41 results about "Pairwise comparison matrix" patented technology

The application provides a multi-channel analysis method and a multi-channel analysis device based on an analytic hierarchy process. The method comprises the steps of: acquiring a sub-target of each channel and an index corresponding to each sub-target, building a sub-target layer paired comparison matrix table by using the sub-targets corresponding to the channels as factors, building an index layer paired comparison matrix table by using the indexes corresponding to the sub-targets of the channels as factors, computing a weight coefficient corresponding to each sub-target of each channel according to the sub-target layer paired comparison matrix table, computing a weight coefficient corresponding to each index in each sub-target of each channel according to the index layer paired comparison matrix table, acquiring a quantity value of each channel at the same index, setting an effect value of each channel at each index according to the quantity value, and weighting the weight coefficients and the effect values to obtain a final assessing score of the channel. According to the multi-channel analysis method and device based on the analytic hierarchy process, a more scientific and accurate multi-channel assessing result can be provided.

The invention discloses a mixed multiattribute group decision making method for network frame reconstruction scheme evaluation. The mixed multiattribute group decision making method comprises the steps that the quantitative attribute and the qualitative attribute of each subsystem in power system subareas are determined, a decision matrix is built, and the object weight of the attributes is determined according to the decision matrix; different decision makers in the group decision making process judge the relative importance of the attributes by using a pairwise comparison matrix or a fuzzy complementary judgment matrix respectively, the subjective weight is obtained, the subjective weight and the objective weight are combined to form a combination weight, a network frame reconstruction scheme is evaluated based on the combination weight and the decision matrix, and an optimal scheme and an alternative scheme are obtained. The method has the advantages that certain variables incapable of being given precisely and variables incapable of being precisely quantized in the restoring process are fully considered, the reliability and flexibility of the decision are improved, and restoring delay or even restoring failures caused by immature quantification methods and attribute precision are avoided.

The invention discloses a spectrum allocation method based on graph coloring and an analytic hierarchy process in cognitive radio. The method comprises the following steps: 1, establishing a recursion order hierarchy structure; 2, constructing paired comparison matrixes; 3, performing single hierarchical sequencing and checking the consistency; 4, performing total hierarchical sequencing, i.e., calculating the weight of relative importance of all factors on each layer relative to the highest layer from top to bottom to obtain a weight sequence of each scheme in the bottom layer relative to a target so as to select a scheme, and checking the consistency too in the total sequencing process, wherein the relative weights of all available spectrum resources about the total target can be normalized into a weight vector by the total hierarchical sequencing, and the spectra corresponding to the maximum value are selected for next allocation in the algorithm; and 5, allocating the selected optimal spectra by using a coloring algorithm in the graph theory. A sequence of spectrum qualities is obtained by analysis and decision on multiple attributes of all current available bands, so that a reasonable spectrum access strategy is provided.

The invention discloses an improved FMEA method based on an interval intuitionistic fuzzy set and a mixed multi-criterion decision model. In the first stage, an interval intuitionistic fuzzy network analysis method is used to determine the weight of risk factors, firstly, the network structure diagram of risk factors and sub-risk factors is formed, the interval intuitionistic fuzzy pair comparisonmatrix is constructed and the aggregation degree is calculated, then the local ranking vector is calculated to obtain the initial super-matrix and weighted super-matrix, and finally the weights of all sub-risk factors are determined. In the second stage, an interval intuitionistic fuzzy comprehensive proportional evaluation method is utilized to determine the risk order of all failure modes, theset interval intuitionistic fuzzy risk assessment matrix is constructed for the first time, then the matrix is standardized and weighted to calculate the total risk and risk degree of each failure mode, and finally the ranking of all failure modes is determined. The fuzziness and uncertainty of expert language evaluation is overcome effectively. the hierarchy and interrelation of risk factors areconsidered. Thus, the risk ranking of failure modes is more accurate.

The present invention discloses an optical network evaluation method including the steps of building an AHP-based network evaluation model based on a necessary evaluation factor, an factor and a guideline influencing a target and a comprehensive evaluation formula; completing a pairwise comparison matrix that A is equal to (aij) n x n, where aij is the ratio of influence of an i-th factor on top factors to influence of an j-th factor on top factors in an n-th layer; determining an eigenvector w and a maximum eigenvalue [lambda] of the pairwise comparison matrix; carrying out a consistency check, and proceeding to step five if the consistency check is passed, or returning to step two if the consistency check fails; calculating a combination weight vector w(s) according to the eigenvector w and carrying out a combination consistency check; and carrying out a comprehensive network evaluation according to the combination weight vector w(s). The optical network evaluation method has the characteristics of accuracy, flexibility and high adaptability.

The invention relates to the large data processing technology in a computer information system, in particular to a criminal propensity and risk degree quantifying method and system based on the AHP. The calculated flow scheduling and optimization algorithm is used for achieving efficient collecting and extracting of service data. Based on a prison condition analyzer and the AHP algorithm is adopted, the criminal propensity and the risk degree are quantified and classified. According to the criminal propensity and risk degree quantifying method and system, prison service information is effectively processed and utilized. By means of the pairwise comparison matrix algorithm, a sequence is protected against damage caused by one-time fault and the problem that the criminal propensity and the risk degree are hard to quantify is solved.

