34 results about "Fuzzy concept" patented technology

Generally, decisions are based on information. To be useful, information must be reliable. Basically, the concept of a Z-number relates to the issue of reliability of information. A Z-number, Z, has two components, Z=(A,B). The first component, A, is a restriction (constraint) on the values which a real-valued uncertain variable, X, is allowed to take. The second component, B, is a measure of reliability (certainty) of the first component. Typically, A and B are described in a natural language, for example: (about 45 minutes, very sure). Z-number has many applications, especially in the realms of economics, decision analysis, risk assessment, prediction, anticipation, rule-based characterization of imprecise functions and relations, and biomedicine. Different methods, applications, and systems are discussed. Other Fuzzy concepts are also discussed.

The invention discloses a method for realizing automatic matching of database schemas, which comprises the four steps of schema information analysis, schema information classification, schema information integration and calculation of the similarity of schema elements, wherein the step of schema information analysis is used for realizing the analysis of element information of formatted source schemas and target schemas; the step of schema information classification is used for classifying schema element information analyzed in the schema information analysis stage and classifying all the elements according to the name, the description and the type respectively; the step of schema information integration is used for integrating classified results of schema information classification and element structure information and establishing weighted fuzzy concept lattices; and the step of calculation of the similarity of the schema elements is used for calculating the matching degree of the schema elements according to the weighted fuzzy concept lattices and setting a threshold to determine the matching relation between the elements. The method for realizing automatic matching of the database schemas solves the problems of schema matching in actual application, improves the efficiency of computers when solving the problem of schema matching, and reduces the waste of CPU resources.

The invention discloses a human face recognition method based on fuzzy kernel-based two-dimensional principal component analysis (K2DPCA), which comprises the following steps: introducing a fuzzy concept to the K2DPCA, calculating the category of samples in a high-dimensional feature space (for short) and the subordination degree of each sample to the category by using the fuzzy K nearest neighbor algorithm, and defining fuzzy divergence matrixes of the samples according to the subordination degree information. Because the category of the samples and the distribution information are completely fused into the human face feature extraction, the marginal problem caused by the reason that the human face is easy to be affected by illumination, expression and other factors and the existing hard classification problem are solved. Due to the establishment of the category division data of the human face samples in the high-dimensional feature space, and the selection of the feature vector which can ensure that the divergence between the category is more than the divergence in the category after projecting as the optimal projection axis direction, the optimum projection axis selection accuracy is improved, and the capacity of representing the human face feature of the fuzzy K2DPCA is increased.

The invention provides a cloud manufacturing capability description method supporting use on demand and sharing circulation of manufacturing capability. The method comprises the following steps of: extracting and classifying fuzzy information and dynamic behavior information in a knowledge-based manufacturing capability description model (namely a multi-dimension manufacturing capability information model); formalizing a fuzzy concept and a fuzzy role relationship according to a fuzzy description logic; describing service state change and dynamic combination flow according to a dynamic description logic; and giving an intelligent search and recommendation mechanism of the manufacturing capability based on the description method. According to the cloud manufacturing capability description method, the qualitative and quantitative properties of each dimension and each level of manufacturing capability can be taken into sufficient consideration, and a knowledge-based manufacturing capability language is provided, so that manufacturing capability services are stored in a cloud manufacturing service platform in an ontology mode, and a manufacturing capability service network is formed on the basis of various relationships among the services and supports the intelligent search and the use on demand of users.

The invention discloses a method for extracting video texture characteristics based on fuzzy concept lattice, which mainly solves the problems of large computation quantity, low efficiency and low real-time performance in a traditional method. The method comprises the realizing steps of: (1) dividing a video lens; separating the divided video lenses into video segments; using a first frame of thevideo segments as a key frame of the video segments; (2) separating an image of the key frame into blocks; computing a gray co-occurrence matrix of the image blocks; computing fourteen texture characteristic vectors of second-order moments, entropy and the like based on the gray co-occurrence matrix; (3) using the image blocks of the key frame as an object set; using the texture characteristic vectors of the image blocks as an attribute set to form a fuzzy form background for constructing the fuzzy concept lattices; (4) generating a texture related rule by the fuzzy concept lattices of the key frame; and (5) extracting the texture characteristics of all video frames in the video segments according to the texture related rule of the key frame. The method can be used for quickly and accurately extracting the video texture characteristics, and video processing fields of target identification, video search and the like.

