66 results about "Indicator matrix" patented technology

The invention relates to a multiple-DC(direct current)-droppoint selection method based on multiple feed-in short circuit ratios, which comprises the following steps of: calculating the multiple feed-in short circuit ratio set M, determining a multiple-DC(direct current)-droppoint scheme, calculating integrated indexes of the scheme, calculating the balance indexes of the scheme, calculating interference indexes of the scheme, standardizing data results of an index matrix, formulating a multiple-DC-droppoint selection strategy, calculating assessed values, comparing the assessed values, selecting the optimal multiple-DC-droppoint scheme under the condition of an AC(alternating current) grid structure, adjusting the AC grid structure, returning to the first step, and comparing the optimal multiple-DC-droppoint schemes under the condition of the AC grid structure. The multiple-DC-droppoint selection method provides assessment indexes and technical basis for the planning and the design of a multiple-DC feed-in power grid, and has the characteristics of simpleness, practical use and strong operability.

The invention discloses a power grid planning risk evaluation system and method based on a grey correlation degree TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). The power grid program risk evaluation system comprises a power grid planning data acquisition module, a power grid planning scheme input module and a controller, wherein the power grid planning data acquisition module and the power grid planning scheme input module are independently connected with the controller; and the controller comprises a power grid risk evaluation index matrix generation module, a power grid risk evaluation index matrix solving module, a grey correlation degree matrix construction module and a power grid planning scheme risk sorting module. The invention has the beneficial effects that the power grid planning risk evaluation system introduces the controller which can process power grid planning data and sort power planning schemes to carry out optimal sorting on power grid enterprise risk indexes, a power grid planning scheme can be evaluated on the whole, potential risks in a power grid planning process can be effectively prevented and solved, power grid planning operation cost is saved, and power grid reliability is improved.

The invention discloses a plant cultivation method based on intelligent data collection and cloud service technology. The method comprises: S1, collecting plant growth indicators, the watering amount,the fertilization amount and the fertilization type, forming an influence factor matrix X, and uploading to the cloud server, wherein the decision variables are the watering amount, the fertilizationamount and the fertilization type; S2, determining plant health indexes, forming an indicator matrix Y, performing training and testing by an Elman neural network, and establishing a plant cultivation model; S3, optimizing the plant cultivation model by using the MOPSO algorithm to obtain a set of optimal solutions for each decision variable and plant health indexes corresponding to the optimal solutions; and S4, predicting the real-time data by using the model in the S3 to obtain a recommended decision X<*>, sending the X<*> to a user terminal, displaying the recommended optimal watering amount, fertilizing amount and fertilizing type in the user interface, a user remotely operating a device control sensor through the user terminal to complete automatic watering and automatic fertilization.

The invention relates to a fuzzy variable-weight engineering geological environment quality evaluation method comprising the following steps: establishing an engineering geological environment quality evaluation hierarchical structure model; acquiring engineering geological data corresponding to all participating indexes in an area to be evaluated; dividing the area to be evaluated into m basic evaluation units; establishing the evaluation index matrix and the variable weight matrix of each basic evaluation unit; calculating the variable-weight comprehensive evaluation value of each basic evaluation unit according to the evaluation index matrix and the variable weight matrix corresponding to the basic evaluation unit; getting the engineering geological environment quality grade of each basic evaluation unit according to the variable-weight comprehensive evaluation value of the basic evaluation unit; and clustering the basic evaluation units of the same engineering geological environment quality grade through use of a clustering method to get an engineering geological environment quality comprehensive evaluation partition map. The method has the advantages of high evaluation precision, objective and reliable evaluation result, and the like.

The invention provides a method and a device for online evaluation of a converter valve state based on grey clustering. The method comprises: acquiring online monitoring data of a converter valve in apreset time period; establishing a state evaluation indicator matrix of the converter valve according to online monitoring data, and calculating a score value of each evaluation parameter class in the state evaluation indicator matrix according to the online monitoring data; respectively constructing a whitening weight function corresponding to each preset gray class according to at least three preset grey classes; according to a preset weight value of each evaluation parameter class and the whitening weight function of the score value of each evaluation parameter class, using a grey clustering algorithm to respectively calculate a clustering weight value of each preset grey class; and evaluating an operating state of the converter valve according to the each clustering weight value. By implementing the method, real-time evaluation of the operating state of the converter valve is realized without manual operation, accuracy of an evaluation result is improved, and potential risk prediction of the converter valve is realized, and provides good data basis for planned maintenance of the converter valve.