The invention discloses a service selection method based on quality dependency relationship under service combination condition. The method comprises storing service logic description data into computer memory and the following steps: reading the service logic description in service procedure stored in the computer memory to get every service role by CPU; analyzing the relations between the service roles, conforming quality demand, and establishing quality judging dependency relation; creating a quality dependency diagram and the quality judging rules for analyzing every service role; selecting quality judging side; deciding the order to execute the service role selection; creating paired comparison matrixes; calculating the satisfaction degree of every service role candidate to the quality demand given by the quality judging side; and selecting a right candidate by the CPU. The whole selection process from establishing the service description in the method is implemented by computer automatically, thus, the objectivity and efficiency are improved.

The invention discloses a method for calculating a minimal software believability test case number. The method comprises the following steps of: constructing a hierarchical structure model by an analytic hierarchy process (AHP), and establishing a judgment matrix according to the hierarchical structure model; determining the value of the judgment matrix by a professional Delphi method; and determining the minimal test case number in an engineering practice by a classical statistical hypothesis theory. The hierarchy of software believability comprises a destination layer, a criterion layer and an object layer, factors in each layer are compared in couples, a coupled comparison matrix is established, and the judgment matrix is constructed on the basis of the coupled comparison matrix. The method has the advantages that the minimal test case number of the believability is calculated by the AHP and the classical statistical hypothesis theory according to elements which are provided by ISO/IEC9126 and influence the software believability, and on the premise of ensuring the complete test of believable software, test cases are reduced as many as possible, and test cost is saved.

The invention discloses a method for personalized cloud recommendation in a multi-cloud platform environment. Firstly, property attention priorities of a user are constructed into preference paired-comparison matrixes, the property priorities of cloud platforms are constructed into property paired-comparison matrixes, further inconsistent elements in inconsistent columns are amended by identifying inconsistent columns and contradicted columns in all the paired-comparison matrixes, the contradicted elements in the contradicted columns are corrected, the paired-comparison matrixes meeting the consistency requirements are obtained, finally preference weight vectors of the user to the cloud platforms are calculated by utilizing an analytic hierarchy process, the cloud platforms are recommended to the user based on the weight vectors, and accordingly a cloud recommendation scheme meeting the personalized requirement of the user in the multi-cloud platform environment is achieved. The method effectively improves the efficiency and accuracy of a cloud recommendation system and makes the system have better practicability.

The invention aims to a multi-objective decision problem, provides an index weight assessment method based on section rating of experts, and mainly solves the problem of consistency in index weight assessment of the experts. The method comprises the following steps: when comprising rating on two indexes is performed, the experts are not required to give a determined judgment result, while the judgment result can be represented by a discrete section containing one or more than one judgment result; an iterative search algorithm is designed to search a pairwise index comparison matrix which has the optimal consistency in section rating results of the experts; according to the optimal-consistency matrix, a logarithm least square method is utilized to calculate weights of each indexes. According to the invention, the section rating is used to replace the determined rating, on one hand, the rating difficulty of the experts is reduced, and on the other hand, the inconsistency of rating results can be effectively improved.

The invention relates to an electric vehicle charging management technology, in particular to an electric vehicle charging station operation potential degree sorting method based on an analytic hierarchy process. According to the method, constructing an index system from multiple dimensions in combination with service knowledge and current data situation analysis in a current service; calculatinga weight vector of each index in the potential index system by adopting a pairwise comparison matrix; calculating each index vector in the potential index system by adopting a pairwise comparison matrix; and multiplying the weight vector point by the index vector to obtain an evaluation result of the potential charging station, and taking the evaluation result as a potential degree sorting resultof the charging station. According to the invention, an analytic hierarchy process is used to sort the charging station utilization rate increase potential, and station selection priority support is provided for targeted marketization operation work of urban public charging stations.

The present invention discloses a business intelligence tool performance evaluation mechanism, which is realized by developing a model to evaluate tool performance according to a series of performance indicators: first determine the key criteria against which the tool performance is evaluated, and then at the most granular level Once these KPIs have been identified, the next step involves assigning the above criteria and the relative weights of the KPIs; creating a pairwise comparison matrix for all criteria items and all KPI items within each criteria item, each identified KPIs are used to evaluate the business intelligence tool, and a set of feedback is defined based on all KPIs, and the weighted average of all KPI scores is the final score. The present invention eliminates the possibility of potential missing parameters when assessing the success of a business intelligence tool, can be effectively used to reduce subjectivity in performance evaluation, and can eliminate bias against any particular standard or performance indicator.

An OWL-S-based method for calculating the comprehensive score of Web services , includes the following steps: first, calculating the semantic similarity between two concepts A and B in the domain ontology; 2, giving a method for calculating the input similarity degree Simput of the service S1 and the service S2; 3, giving the calculation method of the output similarity Simoutput of the service S1and the service S2; Fourth, calculating the functional similarity FunctionalSim (S1, S2) between the service S1 and the service S2; 5, calculating weights of QoS attributes set by users; 6, verifyingthe consistency of the user judgment according to the paired comparison matrix A constructed in the fifth step and the weight vector W obtained in the fifth step; 7, calculating the weighted result ofthe QoS score and the functional similarity to obtain the comprehensive score result of the service. The invention has more comprehensive consideration angle and better effectiveness.