The invention provides a fault diagnosis method of a hydrometallurgy thickener based on credibility. The method includes obtaining on-line variables of a hydrometallurgy thickener; determining fuzzy dimensionality of each variable according to on-line variables, wherein the fuzzy dimensionality is dimensionality corresponding to fuzzy concepts included in rule antecedents in a pre-established expert rule base; aiming at each variable and the fuzzy dimensionality of the variable, adopting a fuzzy membership degree function to obtain the credibility of the fuzzy dimensionality to which the variable belongs; based on an uncertainty reasoning model based on credibility and rules in the expert rule base, performing rational analysis on the credibility of each variable, and obtaining fault conclusion credibility; and comparing the fault conclusion credibility with a preset threshold value, and obtaining a fault result. The abovementioned method can obtain rules corresponding to diagnosis experience of experts or operating personnel in advance, and perform fault diagnosis on current on-line variables, so as to perform timely adjustment according to a fault diagnosis result, thereby effectively reducing an accident rate, and improving production safety.

The invention provides a power quality comprehensive evaluation method and device based on an intuitionistic fuzzy theory, so as to solve the technical problem that in the current fuzzy method, the common defects in the case of fuzzy concept processing by various kinds of membership functions are that the fuzzy characteristics of each evaluation index relative to each quality level are not depicted in details, the membership of the index relative to the whole qualified range is only calculated generally, the power quality level is determined according to a normalized quantized value, the maximum membership principle conceals the difference between two memberships, and judgment deviation is caused to be over large.

The invention relates to a method for generating a complete fuzzy concept lattice, in particular to a lattice updating method for fuzzy concepts based on an integration technology, which uses the integration scheme between two fuzzy concept lattices to solve the problem of L-Fuzzy Concept Lattice Renewal. The invention does not need to regenerate the complete L from the updated data set. Fuzzy concept lattice, and the original fuzzy concept lattice before updating is used in the generation of new fuzzy concept lattice, which avoids the waste of resources and improves the Updating efficiency ofL-fuzzy concept lattice. The invention avoids regenerating the fuzzy concept lattice from the updated formal background, and updates the original fuzzy concept lattice by using the update data, so the update efficiency is greatly improved. Especially for sparse dataset and small truth degree set, the update efficiency is improved obviously.

The invention relates to a pattern and meaning code element coding method and a keyboard thereof, belonging to the field of Chinese information processing. The invention provides a concept of code element, component and configuration, clears the traditional fuzzy concept, improves the structural knowledge on Chinese characters and simplifies the split of the Chinese characters into the split of the component. The well-chosen Chinese character code elements obtain meanings according to patterns, are divided into areas according to the meanings and named according to the positions and are easy to learn and remember so that the method is rapidly mastered and is difficult to forget. The invention can be used for the Chinese character index of computer Chinese character input and dictionary compiling and can also be used for the Chinese character input of hand-held equipment, such as a mobile phone, and the like. In addition, an ignorable repeated code is the great breakthrough of the invention, and defect of the traditional coding method is overcome.

The invention discloses a fuzzy concept related parallel generating method based on load balancing. The fuzzy concept related parallel generating method includes the following steps: (1) generating a fuzzy formal background according to a dataset to be processed and an accuracy requirement, (2) initializing a global section set according to the fuzzy formal background, namely (a formula), (3) carrying out breadth-first traversal from top to bottom on an ||L|| complete search tree of a high order ||Y||, regarding i as the current height, (4) calculating total loads Qi under the current height i by a root node processor according to a global search section set E, a first formula and a second formula, (5) assigning a subtask range (Blow, Bup)of each node in a balanced mode according to the number D of processors which can be governed under the current parallel calculation environment, a fifth formula, a sixth formula and a seventh formula, (6) enabling each processor to obtain a partial task section set, and regarding Esub as the partial task sections. According to the fuzzy concept related parallel generating method based on load balancing, the parallel calculation technology and a load balancing calculating method are used for solving the problems that in a fuzzy concept building process, the time complexity is excessively high and consumed time is excessively long.

The invention relates to a big data clustering algorithm for reducing the risk of customer losing. The method comprises the following steps that: (1), related attributes are selected by using an axiomatic fuzzy set theory and a fuzzy concept is expressed by using a membership function and logical operation; (2), according to the calculated membership degree, a neighborhood radius and a weight coefficient of a subtractive clustering algorithm are automatically determined; (3), with the subtractive clustering algorithm, a mountain function is selected and updated to calculate a clustering numberand centroid, wherein the subtractive clustering algorithm and the axiomatic fuzzy set are integrated into a semantic-driven subtractive clustering method; and (4), on the basis of a K-means algorithm, the clustering of the clustering centroid obtained by the semantic-driven subtractive clustering method is calculated. Therefore, with the semantic-driven subtractive clustering method (SDSCM) based on the subtractive clustering algorithm and the axiomatic fuzzy set, the clustering precision of the subtractive clustering algorithm and K-means method is improved; and because of the novel algorithm, the risk of inaccuracy of operational management based on the axiomatic fuzzy sets (AFS) is reduced.