The invention is a principal component analysis based capacity optimization planning method for a pumped storage power station, which is characterized in that it includes: establishing a comprehensive evaluation index system for the capacity planning of a pumped storage power station, generating a capacity planning scheme for a pumped storage power station, and constructing a comprehensive evaluation Index matrix, convert the comprehensive evaluation index matrix to the same trend, perform standardized transformation on X′, calculate the correlation coefficient matrix for the comprehensive evaluation index matrix after the standardized transformation, calculate the variance contribution rate and cumulative variance contribution rate of the principal components and select Principal components, calculation of the selected w principal components, calculation of factor loads, comprehensive evaluation of each alternative, and determination of the optimal planning capacity of the pumped storage power station. It has the advantages of scientific and reasonable method, simple and practical, fast calculation speed and higher precision.

The invention discloses a comprehensive early warning decision-making method for operating passenger cars based on typical dangerous working conditions, including: 1) determining the indicators of typical dangerous working conditions, and establishing a matrix model S of early warning indicators; 2) selecting causal monitoring parameters, and building a monitoring matrix model R , the specific monitoring parameter value, to obtain the specific monitoring matrix Ri; 3) establish a weight matrix model K, S=RK according to the monitoring parameter value, establish a specific weight matrix Ki; 4) compare the specific monitoring matrix Ri with the weight matrix Ki 5) According to the size of the matrix Si, determine which working condition the current danger is mainly caused by. The larger the value, the more serious the danger. This method takes large commercial passenger cars as the research object, selects typical dangerous working conditions, selects typical monitoring parameters, establishes weights, and multiplies the real-time monitoring variable matrix with the weight matrix to obtain the real-time driving condition matrix. Select the corresponding dangerous working conditions for early warning, so as to achieve the effect of early warning.

The invention relates to an entropy weight method resistance based photovoltaic power station operation characteristic assessment method, and belongs to the technical field of photovoltaic power generation. The entropy weight method resistance based photovoltaic power station operation characteristic assessment method includes firstly, establishing an assessment indicator system taking electric quantity, energy consumption, efficiency, power generation hours and power station operation hours as indicators, and acquiring the related indictors through collection and calculation; preprocessing the related indicators acquired by calculation to acquire an average indicator matrix; calculating anti-entropies of the indicators according to the average indicator matrix; finally, calculating weights of the indicators according to the anti-entropies and calculating an assessed value of photovoltaic power station operation characteristics according to the weights to realize assessment of the photovoltaic power station operation characteristics. The entropy weight method resistance based photovoltaic power station operation characteristic assessment method has the advantages that a photovoltaic power station performance assessment mathematic model is created through establishment of the assessment indicator system for the photovoltaic power station operation characteristics, so that scientific guidance and shared power station experiences are provided for overall operation performance assessment of photovoltaic power stations, and development of operation and maintenance of the photovoltaic power stations is promoted.

The invention discloses a method and system for optimizing an electricity reliability improving object of an intelligent distribution network. The system includes a data acquisition module, an evaluation module and a storage module. The optimization method includes: establishing an intelligent distribution network electricity reliability improving demand degree evaluation index system; allowing the data acquisition module to acquire the related index data and store the related index data in the storage module; allowing the evaluation module to normalize and nondimensionalize the index values of all the objects to be optimized to form a normalized index matrix; calculating subjective and objective weight values of each index, and calculating a comprehensive weight value of each index; calculating a weighted normalized index matrix, determining positive and negative absolute ideal solutions, and calculating the grey relational degree of each object to be optimized; calculating the relative closeness degree of each object to be optimized relative to the positive ideal solution, optimizing the reliability improving object according to the relative closeness degree, and outputting an optimization result to the storage module. The method and system can comprehensively evaluate the real electricity consumption situation of the users in the intelligent distribution network, and guide the development of the electricity reliability improving project of the intelligent distribution network.

