53 results about "Focal element" patented technology

The invention discloses a D-S evidence theory based multi-sensor information fusion method, relates to an evidence theory based multi-sensor information fusion method and belongs to the field of information fusion. The D-S evidence theory based multi-sensor information fusion method aims at solving the problem that a traditional evidence fusion method is large in calculated quantity and is uncertain in combination result and has one-ballot-veto problem during evidence combination. The D-S evidence theory based multi-sensor information fusion method comprises the steps of obtaining an evidence set E={ei, i=1, 2, ..., 1}; disposing the evidence ei into evidence data mi(A) according to a set identification frame theta={theta1, theta2, ..., theta n}; performing sorting from small to large according to cardinal number of the A to form an order focal element set K={C1, C2, ..., CJ}, and conducting BPA determination on evidence data mi(Cj) to obtain m'i(Cj); obtaining a fusion weighting function wi(Cj) according to wi(Cj)=1- m'i(Cj) - mi(Cj); performing evidence combination (as shown in the description) to obtain a combination result of all evidence sets and using the combination result as an output decision of a sensor. The D-S evidence theory based multi-sensor information fusion method is suitable for multi-sensor information fusion.

The invention relates to an improved D-S evidence theory-based lithium battery fault diagnosis method, which is used for determining the state of a lithium battery. The method comprises the following steps: primarily diagnosing the fault of the lithium battery by utilizing at least two diagnosis methods; according to the primary diagnosis results, constructing the evidence body corresponding to each diagnosis method, and calculating the elementary probability distribution function of each evidence body; based on the elementary probability distribution function of each evidence body, correcting the weight of each evidence body to obtain weighed evidence body; calculating the confidence degree of each nominalized focal element, obtaining a combination rule according to the confidence degree, and fusing the evidence body and the weighed evidence body corresponding to the diagnosis method according to the combination rule, to obtain the fused diagnosis result; and according to the fused diagnosis result, determining the state of the lithium battery by applying a decision rule. Compared with the prior art, the improved D-S evidence theory-based lithium battery fault diagnosis method has the advantages of being accurate in diagnosis results, high in evidence utilization rate, high in diagnosis precision, and the like.

The invention provides a method for monitoring an underway ship in real time based on AIS and VTS information integration. The method comprises the steps of collecting signals; acquiring AIS static information, AIS dynamic information, information related to the voyage number and information about the security of a target ship through an AIS; detecting VTS dynamic information of the target ship through a VTS, and reflecting information about the size and the shape of the target by using VTS radar target echoes; building a D-S evidence theory identification framework through analyzing the difference between the AIS dynamic information and the VTS dynamic information acquired by the AIS and the VTS radar respectively; and constructing a focal element confidence function based on a Kalman prediction algorithm, carrying out evidence synthesis within the D-S evidence theory identification framework, and judging monitoring results. The method provided by the invention is based on the two existing real-time monitoring modes for ships, utilizes the D-S evidence theory identification framework, and constructs the focal element confidence function based on the Kalman prediction algorithm so as to achieve more accurate monitoring results.

The invention discloses a method and a device for determining a focal element. The method comprises the following steps of: responding to the clicking operation of a user to obtain the present clicking position of the user; forming a predetermined region around the present clicking position, and determining whether the focal element exists in the predetermined region; if finding out one or more focal elements in a predetermined direction in the predetermined region, determining that the focal element closest to the present clicking position as the focal element for the user to click next. According to the technical scheme provided by the invention, the way of selecting the focal element is quite smart and the clicking result is well in accordance with the expectation of the user; and consequently, the hit rate of the clicking of the user is increased and the experience of the user is promoted.

The invention belongs to the technical field of risk evaluation of an electric power system, and particularly relates to an electric power system operation risk evaluation method based on random set theory. The evaluation method comprises the steps of performing classification quantification on each influence factor according to collection of historical data of the electric power system and prediction of short-time system operating condition in the future, and expressing each variable in a random set form; performing sampling on random set focal elements of each variable by a Monte Carlo method so as to generate system operating states under influences of various kinds of uncertain factors; through section power flow calculation, judging whether branch power flow overload or node voltage out of limit exists or not, and performing correction on the system to eliminate branch power flow and voltage out of limit; and calculating element-level and system-level system operating risk indexes, outputting the system operating risk indexes and performing evaluation on the system short-time risk level. By virtue of the evaluation method, uncertain information in risk evaluation can be solved and processed, so as to comprehensively reflect influence of the uncertain factors on the risk indexes, and the specific probability distribution condition.

