37 results about "Fuzzy vector" patented technology

The invention belongs to the evaluation technical field, and particularly relates to an improved water environment safety evaluation analysis method. The improved water environment safety evaluation analysis method includes the steps of based on the relation of interaction between influence factors, based on the combination of the improved network analysis method and fuzzy mathematics, mainly on the basis of building system network analysis, carrying out pairwise comparison on the influence factors under different criterions, obtaining weight vectors comprising the interaction, combining fuzzy vectors obtained through the fuzzy evaluation method to carry out calculation and analysis, and finally obtaining the safety evaluation results. The improved water environment safety evaluation analysis method is accurate in evaluation result, improves the pre-alarm accuracy, achieves the aim of building a water quality safety evaluation model, increases the time correction value and ensures that the weight vectors can accurately and always reflect the relative importance degrees between the influence factors at different moments.

The invention provides a power distribution network project investment decision technology considering comprehensive effects. The power distribution network project investment decision technology comprises the following steps: s1, establishing a multi-dimensional power distribution network investment comprehensive effect evaluation index system; s2, determining an evaluation index set and a comment set, and establishing a fuzzy relation matrix of evaluation indexes; s3, carrying out comprehensive weight calculation by using an analytic hierarchy process and an entropy weight method; s4, obtaining a final evaluation result according to the product of the comprehensive evaluation fuzzy vector and the weight vector of the index. Calculation case analysis shows that the investment decision ofthe power distribution network project can be scientifically and comprehensively supported, and the method has good application and popularization prospects.

The invention relates to a power grid operation safety risk evaluation method. The method comprises the following steps: an evaluation index set and a comment set are determined; a fuzzy relation matrix for secondary indexes in the evaluation index set is built; weights of primary indexes and secondary indexes are determined respectively, and weight vectors of the primary indexes and the secondary indexes are obtained respectively; the product of the weight vectors of the secondary indexes and the secondary index fuzzy relation matrix is calculated, and a comprehensive evaluation fuzzy vector of the primary indexes is obtained; and the product of the comprehensive evaluation fuzzy vector of the primary indexes and the weight vectors of the primary indexes is calculated, a power grid operation risk comprehensive evaluation vector is obtained, and the grade of a comment corresponding to the maximum value in the power grid operation risk comprehensive evaluation vector is regarded as a final evaluation result. The safety risk evaluation accuracy and the objectivity can be improved, and safe and stable operation of the power grid are ensured.

The invention provides a knowledge graph optimization method based on the fuzzy theory, and the method comprises the steps: obtaining the triple data of a training set, and carrying out the preprocessing of all the triple data;constructing a knowledge graph based on fuzzy relation synthesis to obtain a fuzzy relation of the knowledge graph; and based on the loss function, minimizing a target optimization function, and obtaining an optimized triple vector which is the triple set of the optimized knowledge map. According to the invention, a fuzzy vector operation method is used for carrying outoperation on training data of each dimension; According to the knowledge graph optimization method based on the fuzzy theory, semantic information given to data in fuzzy logic is combined with the deep learning theory, experiments show that the knowledge graph obtained through the knowledge graph optimization method based on the fuzzy theory is more comprehensive and accurate, and the optimized knowledge graph has higher accuracy in the aspects of link prediction and triple classification.

The invention relates to a method for evaluating the coincidence rate of an actual drilling borehole trajectory and a design track, and belongs to the technical field of petroleum and gas drilling. The method comprises the steps that the actual drilling borehole trajectory and the design track are unified to a coordinate system by measuring the well mouth coordinate and altitude of the actual drilling borehole trajectory; then the well depth, well deviation and orientation of the actual drilling borehole trajectory are measured, the vertical depth, east-west coordinate and north-south coordinate of an actual drilling well are figured out and standardized to be fuzzy vectors, the close degrees between the fuzzy vectors of the vertical depth, east-west coordinate and north-south coordinate of the actual drilling well and the fuzzy vectors of the vertical depth, east-west coordinate and north-south coordinate of the corresponding design borehole track is calculated, finally, the average value of the close degrees is figured out, and the average close degree is used for evaluating the coincidence rate of the actual drilling borehole trajectory and the design borehole track. By means of the method, quantitative judgment is achieved, human active factors are overcome, and the coincidence rate of the actual drilling borehole trajectory and the design track is objectively reflected.

