149 results about "Intuitionistic fuzzy" patented technology

The invention discloses a method and a device for selecting a network based on a converged heterogeneous radio access network. The network selection method comprises the following steps of: transforming the attribute evaluation value of each attribute of the spare network to respective intuition fuzzy number according to the network selection state information and the heterogeneous radio converged network information; obtaining a fuzzy multi-attribute decision matrix according to the respective intuition fuzzy number and further obtaining a normalized decision matrix; then, obtaining the optimal attribute weight by using the maximum total difference policy of all the attributes between the attribute evaluation values of all the spare network; and weighting the normalized decision matrix by using the optimal attribute weight vector, processing the optimal normalized weighting fuzzy policy matrix based on a possibility and sorting to obtain the optimal network. By the network selection method and device, the stability of the network selection mechanism is improved without influence on the network selection accuracy.

The invention discloses an agent-based construction method and device of an intuitionistic fuzzy theory medical diagnosis model. With the adoption of a sensor technique and an artificial intelligence technology, remote and automatic acquisition and transmission of patient symptom are achieved; diagnosis analysis is carried out on the patient symptom by an intelligent medical diagnosis model built based on an intuitionistic fuzzy theory; the patient symptom is continuously updated and completed by a systematic knowledge module, namely a symptom-disease knowledge base and a disease-medicine knowledge base, and the diagnosis effect of the system is improved and enhanced; and on the condition that the existing medical staff, resources and technology are limited and the ageing population of China is faster, agent-based intelligent medical diagnosis system (AIMD) design is changed to ATM in a substantialization way and is installed in an aged community, convenient and high-efficiency medical services are provided for a patient through self-service terminal services, and the medical stress is effectively relieved. By the medical service mode, the medical clinic time is saved, and the medical cost is also reduced.

The invention discloses a power grid disaster real-time regulating and control device and method based on an intuition fuzzy rough set. The method includes the steps that historical disaster data in a database unit are called; the collected historical disaster data are reduced through the method based on the intuition fuzzy rough set, and then disaster grade evaluation rules of a power grid are obtained; disaster data of the power grid are collected in real time, and the current disaster grade of the power grid is determined according to the formed historical disaster grade evaluation rules; the data which are evaluated in real time are updated to a historical database and used for addition and modification of a power grid disaster knowledge base; power grid disaster emergency responses are conducted, namely, corresponding emergency restoration measures are taken according to different disaster grades to regulate and control the power grid. According to the system and method, the situation that the data size used in the power grid disaster evaluation process has fuzziness, randomness, uncertainty, redundancy and other characteristics is taken into account, the defect that internal relations and potential relations of data attributes can not be acquired through a traditional probability theory and other method is successfully overcome by the utilization of the method based on the intuition fuzzy rough set, and evaluation accuracy is improved.

The present invention discloses a lifting intuitionistic fuzzy tree based target tracking method. The method comprises: carrying out movement detection on a current video frame, and taking possible movement objects obtained from detection as observation results; associating the observation results with prediction results of targets, wherein the targets comprise reliable targets and temporary targets; carrying out trajectory management on unassociated observation results and prediction results, including carrying out on-line tracking on the unassociated prediction results of reliable targets so as to obtain candidate results, and using lifting intuitive fuzzy trees of the unassociated reliable targets to match the candidate results; and using associated results and matched results to obtain a trajectory of the target of the current frame, using the trajectory of the target of the current frame to predict, and updating the lifting intuitionistic fuzzy tree for the successfully associated or successfully matched reliable targets. The present invention further discloses a lifting intuitionistic fuzzy tree based target tracking apparatus. According to the method and apparatus disclosed by the present invention, performance of the target tracking in the case of the leak detection can be improved.

The invention discloses an unmanned combat aerial vehicle maneuvering gaming method with intuition fuzzy information. The method comprises steps of firstly, establishing a strategy set of an unmannedcombat aerial vehicle maneuvering decision; then, carrying out multi-attribute intuition fuzzy estimation on selectable maneuvering strategies according to the threatening size so as to obtain an intuition fuzzy payment matrix of unmanned combat aerial vehicle maneuvering gaming; establishing a unmanned combat aerial vehicle maneuvering gaming planning mode with intuition fuzzy information under an undetermined environment; and finally, using an improved differential evolution algorithm, solving the mode so as to obtain the optimal maneuvering gaming strategy of the unmanned aerial vehicle under the undetermined environment. According to the invention, the optimal decision problem of the unmanned combat aerial vehicle maneuvering under the undetermined environment is mainly solved.