An imaging system is provided that includes a optical pulse generator for providing an optical pulse having a spectral bandwidth and includes monochiromatic waves having different wavelengths. A dispersive element receives a second optical pulse associated with the optical pulse and disperses the second optical pulse at different angles on the surface of the dispersive element depending on wavelength. One or more focal elements receives the dispersed second optical pulse produced on the dispersive element. The one or more focal element recombine the dispersed second optical pulse at a focal plane on a specimen where the width of the optical pulse is restored at the focal plane.

The invention provides an unmanned ship false target detection method based on a three-dimensional laser radar. The method is characterized by taking an obstacle target, which does not influence sailing of an unmanned ship, as a false target, and comprises the following steps: mounting the three-dimensional laser radar, a differential GNSS receiver and an attitude angle sensor onto the unmanned ship; carrying out pretreatment on the three-dimensional laser radar data, and carrying out laser point cloud correction based on unmanned ship real-time attitude angle data obtained by the attitude angle sensor and real-time self motion status data obtained by the differential GNSS receiver; and carrying out false target detection through the three-dimensional laser radar, which comprises the substeps of carrying out grid segmentation to obtain an obstacle target, carrying out multiple-feature extraction and with each feature serving as an evidence to determine the target type, establishing a target type identification framework, and judging the false target according to credibility of each focal element. The method, by utilizing the high-reliability three-dimensional laser radar, takes andconsiders the three-dimensional laser radar false target as the detection target separately, so that the unmanned ship is not influenced by the false target when avoiding the obstacle, and accuracy of target detection is improved.

The invention discloses an evidence theory-based multi-source information fusion risk analysis method, which belongs to the technical field of information processing. The method comprises the following steps of: determining an index and a weight of a risk system by using an analytic hierarchy process; dividing a risk level by using a mean principle in a statistical method and generating basic probability assignment; fusing basic probability assignment by a weighted fusion method which effectively processes conflicting evidence; determining a main focal element of a fusion result; and obtaining the risk level of the risk system according to the corresponding relationship between the risk level and a basic probability assignment function focal element so as to realize risk analysis. The method has high generality and the advantages of low calculation complexity and high instantaneity and can be conveniently applied to risk evaluation of the system.

The invention discloses a conflict evidence fusion method based on arithmetic average proximity. The method comprises the following steps of obtaining the measurement information of a plurality of sensors, selecting a proper method according to an actual application scene to obtain BPA of evidence, converting the BPA into evidence information, introducing an arithmetic average close degree conceptin a fuzzy theory to measure the mutual support degree of the evidence on the same focal element, and calculating a weight coefficient of the fusion evidence by utilizing the arithmetic average closedegree between the evidence; and finally, fusing the corrected evidence one piece by one piece by adopting a Dempster combination rule, and outputting a decision result of final target identification. According to the invention, the arithmetic average close degree method in fuzzy mathematics is introduced; the mutual support degree of each evidence to the same proposition is measured by using thearithmetic average close degree of the basic probability assignment of the same focal element in the evidences, and the corrected evidence is fused one piece by one piece by using the Dempster combination rule after the evidence is corrected, so that the method has the important theoretical significance and application value.

The invention discloses a multi-level hierarchical DSmT rapid approximate reasoning fusion method. Aiming at the condition that only a monad focal element has the belief assignment in an ultra power set space, a binary tree and trinomial tree grouping technique is applied to perform the rigid grouping to realize the mapping of different granular focal elements. In the meantime, the belief assignment summation is performed to each grouping focal element corresponding to each information source, two information sources of a coarsing ultra power set space are fused by applying the DSmT rule and the proportion distributing conflict rule, a fusion result is stored to be used as a connecting weight between a father node and a child node, and then the normalized treatment is performed to each grouping focal element belief assignment. The multi-level hierarchical frequency is determined through setting the depth of the tree. The invention has the advantages of simple computation, high computational efficiency, good robustness of the approximate computing result and the like, and solves the problem that the DSmT evidential reasoning has the computational bottleneck along with the increase of discrimination frame focal elements.

The invention provides a message conversion method and a message conversion device which are applied to an embedded application system. The method comprises the following steps of: acquiring a key message in a message queue; determining a key value of a key corresponding to the message; if the key value is a key value of the key which is preset and needs to be intercepted, converting the message corresponding to the key value into a virtual mouse type message; and sending the virtual mouse type message to a browser of the application system to process. In the embodiment of the invention, for the embedded system without a mouse, the message sent by the preset key on a remote controller can be converted into the virtual mouse type message, so that the browser of the application system, which receives the virtual mouse type message, carries out identification and processing. The problems that in the prior art, the response of the embedded browser on an event depends on focal elements and non-focal elements on a HTML (Hypertext Markup Language) page cannot be processed are solved, so that the satisfaction of a user is improved.