An elevator reliability prediction method based on an unbiased grey fuzzy Markov chain model is presented. When the elevator breaks down, the fault code is extracted, recorded and the historical datais obtained. The unbiased GM (1, 1) model is established according to the historical data, and the residual error of the model is checked. The residual value interval is divided into m states, fuzzy function is constructed by fuzzy classification theory, fuzzy state probability vector of each data point is calculated, and the state of each data point is determined according to the maximum membership principle. The Markov state transition matrix is established to predict the fuzzy vector of the fault next time, and the membership state of the predicted data is determined according to the maximum membership principle. The invention predicts the reliability of the elevator, obtains the time interval trend of the occurrence of a certain fault through an unbiased GM (1, 1), approaches the datafluctuation trend by utilizing the anti-interference property of the fuzzy Markov chain, and slides the Markov chain, so that the reliability prediction result of the elevator is more accurate.

The invention discloses a robust image watermark detecting method based on fuzzy classification. The robust image watermark detecting method comprises the following steps: in a watermark-containing image correcting process, extracting an eight-circumcircle lower PHT matrix (low 7-order), obtained by circumcircle lower PHT decomposition, of a to-be-detected image, taking the eight-circumcircle lower PHT matrix as a training characteristic to combine with a fuzzy support vector machine theory, training a sample to obtain a training module for performing geometric correction. The fuzzy vector machine FSVM has very good learning capacity and the matrix obtained by PHT decomposition has high precision, so that watermark information under different attacks can be correctly extracted, and the watermark robustness is improved. Moreover, the method has the characteristics of simple calculation, no need of an initial carrier during watermark extraction, and the like, so that the copyright protection practicability of digital image works is strengthened.

The invention discloses a frequency converter S-curve acceleration / deceleration sudden change control method. The method includes the following steps that: current frequency signals are acquired, first deviation signals are calculated, so that whether sudden change occurs on a frequency converter in an acceleration / deceleration process can be judged; second deviation signals are calculated, and the first fuzzy vector of a fuzzy controller is obtained; a deviation change rate is calculated, and the second fuzzy vector of the fuzzy controller is obtained; the fuzzy control quantity of the fuzzy controller is obtained, and the exact quantity of S-curve acceleration / deceleration circular curve time is obtained; and real-time output information is calculated by means of an S-curve acceleration / deceleration algorithm. With the method of the invention adopted, given rotation speed at an output rotation speed real-time tracking sudden change time point can be ensured when an intelligent fuzzy control method gives sudden change in an S-curve acceleration / deceleration process, and the stability of a system can be improved.

The invention discloses an assessment method of pile sinking of ocean platform taking consideration of risk level classification. The method includes the following steps: classifying risk levels of pile sinking; establishing a system of assessment indexes and classifying the risk levels for all the assessment indexes, confirming the comparison matrix and using the average and range method to construct the judgment matrix to determine the weights of all the assessment indexes, determining the membership grade of each risk level for each assessment index, establishing a fuzzy mathematical model to solve the fuzzy vector of the pile sinking risk level for the ocean platform and based on the principle of the largest membership grade making the assessment about pile sinking risk level of the ocean platform. The invention provides an assessment method based on AHP and fuzzy mathematical theory, applies the method of risk levels classification to give an assessment to the pile sinking of ocean platforms. The assessment results are more close to the actuality. The method is suitable for the assessment of pile sinking risks of ocean platforms.

The invention discloses a fuzzy control-based oil well paraffin removal method and system. The method includes the following steps that: input variables are determined, wherein the input variables comprise a paraffin precipitation deviation value and a time deviation value; and the input variables are fuzzified with a language variable, so that fuzzy input variables are obtained; the fuzzy input variables are inputted into a fuzzy controller, a fuzzy vector is determined according to a fuzzy control rule; the fuzzy vector is defuzzicated, so that a fuzzy output quantity can be obtained; and the second-stage-fire time and three-stage fire time of oil well paraffin removal are determined according to the fuzzy output quantity and on the basis of a second-stage-fire time adjustment rule anda three-stage fire time adjustment rule. With the method and system of the invention adopted, high-efficiency well washing can be realized, yield can be increased, and oil extraction energy consumption can be reduced.