The invention discloses an enterprise evaluation method based on big data analysis. The method comprises the steps of obtaining operation related data of a target enterprise from related websites of the target enterprise; screening out actual values of a plurality of evaluation indexes from the operation related data; establishing a paired comparison matrix based on the plurality of evaluation indexes; calculating feature vectors of the paired comparison matrixes, and calculating weight values of the plurality of evaluation indexes based on the feature vectors of the paired comparison matrixes; calculating an operation performance score of the target enterprise according to the weight values of the plurality of evaluation indexes and the actual values of the plurality of evaluation indexes; and if the operation performance score is lower than the preset operation score, sending an early warning prompt for the target enterprise. The invention further provides an enterprise evaluation device based on big data analysis and a computer readable storage medium. According to the method, the efficiency and accuracy of enterprise evaluation can be improved.

The invention discloses a workload estimation mechanism for company management. First, all major workflows that may be involved in the life cycle of the entire improvement work are determined, and it is necessary to determine the potential impact on the workload or work time occupied by completing a certain improvement function. A detailed list of parameters; the above parameters are presented in the form of questions, and the work is done after many discussions with experts, after each parameter has been determined at the most granular level, the next step is to assign the workflow and the relative relationship of each parameter Weights: A pairwise comparison matrix is ​​established for all workflows and all parameters in each workflow, and the matrix is ​​filled according to expert opinions after repeated discussions for weight calculation. The present invention largely eliminates the possibility of potential missing parameters when evaluating retrofit effort, it can clearly indicate the amount of work required to complete an analytical tool or product retrofit, provide a price estimate for retrofit and expedite decision-making process.

The invention relates to a fracturing acidification well and layer selection method based on a grey correlation method and an analytic hierarchy process, and belongs to the technical field of fracturing acidification. In order to overcome the defects in the prior art, the fracturing acidification well and layer selection method based on the grey correlation method and the analytic hierarchy process comprises the steps that the weight of a criterion layer to a target layer is determined according to the grey correlation method; a paired comparison matrix and a weight vector of the criterion layer to the target layer are determined according to the weight of the criterion layer to the target layer; the weight of a scheme layer to the criterion layer is calculated; a paired comparison matrix and a weight vector of the scheme layer to the criterion layer are determined according to the weight of the scheme layer to the criterion layer; a combined weight vector of the scheme layer to the target layer is calculated; and an optimal fracturing acidification well is determined according to the combined weight vector. The defect that the weight of well feature data must be known in a traditional well and layer selection method is overcome, calculation is simple and practical, and certain field practical value is achieved.

The invention provides an active maintenance-oriented power equipment health state evaluation method, which comprises the following steps of: firstly, acquiring state quantity index data of any power equipment in a power system, calculating the membership degree of each state quantity index through a fuzzy distribution membership degree function, and constructing a paired comparison matrix. According to the method, the maximum characteristic value and the initial weight of each corresponding index are calculated, consistency verification is performed on the maximum characteristic value and the initial weight, and meanwhile, an objective correction coefficient is introduced to correct the initial weight coefficient, so that the influence of subjective factors in determining the initial weight distribution is eliminated, and the requirements of system operation on the aspects of safety, reliability, economy and the like can be better considered; an equipment health state research basis is provided for researching an active maintenance strategy of power equipment; the power equipment is kept in an excellent health state in the full-life service cycle, and the optimal service performance of the equipment is maintained by using a low-cost and high-efficiency maintenance strategy, so that the safe, reliable and economical operation of a power system is ensured.

The invention discloses a routing method and device based on multi-attribute decision, equipment and a medium. The method comprises the following steps: acquiring network topology information and values of at least two network state attributes of each link; normalizing the value of the network state attribute according to the type of the network state attribute; obtaining a weight value of each network state attribute according to the paired comparison matrix; obtaining a cost function value of each link according to the normalized attribute value of each network state on each link and the weighted value of each network state attribute; and according to the cost function value of each link, calculating a shortest path meeting at least two network state attribute requirements. According to the method, the influence of various network state attributes is comprehensively considered, the weight value of each network state attribute is calculated in a mode of comparing the matrixes in pairs, the network state attributes are combined into one piece according to the weight values to serve as routing overhead to jointly determine routing, and routing can be carried out according to individual requirements of users.

The embodiment of the invention discloses a monocular depth estimation algorithm, system and device, and a storage medium. The method comprises the steps: firstly estimating an original depth image and a plurality of common depth images with different resolution levels for a monocular image through employing a convolutional neural network; secondly, recovering a relative depth map from the selective estimation data according to rank-1 properties of the paired comparison matrixes; and 3, decomposing the common depth map and the relative depth map into a plurality of depth components, and optimizing and recombining the depth components to reconstruct an optimal depth map. Experimental results show that the embodiment of the invention has good depth estimation performance.