The invention discloses a power load prediction method based on a cloud model, and the method comprises the steps: determining a factor which exerts the biggest impact on a power load and an output factor of power load prediction; carrying out the description of the uncertainty of the obtained factors; building a two-dimensional multi-rule generator; and carrying out the prediction of the power load. According to the invention, the method forms a quantified sample database through the building of the cloud model, enables an original limited sample space to be extended to be extended sample data with the randomness and popularity through the cloud model, and irons out the defect that the sample data is difficult to collect. The method creates conditions for improving the prediction precision of a load index. According to the invention, the method is high in prediction precision, is suitable for a current large-scale power grid, and can process the uncertain information and fuzzy concepts.

The invention discloses a load distribution adjusting method based on a circulating water system operation mode and belongs to the technical field of power plant load distribution. The method aims atsolving the problem that an existing circulating water pump takes large redundancy in a fuzzy concept as an adjusting principle, and safety risks exist in water pump switching under the condition thatthe unit load is greatly adjusted. The method comprises the steps of arranging n unit combination operation modes; obtaining the optimal circulating water flow corresponding to the single unit when the load changes and the circulating water temperature changes and the maximum load adjustment amplitude under the current unit combination operation mode; establishing an operation mode selection model, and determining a selected unit combination operation mode according to the maximum load adjustment amplitude; determining whether the circulating water pump combination is adjusted or not and whether the unit combination operation mode is switched or not according to the adjustable allowance, and finally determining the final unit combination operation mode to serve as primary load distribution guidance. The method is used for reversely guiding inter-plant load distribution.

The invention discloses a fuzzy evaluation method based on primary and secondary hierarchies under a joint learning framework. The method comprises the following steps: collecting data, judging whether equipment has a fault or not, constructing a matrix, calculating expert set weight, carrying out comprehensive evaluation, fusing results and carrying out health evaluation on factory equipment. According to the primary and secondary hierarchy-based fuzzy evaluation method under the joint learning framework, the fuzzy set theory is introduced, the membership degree of the health state of the equipment parameters is determined, the health state evaluation of the equipment is a multi-attribute decision problem, and the purpose of judging the target attribute can be achieved only by fusing the health states of the parameters; the method solves the problem that traditional non-standard equipment health degree judgment is too rough, expert experience and fuzzy concepts are combined and introduced, energy for processing uncertainty problems is provided, independent evidence information from different information sources can be fused, a multi-factor and multi-factor evaluation system is utilized, all parameter indexes are synthesized for judgment, and the method is high in practicability and high in practicability. And the judgment is more comprehensive.

The invention provides a brittleness rule engine obtaining method easy to expand. The brittleness rule engine obtaining method easy to expand comprises a, a rule set comprising fuzzy expressions is submitted to an engine compiler and all fuzzy concepts are marked through specific definition symbols; b, the rule set is compiled through the engine compiler, so that all the fuzzy expressions are identified; c, all the fuzzy expressions are interpreted, so that operation codes of the same type are generated; d, non-fuzzy expressions are compiled, so that operation codes specifically corresponding to the non-fuzzy expressions are generated; e, other compiling work is completed, a brittleness rule engine is obtained according to the rule set of a compiled version. Processing related to fuzzy rules is set to be external calling, so that the expanding capacity of the fuzzy rules is improved, and modification is easy.

The present invention discloses a process method for large-scale production of fried rice, wherein the formula, the taste, the production conditions and other fuzzy concepts are quantified, the reasonable parameters are provided, the standard is drawn up, the production process is set, and the fixed template is made. According to the present invention, the traditional fixed mode that the fried rice is completely made through manual operation of the cook is changed, the rice, the ingredients, the seasoning material and the like are decomposed into a plurality of processes, and are processed by setting different production lines; the modern professional processing technology is introduced, the factory production is adopted as the core, the standardized formula is used, the fixed parameters are set, the fixed template is used, the standardized operation is performed according to the standard and unified process so as to achieve the factory production and large-scale management, and maintain the uniform taste of the fried rice at a maximum; and the product standardization, the production flowing, the production scalization and the management modernization can be achieved, and the change of the fried rice from the kitchen operation to the modern industrial production is basically achieved.