The invention provides a method for evaluating multi-level development potential of whole-loading oil field in high water-cut period based on improved QFD. The core tool of the method is an evaluationhouse, which consists of nine parts, namely a development effect evaluation index matrix, a technical measure matrix, a development effect index and technical measure correlation matrix, a technicalmeasure first-level, second-level and third-level application potential matrix, and a first-level, second-level and third-level development potential matrix. The multi-level development potential of whole-loading oil field in high water-cut period after different technical measures are carried out can be analyzed. Compared with the numerical simulation, the method is simple and convenient: after the mutual correlation matrix is determined, the application potential of various levels of technical measures is evaluated, and the multi-level development potential of the target oil field can be calculated; at the same time, the method also realizes the development potential evaluation corresponding to the technical measures of different grades which are already applied in the local block and are applied in the same block and are to be applied in the test stage, and has higher reference value for the actual production of the mine field.

The invention relates to a power distribution network repair ability assessment method based on improved grey clustering. The method comprises the steps that S1, the analytic hierarchy process is adopted to establish an assessment indicator system; S2, original indicator values of all electric power companies are collected to obtain an original indicator matrix, and the original indicator values are subjected to dimension removal to obtain a standard indicator matrix; S3, the original indicator matrix is normalized, and weights are established for indicators according to the information entropy theory to obtain an entropy weight matrix; S4, a grey clustering method is adopted to set the number of grey clusters and a whitening weight function, and a saturability matrix corresponding to each grey cluster is calculated; S5, fuzzification operation is performed according to the saturability matrix obtained in the step S4 and the entropy weight matrix to obtain a clustering assessed value matrix, and the grey clusters which all the electric power companies belong to are determined according to the maximum value of elements in each row of the clustering assessed value matrix. Compared with the prior art, power distribution network repair ability characteristics can be reflected completely, and a whole set of complete reference basis is formulated for scientific assessment of the power distribution network repair ability level.

A graphical indicator comprises a plurality of first header blocks, a plurality of second header blocks and a plurality of data blocks to form an indicator matrix. Each of the first and second header blocks includes a header graphical micro-unit, and each data block includes a data graphical micro-unit. An array region is formed by the second header blocks and the data blocks. A first virtual line is formed at virtual centers of the first header blocks, and a second virtual line is formed at virtual centers of the second header blocks. The included angle between the first and second virtual lines is smaller than 90 degrees.

A method for modeling an image for multiple tasks includes providing an image with n image features, providing an indicator matrix which has m non-zero components corresponding to the m features selected from the n features, constructing a model of the image using the m selected features for each specific labeling task. There are a variable for a specific task to be performed on the image and a variable for a plurality of tasks to be performed on the image.

A dynamic evaluation method for the running state of an integrated energy system comprises the steps that firstly, multi-stage data of the integrated energy system are collected, and an index system including the technical, economic and environment-friendly integrated energy system is constructed; secondly, analyzing the influence of the indexes on the running state of the integrated energy system, dividing the indexes into benefit type indexes and cost type indexes, and calculating to obtain a standard index matrix; thirdly, inviting an expert group to carry out importance sorting on the index system, comprehensively considering influence factors of experts, and applying a group G1 method to obtain an index weight; then, a TOPSIS method is used, an absolute ideal solution is set, and the close degree is solved; and finally, according to the operation state characteristics of the multi-stage comprehensive energy system, performing dynamic evaluation by using a double-excitation control line principle. According to the method, one-sided reflection of a single type of index on the running state of the integrated energy system is avoided, the development trend of the integrated energy system is considered, the evaluation result can be more comprehensive, and the method is of great significance in guiding running and planning of the integrated energy system.