The invention discloses a gas pipe network leakage grade judgment method based on an improved evidence fusion algorithm. The gas pipe network leakage grade judgment method comprises the steps that multiple evidence sources used for judging gas pipe network leakage are obtained through gas pipe network information measured by a sensor; and for weak decision evidences, the focal element weight of the focal element with the highest mass value is taken as 1, and the other focal elements are multiplied by the respective focal element weights respectively, so that the difference between the maximumtrust focal element and the other focal elements is effectively expanded, and the evidence fusion result is more reliable, and the convergence speed is high. For conflict evidences, average evidencesare adopted to replace the conflict evidences, and the conflict evidences are limited by the evidence distance weights, so that the influence of the conflict evidences on an evidence synthesis resultis reduced, and weak decision evidences can play a decision role. According to the invention, the accuracy of gas pipe network leakage level decision can be improved.

The invention discloses a robot functional module granularity division evaluating method based on a D-S evidence theory and belongs to the field of robot decentralized control. The method mainly comprises four steps of: creating a relation measure index among the functional modules and a relation measure index in each functional module in virtue of a principle that functional modules of a smart service robot system are independent, and solving a cohesion degree utility value and a coupling degree utility value of each model division scheme in combination with a correlation measure matrix; constructing a multi-attribute decision matrix by using the cohesion degree and the coupling degree as two evidence sources of the evidence theory, and introducing the concept of a membership function in order to transform the utility value in the decision matrix; solving the utility assigned value of each focal element in combination with the definition of a basic probability assigned value, and synthesizing the preference information with different attributes of each scheme to construct a trust interval; and ordering the decision schemes on the basis of an interval number preference ordering method in order to obtain the optimal division granularity of each functional module of the smart service robot system.

The invention provides a reservoir adaptive scheduling method based on the D-S evidence theory, which is characterized by including the following steps: S1, predicting the temperature and precipitation within a future research time through GCMs (Global Cycle Model) and a downscaling technology, taking the prediction result as the input predicted runoff of a hydrological model, and taking the runoff prediction results output by GCMs as multiple future climate change scenarios; S2, constituting a recognition framework with each potential climate change scenario as a focal element Theta in the D-S evidence theory; S3, defining corresponding basic probability assignment functions m1, m2 and m3; S4, synthesizing three evidences based on a modified D-S synthesis rule, and calculating the synthesis probability m123 of the scenarios; S5, letting the weight Alpha of each scenario be equal to a trust function; and S6, constructing a reservoir optimal scheduling model with the maximum weighted average of the average benefits over the years as an optimization objective, setting a linear scheduling function, and optimizing the parameters of the scheduling function through a simulated optimization approach to get an adaptive scheduling scheme.

The invention provides a method and a device for controlling input data. The method comprises the following steps of: intercepting a keyboard message which includes a first language message; acquiring a focal element in a current window; acquiring a second language input in the focal element in accordance with a preset target element attribute mapping table; converting the keyboard message into corresponding keyboard information coded according to the second language in accordance with a preset language code mapping table; and outputting the keyboard information coded according to the second language in the focal element. The shielding of an input method is realized in a condition that the compatibility of a browser cannot be met in the prior art, and by using the method and the device, through intercepting the keyboard message and converting a keyboard input, the conventional technical problem is effectively solved.

The invention discloses a weighted conflict evidence fusion method based on a Hellinger distance and reliability entropy. The method comprises the following steps: firstly, acquiring measurement information of a plurality of sensors, converting the measurement information into evidence information, then converting focal elements in fused evidences into single subset focal elements by utilizing a basic probability assignment conversion formula, and introducing a Hellinger distance to obtain the support degree of the fused evidences; besides, determining the trust degree of the fused evidence byrepresenting the uncertainty degree of the evidence by improving the reliability entropy and comprehensively considering the Hellinger distance and the improved reliability entropy, obtaining a weight factor, then correcting the fused evidence by utilizing a weighted average thought, finally fusing the corrected evidences one by one by adopting a Dempster combination rule, and outputting a finaltarget identification decision result. Compared with a traditional algorithm, through the basic probability assignment conversion function and the Hellinger distance, the conflict degree between the proposition evidences of the non-single subset can be effectively measured; meanwhile, the uncertainty degree of the evidence is represented through the improved reliability entropy, the weight coefficient of the fused evidence is jointly determined by comprehensively considering the support degree and the information amount, and the method has important theoretical significance and application value.

A computer system utilizing software to map content by determining a field of relevance and at least one topic in the field of relevance is presented. The system determines at least one content pertaining to the topic, retrieves a representation of the content and maps the representation of the content onto the field of relevance. Then, it provides an extremely flexible presentation mechanism where the content is organized by multi-dimensional mappings to present the information effectively. One of the features allows a vector to be assigned to each entity, queries a user or software agent for a particular focal element and displays the multiplicity of distinguishable entities based upon the assigned vectors utilizing the focal vector as a reference point to view the information. The system facilitates the organization of results of database interrogations, web searches and other large data situations, creating a multi-dimensional topic space of content. The invention represents a novel, unique approach that matches nicely with the requirements of the Internet to efficiently examine the results from search engines in an efficient manner.

