological classification evaluation index parameters; (4) performing classification evaluation on the target complex fault block reservoir according to quantitative criteria of the geological classification evaluation index parameters. According to the method, main control factors affecting the reservoir development effect are selected as the classification evaluation index, and the quantitative classification evaluation criteria are utilized to comprehensively judge the development difficulty of the complex fault block reservoir, so that a comprehensive classification evaluation result of the reservoir is more reasonable, and the method has more promotion value.

The invention relates to a method for estimating the signal quality of MSK and O-QPSK signals. Firstly, the signal quality of MSK and O-QPSK signals is estimated based on the statistical characteristics of a chip. Secondly, the chip synchronization is established, and the establishment of the chip synchronization is before the synchronization of spread spectrum code phases and the synchronization of frames. Thirdly, with the assistant of a chip symbol synchronization signal, the simple nonlinear operation of a baseband signal and the simplified linear average of an operation result are carried out, and the high resolution estimation of the current signal quality can be rapidly obtained. The signal quality can be accurately estimated in a short time, an estimation value is subjected to delicate quantitative classification, and the accurate use of the estimation value by an upper application is facilitated.

The invention relates to a quantitative classification calculation method for quantitatively describing the demands of different positions in an urban park-and-ride facility attraction demand range and belongs to the urban traffic planning field. The method comprises the following steps that: a virtual analysis network of a park-and-ride facility attraction demand range area is constructed according to demand point samples and geographic coordinate positions which are obtained through investigation; the distribution density of sampled demand points is calculated through using a kernel function in probability theory; and the total demand density of each position in the facility attraction demand range is calculated and classified through using an adaptive kernel density analysis theory and a numerical value superposition method. The quantitative classification calculation method can be utilized to quantitatively analyze demand intensity distribution of each point at different directions and different distances in the park-and-ride facility attraction demand range, and can classify the demands in the facility attraction demand range through the total demand density, and has a favorable role of reference in the determination and analysis on distribution characteristics of the park-and-ride facility attraction demand range, and provides a new method for park-and-ride facility demand forecast.

The invention relates to a device for detecting pesticide residue and a detection method. The device comprises a pesticide residue fast detection card, a power supply, a device main body, a temperature control assembly, a camera and a controller; the temperature control assembly and the camera are respectively used for heating at constant temperature and shooting according to the control of the controller. The detection method comprises the following steps: (1) respectively obtaining the reference image of extracting solution of the matter to be detected and the standard image of the extracting solution of the matter without pesticide residue by the device; (2) respectively calculating the tone, saturability and brightness corresponding to each pixel point in the reference image characteristic region and the standard image characteristic region; (3) having quantitative classification process on the corresponding tone, saturability and brightness to obtain the reference quantization series weight vector and the standard quantization series weight vector, calculating the degree of association between the reference quantization series weight vector and the standard quantization series weight vector; (4) obtaining the average degree of association, the average degree of association is more close to 1 and the pesticide residue is less. The operation process is simplified, and the pesticide residue is detected exactly and quickly.

The invention provides a preparation method of ceramic balls implanted with a quantum technology function. The method comprises the steps as follows: S1, material selection: different types of commonor functional ceramic ball products are selected; S2, component analysis; S3, specific gravity measurement; S4, classification: quantitative classification is performed according to the component proportion and specific gravity measured in the steps, and the indexes are used as quantum technology frequency modulation implantation indexes; S5, quantitative analytic statistics; S6, quantum implantation; S7, sorting and packaging: products treated in S6 are weighed and sorted, packaging is performed according to the quantitation of packaging bags, and the products are obtained. The method has thebenefits as follows: the preparation process is very simple, safe and practical, has wider application ranges and good safety, causes no pollution and meets the environmental protection requirement.

The invention discloses a tongue colour sensing and quantitative classification method combining an equal interval scale with a classificatory scale in the traditional Chinese medicine, which belongs to the field of objectifying researches on the inspection diagnosis of the traditional Chinese medicine. According to the tongue colour sensing and quantitative classification method disclosed by the invention, a visual psychophysical method is adopted to solve the problem of quantitative classification for tongue colours in the dimensionality of the description rule of the traditional Chinese medicine. According to the tongue colour sensing and quantitative classification method disclosed by the invention, a part of representative tongue colour blocks are taken out from the colour gamut range of the tongue colours and used as sensing simulation quantity values; the description rule of tongue colour scales in the tongue diagnosis of the traditional Chinese medicine is used as the guidance basis of psychological perception evaluation for performing psychophysical experiments, establishing the equal interval scale and classificatory scale of psychological perception, and determining the psychological perception quantities of the tongue colours and the boundaries of the various scales; the psychological perception quantities meeting the tongue colour description rule of the traditional Chinese medicine and corresponding to the tongue colour physical quantities are obtained by creating a mathematic relationship model between the tongue colour physical quantities and the psychological perception quantities, and the scales of the psychological perception quantities are determined. The tongue colour sensing and quantitative classification method disclosed by the invention has the characteristic of realizing tongue colour one-dimensional sensing and quantification meeting the tongue diagnosis description custom of the traditional Chinese medicine, and determining classification boundaries, thus achieving the purpose of really combining the tongue colour quantitative description with the tongue colour qualitative description of the traditional Chinese medicine.

The invention provides a neural network quantitative classification method and system. The neural network quantitative classification method and system are different from the prior art in which only the weight of the neural network model is classified and quantized. According to the method and the system, statistical processing, classification processing and weight quantification processing are carried out on the input information of each layer in the neural network model, so that proper weight quantification processing can be carried out on the output information of each layer in a targeted manner; therefore, the precision of the output information of each layer is improved to the maximum extent under the same quantization bit number. According to the method and the system, the output information of each layer of the neural network model is sorted; in this way, a proper calculation mode can be selected according to the respective output channel characteristics of the output information of each layer, so that the neural network model can obtain the optimal calculation efficiency and reduce the power consumption required by hardware operation during hardware operation.

The invention relates to a method for determining quantitative classification of altered pyroclastic glutenite reservoirs, which comprises the following steps: 1. Selecting a plurality of wall core orrock core samples in pyroclastic glutenite reservoirs, carrying out research analysis on the plurality of wall core or rock core samples, determining the clay content of the wall core or rock core samples, and distinguishing the value of the clay content; 2, determining the alteration argillization degree of the pyroclastic glutenite reservoir in the wall core or rock core sample, and classifyingthe alteration argillization degree of the pyroclastic glutenite reservoir; 3, determining the effectiveness classification of the pyroclastic glutenite reservoir; performing reservoir classificationthrough the alteration index and the reservoir quality factor, and when PI is larger than or equal to 0.05 and SH is smaller than or equal to 0.00, the reservoir is a first-class reservoir; when PI is smaller than -0.035 and SH is larger than 0.020, the reservoir is a three-class reservoir; and the reservoir between the first-class reservoir and the third-class reservoir is the second-class reservoir. According to the invention, the argillization alteration degree of the pyroclastic glutenite reservoir can be quantitatively described; moreover, a reservoir classification standard is established, and a foundation is laid for subsequent glutenite reservoir well logging evaluation.