The invention discloses a power grid peak-valley period division method based on a reverse peak regulation risk caused by new energy output. Firstly, peak and valley membership indexes of each point on a load curve are obtained by utilizing a semi-trapezoidal membership function, a reverse peak regulation risk index is obtained by analyzing new energy output characteristics, index matrix data is standardized by utilizing a translation-standard deviation change method, clustering is carried out by adopting a fuzzy transfer closure method, and a lambda-intercept matrix is solved. Finally, the intra-class and inter-class difference is reflected by establishing a statistic F, the optimal threshold lambda is obtained with the maximum F as the target, and the classification corresponding to theoptimal threshold lambda is the divided peak and valley time periods. According to the method, the reverse peak regulation risk caused by new energy output characteristics is fully considered, and a reliable basis can be provided for peak regulation and reverse peak regulation inhibition of new energy grid connection.

The invention discloses an electric energy meter manufacturer evaluation method based on a multi-attribute decision model, which relates to an evaluation method. The invention comprises the followingsteps: acquiring the original data of the electric energy meter and determining an evaluation index; Calculate each index value of the electric energy meter, construct the index matrix, form the decision matrix; Calculate the information entropy and Spearman grade correlation coefficient of each index value of watt-hour meter, determine the objective weight of the quality evaluation index according to CRITIC method, process the decision matrix and obtain the watt-hour meter supplier evaluation matrix; Calculate the positive ideal solution and negative ideal solution of the watt-hour meter supplier, and calculate the Euclidean distance from each watt-hour meter supplier to the positive ideal point vector and the negative ideal point vector. Calculate the relative approximation degree between each watt-hour meter supplier and the ideal solution, and determine the quality level of each watt-hour meter supplier from high to low. The technical scheme provides an objective and scientific basis for the electric energy meter quality evaluation and supervision of the power grid company.

The invention provides a method for optimizing technical measures of a fault block old oil field based on improved QFD. Based on the basic thought of QFD, a technical decision house is put forward, which consists of an index improvement demand degree matrix, a development effect evaluation index matrix, a technology measure classification type matrix, an evaluation index and technical measure correlation matrix, a technical measure primary importance degree matrix, a technical measure improvement rate matrix, and a development effect improvement matrix; combined with a fuzzy comprehensive evaluation the two-stage expansion method, the complicated technical measures are optimized and ordered, a set of optimized methods for the potential-tapping measures of the fault block old oil field forthe water drive development are formed, and the application of examples is explained. According to the method, a technical decision house model is utilized, the development stage characteristics of the fault block old oil field are fully considered, and by using the production experience accumulated form field measure adjustment, the workload of numerical simulation work is greatly reduced, and the working efficiency is improved. The technical measure optimization method has higher practical application value and reference significance.

The invention discloses an operation state monitoring method for an intelligent vehicle road system. The method comprises the steps of: building an index matrix from the dimensions of an intersection,a road segment and a road network to obtain an operation state index set; aiming at the characteristics of multiple index parameters and different dimensions, adopting a threshold value method to carry out normalization processing on numerical values; determining the dispersion degree of each index by using an entropy weight method, and calculating the weight of the indexes; measuring the calculation deviation between the index values by adopting a weighted total root-mean-square deviation calculation method to reflect the evaluation accuracy; and performing combined weighting on the index set by using entropy weight-weighted total root-mean-square deviation calculation; importing the index set into a deep reinforcement learning neural network, performing multi-layer convolution by usinga gating structure, extracting a feature value, obtaining an optimal index set by using the reinforcement learning network and training a maximized objective function, and performing comprehensive analysis on an IVIS operation condition. Through the scheme, the possibility of absolute concentration of the indexes is reasonably avoided, and the accuracy of the index set is greatly improved.

The patent discloses a running condition monitoring method of an intelligent vehicle-road system. The method comprises the steps that an index matrix is established based on dimensions such as intersections, road sections and road nets, and a running condition index set is obtained; aiming at a characteristic that a lot of index parameters exist and dimensions are different, values are normalizedthrough a threshold method; an entropy weight method is used for judging a dispersion degree of each index and calculating a weight occupied by each index; a calculation method of weighting total root-mean-square deviations is used for measuring calculation deviations between the index values and reflect accuracy of measurement; calculation of entropy weight-weighting total root-mean-square deviations is used for combined empowerment of the index set; and the index set is import into a deep reinforcement learning neural network, a gate control structure is used for multi-layer convolution, characteristic values are extracted, the reinforcement leaning network is applied, an optimal index set is obtained through training of a maximized target function, and comprehensive analysis of IVIS running conditions is realized. By the scheme, possibilities in an index absolute set are avoided rationally, and accuracy of the index set is greatly increased.