The invention discloses a vector quantization based long-term intuitionistic fuzzy time series prediction method. The method includes the steps of A, intuitionistic fuzzification preprocessing of serial data and B, vector quantization based long-term intuitionistic fuzzy time series prediction. A long-term intuitionistic fuzzy time series prediction model built by the method expands single output of the serial data into multiple outputs, a predicated value is converted from a scalar into a vector, and accordingly long-term predication performance of a time series system is improved to a great extent. A sliding window mechanism is introduced into the method, fuzzy change characteristics of the serial data are acquired accurately and rapidly; a discourse domain internal is divided dynamically by the aid of an IFCM (intuitionistic fuzzy C-means) algorithm to be more close to the actual uncertain data distribution; by the aid of vector quantization based long-term time range prediction, the problems of zero matching of intuitionistic fuzzy rules and system error accumulation can be well solved; through example verification and result analysis, the model has good predication performance.

The invention discloses a multi-target threat assessment method suitable for a high dynamic environment, which relates to high-level information fusion and decision problems of a sensor network. Basedon the entropy measurement method and dynamic intuitionistic fuzzy method, the attributes of battlefield targets are reasonably weighted, and attribute information of multiple successive time of eachtarget is selected, according to the importance of target information in threat assessment, the time series weights of target information are calculated by the normal distribution method, and the target information at multiple times is weighted synthetically according to the time series weights; on the basis, the dynamic intuitionistic fuzzy multi-target threat estimation model is established, and the final dynamic threat assessment result, i.e., the threat degree ranking of multi-targets, is calculated. The method not only considers the current time target information, but also can effectively fuse the preorder time target related information, so it can dynamically reflect the continuously changing battlefield situation, and make the multi-target threat assessment effect more scientificand reasonable under the highly dynamic environment.

The invention discloses an on-line sequence data prediction method and device. The prediction method includes: constructing an interval type-2 intuitionistic loop fuzzy neural network model; and training the interval type-2 intuitionistic loop fuzzy neural network model. The special procedure is as follows: recursively updating an average and an standard deviation to standardize sequence data samples; selecting an intuitionistic fuzzy set fuzzy rule on the basis of a dynamic clustering method of recursive computation of an approximate density center; inputting the standardized sequence data samples into the interval type-2 intuitionistic loop fuzzy neural network model with the selected intuitionistic fuzzy set fuzzy rule, outputting a sequence data prediction result, and determining whether the sequence data prediction result meets a preset precision requirement or not; completing training of the interval type-2 intuitionistic loop fuzzy neural network model; otherwise, updating an output weight, a feedback weight, an intuitionistic fuzzy set fuzzy rule center and a point difference until the output prediction result reaches the preset accuracy requirement; and inputting on-line sequence data into the trained model to obtain a prediction result.

The invention discloses a naval vessel formation dynamic air defense threat estimation method based on intuitionistic fuzzy TOPSIS, and relates to the field of naval vessel formation air defense decision. The method comprises the following steps of firstly standardizing different types of target information, and establishing an intuitionistic fuzzy decision matrix; secondly obtaining an initial weight of an evaluation index by using an intuitionistic fuzzy entropy weight method, and fusing subjective preference information of a commander to solve an index weight optimization model, so that a weight result better meets the requirements of a battlefield; then, determining a dynamic decision matrix by adopting intuitionistic fuzzy cross entropy and relative closeness, processing the multi-moment information by adopting a normal distribution method, establishing a weighted dynamic decision matrix to present the air defense threat situation dynamically; and finally obtaining a threat degreesorting result of the incoming targets by using a TOPSIS method. The method can be applied to the dynamic air defense threat estimation of a naval vessel formation in an uncertain sea battlefield environment.

A method of manufacturing demand and device capability normalization modeling facing cloud manufacturing provided by the invention comprises the steps of: introducing a feature process route on the basis of establishing a device manufacturing capability model and a part manufacturing demand model, employing an intuitionistic fuzzy algorithm to perform matching of a device source set and a cloud task manufacturing demand, and constructing a manufacturing demand and device capability normalization model facing cloud manufacturing. Through combination of features of cloud manufacturing, the method of manufacturing demand and device capability normalization modeling facing cloud manufacturing integrally considers diversity of parts and devices, complexity of the manufacturing process, manpowerparticipation factors and quantifiable factors of the resource capability, performs feature modeling of the demand and the capability, and establishes a mapping relation of the cloud manufacturing task and the device capability, so that the efficiency and the capability of subsequent manufacturing resource intelligent search and cloud manufacturing service combination optimization matching, a cloud manufacturing service platform can rapidly and effectively select manufacturing resources satisfying the manufacturing demand from lots of manufacturing resources, and therefore, the manufacturingcost is reduced, product quality is improved, and efficient sharing and optimization configuration of the manufacturing resources are achieved.