The invention discloses an evaluation method for the existing use quality of an asphalt pavement. The method comprises the following steps: selecting an asphalt pavement on which the existing use quality is to be evaluated; according to an existing standard basis, analyzing and selecting an existing use quality evaluation index of the asphalt pavement; determining the selected existing use quality evaluation indexes as a factor set of a multi-level fuzzy evaluation method; according to the principle of a multi-level fuzzy evaluation method, determining a comment set for evaluating the existing use quality of the asphalt pavement; and performing matrix synthesis operation on the weight matrix and the multi-level fuzzy comprehensive evaluation matrix to obtain a fuzzy vector of multi-level fuzzy evaluation of the existing use quality of the asphalt pavement, and evaluating the existing use quality of the asphalt pavement based on the fuzzy vector. According to the invention, the multi-level fuzzy evaluation method is adopted to evaluate the existing use quality of the asphalt pavement, a new method is provided for evaluating the existing use quality of the asphalt pavement, and meanwhile, the method has important guiding significance for accurately judging the maintenance opportunity of the asphalt pavement.

The present invention proposes a method for accurately analyzing quality of adjustment and control. The method comprises the following steps: S1, building an adjusting and controlling system database of a power grid; S2, building a real-time alarm monitoring analysis index, and calculating a signal response score Sa; S3, monitoring and obtaining patrolling data of substations, and calculating an evaluation score Sb of patrolling situations of the monitored substations; S4, building a quality index tree, wherein the quality index tree comprises a tree node R, an intermediate node mi and a leaf node 1j; bringing the real-time alarm monitoring analysis index and the patrolling data of the substations in the quality index tree; analyzing indexes by taking the quality index tree as a frame, and then obtaining grade fuzzy vectors Vq and j of the index, namely, an adjusting and controlling quality index of a controller; and obtaining the reliability for adjusting and controlling the power grid and a best adjusting and controlling scheme according to the adjusting and controlling quality index of the controller. The method is rapid and effective, thereby improving the adjusting and controlling quality of the controller for the substations and the reliability for adjusting and controlling the power grid.

The invention discloses an energy-saving control system and an energy-saving control method, based on vectorization analysis, for a heating and ventilation circulating water system. The energy-savingcontrol system comprises a water temperature transmitter, a working condition parameter sampling unit, a parameter monitoring unit, a variable-frequency control calculating unit, an output inverting unit, a frequency converter and a circulating water pump. By adopting a membership degree vector decomposition method, a sampling object value is decomposed into a multi-dimensional membership degree vector, and at the moment the sampling object changes are also decomposed to a plurality of dimensionalities. A membership degree function is reasonably selected to make sure that the change value of the sampling object is reflected to different sub-vectors of the membership degree vector in different value ranges, and thus an effect of obviously showing variation tendency. The system and the method disclosed by the invention realize look-ahead assuagement of state transition of the system by assuaging the tendency. Slowly-responding system variables in an air conditioning system are subjectedto fuzzy vector analysis so as to amplify the system state transition tendency reflected in small-amplitude changes of the system variables, and the running state of the system is regulated accordingto the tendency so as to maintain the running stability.

The invention discloses a meteorological decision support method and a meteorological decision support device based on a T-S model, and relates to the technical field of agrometeorological information. The method comprises the following steps of: acquiring meteorological parameter data, and generating a meteorological factor vector; executing fuzzification for the meteorological factor vector, and generating a meteorological factor fuzzy vector; determining a fuzzy decision rule based on a built T-S model, executing decision calculation for the meteorological factor fuzzy vector according to the fuzzy decision rule, and outputting a control quantity; and executing decision regression detection for the control quantity. The meteorological decision support method and the meteorological decision support device based the on T-S model, provided by the invention, are based on a fuzzy control algorithm of the T-S model, organically fuse agricultural experience data, improve analysis and processing capacity of agrometeorological data, can effectively solve problems, such as non-effective use of agrometeorological information and agricultural knowledge experience, and have very important significance for intelligent decision in wisdom agriculture production, avoiding influence of meteorological environment mutation and promoting crossed fusion of the information technology and the agricultural production management field.