The invention provides a graph database-based risk control management system and method for small and medium-sized enterprises, and the system comprises: a data interface unit which is in butt joint with multi-dimensional external data; the index extraction unit that is used for extracting the obtained data according to a preset risk control standard to obtain a risk control index; the first processing unit that is used for carrying out initial assignment on each obtained risk control index to obtain an index matrix and carrying out calculation to obtain a weight distribution matrix; the second processing unit that is used for establishing an evaluation set for each risk control index and carrying out assignment to obtain a corresponding evaluation matrix and carrying out calculation to obtain an evaluation result matrix; the third processing unit that is used for obtaining a risk vector set by combining the weight distribution matrix with the evaluation result matrix; the graph data unit that is used for constructing a graph database according to the data obtained by each unit; the risk control unit that is used for transmitting enterprise data needing to be evaluated to the graph database for processing. The invention has the advantages that an accurate and objective credit risk evaluation system for small and medium-sized enterprises is constructed, and corresponding financial risks are reduced.

The invention discloses a community detection method of comprehensive analysis of a topological structure and node attributes. The method includes the implementation steps of: respectively carrying out single-factor similarity analysis for two factors of the node attributes and the topological structure of nodes of a social network to obtain an initial single-factor community distance set of eachfactor; carrying out decorrelation operation for the initial single-factor community distance set of each factor on the basis of a Spearman correlation coefficient to respectively obtain correspondingcorrected single-factor community distance sets; introducing two-degree distances for the corrected single-factor community distance set of each factor to obtain corresponding comprehensive single-factor community distance sets; carrying out stability weight assignment on the comprehensive single-factor community distance set of each factor to calculate a community distance index matrix; and carrying out community detection from an angle of relation transformation on the basis of the community distance index matrix and fuzzy relation operation. According to the method, correlation errors canbe reduced, weight assignment errors can be reduced, community distance reliability can be improved, and accuracy of community detection can be improved.

The invention relates to a power transaction mechanism operation compliance risk assessment method. The method comprises the steps of constructing a power transaction mechanism operation compliance risk index system; obtaining an original evaluation index matrix based on the constructed power transaction institution operation compliance risk index system, and preprocessing the original matrix to obtain a standardized evaluation index matrix; determining a subjective weight and an objective weight of each evaluation index according to the standardized evaluation index matrix; determining the comprehensive weight of each evaluation index, and obtaining the severity coefficient of the operation compliance risk; and calculating an operation compliance risk coefficient of the power transaction mechanism based on the severity coefficient of the operation compliance risk. Compared with the prior art, the method has the advantages of accurate and reliable evaluation and the like.

The invention discloses a gas field overall layout evaluation method based on multi-level fuzzy comprehensive evaluation. The method comprises the following steps: (1) taking technical economy, dependable conditions and safety production as first-level indexes, refining each first-level index into a second-level index, and establishing a multi-level analysis evaluation index system; (2) determining the weight of each secondary index by using an AHP analytic hierarchy process; (3) constructing an evaluation index matrix; (4) standardizing the evaluation index matrix to obtain a fuzzy relative membership matrix R; and (5) introducing the weight of the secondary index into fuzzy comprehensive evaluation calculation, calculating the relative membership degree of each scheme, and finally determining the optimal scheme of the overall layout of a gas field according to the maximum membership degree principle. The evaluation method has objectivity and provides a certain theoretical basis for comparison and selection of the overall layout scheme of the gas field.