An image processing method forming realistic stratum detritus detail in a camouflage pattern comprises the steps of: Identifying the desired camouflage genre; Forming a base image layer with a shallow depth of field which includes a foreground focal element extending substantially across the width of the pattern; Forming a lattice work image layer including a lattice work of appropriate natural elements; Overlaying the lattice work image layer onto the base image layer; and Blending the detritus images into the natural elements of the lattice work. Camouflage patterns formed according to the disclosed process are also disclosed which form a more effective hunter camouflage pattern.

The invention relates to the field of computer software, and discloses a focus element navigation method in a human-computer interface, which solves the problem of more occupied system resources during navigation by the prior art. The technical scheme has the key point that the method comprises the following steps of: a, establishing a data structure according to coordinates of the positions of elements and height and width data of the elements; b, filling the acquired coordinates and the height and width data of the elements in the data structure, and establishing an element management queueobject; c, when a navigation event comes, determining a set of navigable effective cutting elements, and judging whether the set is empty, if so, executing a step d, otherwise executing a step e; d, using the current focus element as a focus element after the navigation event is triggered, and turning to a step f; e, searching a focus element most close to the current focus element in the navigation direction, using the searched focus element as the focus element after the event is triggered, and turning to a step f; and f, acquiring the focus element after the navigation. The method has the advantages of less occupied system resources and high focus navigation efficiency, and is widely applied to various embedded devices.

The invention relates to a water source pollution detection method based on an evidence theory, and the method uses an information processing technology to detect the pollution degree of water. A fuzzy number model of the water resource water quality index is generated according to existing data, the similarity between a sampling value in a water resource distribution system and the fuzzy number model of the existing index is obtained according to a similarity measurement method of the fuzzy number, basic possibility appointment is generated on the basis of the similarity, a classic fusion method is used to fuse the basic possibility appointment, a main focal element of a fusion result is determined, the pollution degree of the system is obtained according to the correspondence between the pollution level and function elements of the basic possibility appointment, and water resource pollution is detected. The detection method has the advantages of higher versatility, low computational complexity and high instantaneity, and can be conveniently used in water resource pollution detection.

An improved method and module for auto focusing utilizes a variable thickness focus element. A different thickness, and thus a different focus, is optically coupled to an image sensor by rotating the focus element. Movement along the optic axis is not required. This minimizes the amount of space required to provide the auto focusing function, allowing a mobile device utilizing the module to be smaller while still providing the auto focusing feature. In addition, the mechanism for rotating the focus element is smaller and/or less complex than a mechanism for moving a lens assembly along the optic axis, further allowing the device to be smaller. The focus element has less inertia than conventional lens assemblies and so required less power to move and allows for fast focusing.

The invention discloses a mechanical fault diagnosis method based on multi-sensor fusion. The method comprises the following steps: converting operation data, observed by sensors at different positions, of mechanical equipment into evidence information; calculating support intervals of focal elements in the evidences, and measuring conflict degrees among the evidences through interval distances so as to obtain support degrees of the evidences; quantifying the uncertainty degree of the evidence through the improved reliability entropy to serve as the information amount of the evidence; comprehensively considering the interval distance and the improved reliability entropy to determine the credibility of the evidence and obtain a weight factor; and carrying out weighted average on the obtained evidence by using a weight factor, and outputting a decision result of mechanical fault diagnosis. Compared with a traditional algorithm, the scheme can effectively measure the difference between evidences through the interval distance, quantifies the uncertainty of the evidences through the improved reliability entropy, and comprehensively considers the support degree and the information amount to jointly determine the weight factor of the evidences.

The invention provides a target identification method used for processing the fuzzy and high conflict information and can reduce computational complexity and improve detected target classification accuracy. The method comprises steps that according to acquired single focal elements under an identification framework, the fuzzy and high conflict information single focal units having the support information are merged in a new combination mode to form new focal elements, and a shape power set formed by the new focal elements is acquired, and the new combination mode refers to merging through utilizing an operator symbol as described in the specifications; according to the information supported by each evidence, the new focal elements in the shape power set and a basic confidence designation function, information synthesis rules based on logic operation are utilized to fuse multiple evidences containing the fuzzy and high conflict information to acquire the preliminary synthesis result for target identification; according to the identification framework and the preliminary synthesis result, detected targets are identified according to preset decision rules. The method relates to the target classification field of the wireless sensor network.