A routine test range wireless communication system comprehensive performance evaluation method provided by the invention comprises: establishing an evaluation index; leading in an analytic hierarchy process to determine the evaluation index weight; leading in the fuzzy theory to determine the fuzzy vector of each index; and performing multistage fuzzy comprehensive evaluation, and determining the comprehensive performance evaluation. The routine test range wireless communication system comprehensive performance evaluation method ensures that the indexes are mutually independent as far as possible and have no crossing redundancy.

The invention discloses an interaction control method for improving the safety of an automobile product based on virtual reality. The method comprises the following steps: establishing a hierarchicalstructure model by utilizing an analytic hierarchy process; forming a set by taking various factors influencing the evaluation object as elements; taking a set composed of various results made by an evaluator for the evaluation object as an evaluation set of comprehensive evaluation; if the membership degree of the ith element in the factor set U to the first element in the evaluation set V is ri1, representing the result of single-factor evaluation of the ith element by using a fuzzy set; forming a matrix Rm * n by taking m single-factor evaluation sets R1, R2-Rm as rows, and taking the matrix Rm * n as a fuzzy comprehensive evaluation matrix; giving a weight ai and a fuzzy set of a weight set of each factor ui to each factor ui; after the single-factor evaluation matrix R and the factorweight vector A are determined, changing the fuzzy vector A on the U into the fuzzy vector on the V through fuzzy change, determining the final score of the operation part and if the score is smallerthan a threshold value, improving the operation part.

The invention provides a noise reduction parameter determination method. The method comprises the following steps: acquiring a noise reduction signal sample output by a loudspeaker and an error signal sample collected by an error microphone; performing fuzzy quantization processing on the error signal sample and the noise reduction signal sample to obtain an error signal sample fuzzy vector and a noise reduction signal sample fuzzy vector; determining a fuzzy control mapping relation between the error signal sample fuzzy vector and the noise reduction signal sample fuzzy vector; and determining a noise reduction parameter based on the error signal sample fuzzy vector, the noise reduction signal sample fuzzy vector and the fuzzy control mapping relation. By combining with fuzzy control, noise reduction parameters can be determined without establishing a mathematical model with an accurate acoustic path, the design cost of the active noise reduction system can be remarkably reduced, based on the characteristics of fuzzy control, the active noise reduction process combined with the fuzzy control has intelligence and high efficiency of processing a nonlinear time-varying process, and the active noise reduction effect is obviously improved.

The invention relates to a coincidence rate determining method and system of a really drilled well and a designed well belonging to the petroleum and natural gas drilling technical filed. The method comprises following steps: determining comparison items and element values thereof of the really drilled well and the designed well according to drilling engineering design and real drilling data; setting weight values according to the significances of the comparison items; calculating and evaluating item element subordinating degrees through a subordinating degree function and constructing fuzzy vectors; calculating the close degrees of the fuzzy vectors of corresponding comparison items; and calculating the total close degree of the comparison items according to the weight values of the comparison items in an item weight module. According to the method and the system of the invention, the coincidence rate of the really drilled well and the designed well is described according to the close degrees of the fuzzy vectors; the evaluation quantification is realized; the artificial subject judgment is reduced; the evaluation is more scientific; and the method and the system have very important significance in drilling post-evaluation.

The invention belongs to the evaluation technical field, and particularly relates to an improved water environment safety evaluation analysis method. The improved water environment safety evaluation analysis method includes the steps of based on the relation of interaction between influence factors, based on the combination of the improved network analysis method and fuzzy mathematics, mainly on the basis of building system network analysis, carrying out pairwise comparison on the influence factors under different criterions, obtaining weight vectors comprising the interaction, combining fuzzy vectors obtained through the fuzzy evaluation method to carry out calculation and analysis, and finally obtaining the safety evaluation results. The improved water environment safety evaluation analysis method is accurate in evaluation result, improves the pre-alarm accuracy, achieves the aim of building a water quality safety evaluation model, increases the time correction value and ensures that the weight vectors can accurately and always reflect the relative importance degrees between the influence factors at different moments.