The invention provides a fresh air system control method. The method comprises the steps that data feature extraction is conducted on air quality data packets uploaded by area management servers, and air data index matrixes of all the air quality data packets are obtained; air quality sequences corresponding to all the air quality data packets are determined according to the air data index matrixes and the weight proportions of corresponding data, and reference data packets are obtained; a first air quality weight and a second air quality weight which are used for evaluating the air quality are determined; and finally, a fresh air control strategy of each area is generated and issued to the corresponding area management server so that fresh air equipment of all fresh air control sub-areas of the corresponding areas can be controlled. Through the method, the multiple areas are controlled in a centralized mode, the other areas are coordinated by determining the reference areas, and thus the control strategies for the fresh air equipment of all the areas are generated; and compared with traditional unified control strategies, the control strategies are more intelligent and accurate.

The invention provides a variety identification method and system based on component structure characteristics, and relates to the technical field of variety identification, and the method comprises the steps: obtaining the content data of a target component substance contained in a sample to be identified; Converting the content data into component data of relative percentage closed structure characteristics; Establishing a sample index matrix according to the component data; Converting the sample index matrix into an Euclidean space to obtain a new sample index matrix; And identifying the variety of the to-be-identified sample according to the new sample index matrix to obtain the identification accuracy of the to-be-identified sample. According to the variety identification method and system based on the component structure characteristics provided by the embodiment of the invention, the substance varieties can be identified more objectively and reliably, and the identification accuracy is effectively improved.

The invention relates to a comprehensive performance evaluation method of a numerical control machine tool based on an improved pull-out method, which belongs to the technical field of performance evaluation of a numerical control machine tool. The linear proportional method is used to standardize the data of various performance indicators of the machine tool. The subjective weights of indicators at all levels are determined based on the ordinal relationship analysis method, the two objective weights of indicators at all levels are determined by the entropy weight method and the mean square error method, and the subjective and objective weight information is synthesized based on the principle of vector Pearson correlation coefficient. The comprehensive weight is used to weight the index, the final weight coefficient of the index is determined by the positive definite matrix corresponding to the weighted index matrix, and the comprehensive evaluation value of the three-level index is obtained based on the linear weighted evaluation function. Finally, a similar method is used to calculate the comprehensive evaluation value of the large system layer by layer. The invention is used for the comprehensive performance evaluation of various numerical control machine tools and the horizontal comparison of the specific performance of different machine tools, and provides a scientific and operable evaluation method and process for the comprehensive performance evaluation of the machine tools.

The invention discloses a stock transaction point prediction method and system based on a minimum entropy score, and a storage medium. The method comprises the steps: obtaining stock data, obtaining the technical indexes of a plurality of transaction days according to the stock data, and constructing an index matrix according to the obtained technical indexes; calculating a future return rate according to the stock data, obtaining a trend grade according to the future return rate, and obtaining a data matrix in combination with the trend grade and the index matrix; mining a stock trend mode ofthe data matrix by adopting a biclustering algorithm based on a minimum entropy score to obtain a transaction rule; and predicting transaction operations in combination with the transaction rules anda preset neural network, wherein the transaction operations include selling, no operation and buying. According to the method, the biclustering algorithm based on the minimum entropy score can effectively help to find transaction information and rules hidden behind stock historical data, transaction prediction information with high reference value can be provided for investors, and the method canbe widely applied to prediction of stock market transaction operation.

The invention provides a residual oil dispersion degree characterization method. The remaining oil dispersion degree characterization method comprises the steps that S1, an oil reservoir numerical simulation model of a to-be-measured area is established, and then production history fitting is conducted; S2, according to the parameters obtained in the step S1, residual oil abundance of different time steps is calculated through a residual oil abundance formula; S3, the high-abundance continuous oil phase is identified, namely remaining oil patches, in the step S2 by using a neighborhood boundary tracking algorithm, the area and perimeter of each remaining oil patch, the total number of the remaining oil patches and other attributes are obtained, and the average patch area MPS, patch densityPD and average shape index MSI are calculated. and S4, an index matrix is formed by using the average plaque area MPS, the plaque density PD and the average shape index MSI of different time steps obtained in the step S3, and then calculating is performed to obtain the residual oil dispersity of different time steps through an entropy weight method. According to the invention, the problem of lackof a residual oil dispersion degree characterization method in the prior art is solved.