The invention relates to a method for recognizing type of fluid flowing into a well, and belongs to the technical field of oil and gas well drilling and well completion. The method comprises the following steps: measuring viscosity of to-be-recognized fluid flowing into the well at different revolving speeds at first and converting the viscosity into shearing rate and shearing stress; calculating rheological parameters of types of various fluids and calculating shearing stresses corresponding to the types of the various fluids under the various actually measured shearing rates according to a rheological equation of the fluids; respectively carrying out standard treatment on the shearing stress of the to-be-recognized fluid and the shearing stresses corresponding to the types of the various fluids and establishing a corresponding fuzzy vector; and calculating close degrees, comparing the close degrees, and taking the fluid corresponding to the maximum close degree as the type of the to-be-recognized fluid. A common rotational viscometer is used for measuring data, and through calculation of the close degrees, the type of the fluid flowing into the well is recognized. The method has the advantages of high recognition capability, wide recognition range, high recognition accuracy and the like, and has quite important significance on hydraulic calculation and rheological parameter control.

The embodiment of the invention discloses a power signal filtering method and system using a deblurring operator. The method comprises the following steps: step 1, inputting an actually measured powersignal sequence S; and step 2, performing noise filtering processing on the power signal sequence S, wherein the power signal sequence after noise filtering is SNEW. Specifically, D is a deblurring matrix, gamma is a fuzzy factor, mu is a deblurring factor, alpha is a deblurring adjustment factor, WOPT is a fuzzy vector, and lambda OPT is a defuzzification vector.

The application discloses a self-adaptive fuzzy data uploading method based on NB-IoT. A data uploading time point of equipment is an optimization control object and a reference input is a data uploading time point of the current equipment; error comparison is carried out on a communication result and original data; when an error signal e occurs, an error signal e is selected as an input quantityof a fuzzy controller; fuzzy quantization is carried out on an accurate quantity of an error signal to form a fuzzy quantity; the fuzzy quantity of the error e can be expressed by a corresponding fuzzy language and thus a subset E of the fuzzy language set of the error e is obtained; fuzzy decision making is performed on the E (fuzzy vector) and a fuzzy control rule R (fuzzy relationship) according to a reasoning synthesis rule to obtain a fuzzy control quantity U. In order to apply accurate control to a controlled object, the fuzzy quantity U needs to be subjected to non-fuzzy processing to be converted into an accurate quantity, and after an accurate digital quantity is obtained, a data uploading point of the equipment is modified, so that an optimal uploading time point is finally foundthrough loop optimization.

The invention relates to a method for evaluating the coincidence rate of an actual drilling borehole trajectory and a design track, and belongs to the technical field of petroleum and gas drilling. The method comprises the steps that the actual drilling borehole trajectory and the design track are unified to a coordinate system by measuring the well mouth coordinate and altitude of the actual drilling borehole trajectory; then the well depth, well deviation and orientation of the actual drilling borehole trajectory are measured, the vertical depth, east-west coordinate and north-south coordinate of an actual drilling well are figured out and standardized to be fuzzy vectors, the close degrees between the fuzzy vectors of the vertical depth, east-west coordinate and north-south coordinate of the actual drilling well and the fuzzy vectors of the vertical depth, east-west coordinate and north-south coordinate of the corresponding design borehole track is calculated, finally, the average value of the close degrees is figured out, and the average close degree is used for evaluating the coincidence rate of the actual drilling borehole trajectory and the design borehole track. By means of the method, quantitative judgment is achieved, human active factors are overcome, and the coincidence rate of the actual drilling borehole trajectory and the design track is objectively reflected.

The invention discloses an assessment method of pile sinking of ocean platform taking consideration of risk level classification. The method includes the following steps: classifying risk levels of pile sinking; establishing a system of assessment indexes and classifying the risk levels for all the assessment indexes, confirming the comparison matrix and using the average and range method to construct the judgment matrix to determine the weights of all the assessment indexes, determining the membership grade of each risk level for each assessment index, establishing a fuzzy mathematical model to solve the fuzzy vector of the pile sinking risk level for the ocean platform and based on the principle of the largest membership grade making the assessment about pile sinking risk level of the ocean platform. The invention provides an assessment method based on AHP and fuzzy mathematical theory, applies the method of risk levels classification to give an assessment to the pile sinking of ocean platforms. The assessment results are more close to the actuality. The method is suitable for the assessment of pile sinking risks of ocean platforms.

The invention provides a fuzzy vector morphological filtering method based on hypercomplex description. The method includes the steps of carrying out hypercomplex description on each pixel of a color image to obtain three components representing pixel features, carrying out opening operation and closed operation on each pixel in the image in sequence and then obtaining a filtered image. According to the fuzzy vector morphological filtering method based on the hypercomplex description, hypercomplex numbers are utilized to describe the color image, a fuzzy lexicography sequence is led in, and consequently the fuzzy vector morphological filtering method has good recovering effects on the color images which are polluted by impulse noise.

The invention relates to a power grid operation safety risk evaluation method. The method comprises the following steps: an evaluation index set and a comment set are determined; a fuzzy relation matrix for secondary indexes in the evaluation index set is built; weights of primary indexes and secondary indexes are determined respectively, and weight vectors of the primary indexes and the secondary indexes are obtained respectively; the product of the weight vectors of the secondary indexes and the secondary index fuzzy relation matrix is calculated, and a comprehensive evaluation fuzzy vector of the primary indexes is obtained; and the product of the comprehensive evaluation fuzzy vector of the primary indexes and the weight vectors of the primary indexes is calculated, a power grid operation risk comprehensive evaluation vector is obtained, and the grade of a comment corresponding to the maximum value in the power grid operation risk comprehensive evaluation vector is regarded as a final evaluation result. The safety risk evaluation accuracy and the objectivity can be improved, and safe and stable operation of the power grid are ensured.

The invention discloses a warm mix asphalt mixture construction process effective compaction time control method and a warm mix asphalt mixture construction process effective compaction time control system, which are applied to the technical field of traffic construction. Fuzzy variables and a fuzzy set of the fuzzy variables are determined, and the fuzzy variables are divided; determining a discourse domain table according to the division result of the fuzzy variables and the corresponding relation of the fuzzy sets; constructing fuzzy inference rules, and obtaining different fuzzy relation equations according to different fuzzy inference rules; and obtaining an output value according to the fuzzy vector value in combination with different fuzzy relation equations, and determining an accurate value through a defuzzification method. According to the fuzzy analysis method for the effective compaction time of the asphalt mixture, the requirement of surface layer construction can be basically met, and especially when the air temperature is lower than 20 DEG C or other environment conditions are severe, prediction of the effective compaction time of the asphalt mixture has important significance. And when the environmental condition is better and the surface layer is thicker, the compaction time of the asphalt mixture can meet the requirement of normal rolling work.

The invention discloses a clustering correction method, system and medium for phase unwrapping of a multi-baseline interferometric synthetic aperture radar, and the method comprises the steps: calculating the integer ambiguity number corresponding to each pixel in each interferogram according to the parameters of the multi-baseline interferometric synthetic aperture radar, and obtaining the fuzzy vector of each pixel; clustering the pixels with the same fuzzy vectors into the same class; performing class correction on the pixels in the interferogram: if the size of the interferogram is smaller than a preset size value, performing class correction on all the pixels according to the maximum class in the expansion area of the pixels; if the size of the interferogram exceeds the preset size value, judging whether the pixel needs to be corrected or not according to the density of the expansion area of the pixel, and then carrying out class correction on the pixel needing to be corrected according to the maximum class in the expansion area of the pixel. According to the invention, the accuracy and effectiveness of the pixel clustering result of the phase unwrapping of the existing multi-baseline interferometric synthetic aperture radar can be improved, and the precision of the unwrapping phase is further improved.