48 results about "Cartesian product" patented technology

The invention discloses a Chinese text verification system and method based on Chinese vague pronunciation and voice recognition. The system comprises a voice collecting and processing module, a voice recognition module and a text verifying and sharing module, wherein the voice collecting and processing module is used for collecting an audio and compressing and denoising the audio, the voice recognition module is used for recognizing voices into a text, and the text verifying and sharing module is used for achieving text verification and meanwhile supports text editing and sharing. The method comprises the steps that Chinese error judgment rules based on parts of speech are defined; word segmentation is carried out on the Chinese text obtained after voice recognition; the segmented words are scanned according to the Chinese error judgment rules to find out wrong Chinese words; a vogue pronunciation table is defined based on Chinese vogue pronunciation rules; all vogue pinyin of the wrong words is found out through a Cartesian product mode; a dictionary table is inquired to obtain a candidate word set of all the vogue pinyin; a candidate error correction set is selected out of words of the candidate set of all the vogue pinyin according to a word frequency rank. By means of the Chinese text verification system and method based on Chinese vague pronunciation and voice recognition, Chinese errors, caused by Chinese vogue pronunciation, in voice recognition are eliminated, and the error correction accuracy rate of a verification algorithm is effectively increased.

A storage robot path program method based on linear temporal logic theory comprises the steps of modeling a storage environment into a weight switching system based on assignment nodes; describing complex assignment tasks of the storage system by using the linear temporal logic language (LTL); then, switching the task formula into a Buchi automatic machine through an LTL2BA tool kit; conducting cartesian product to the extensible weight switching system and the Buchi automatic machine to form a task feasible network topology; employing SPFA(Shortest Path Faster Algorithm) on the topology to search an optimal path, wherein the task feasible network topology includes storage environment information and package-taking task information, guaranteeing that the searched obtained path is the optimal path and isn't influenced by the order of the selected assignment node; mapping the obtained optimal path from the task feasible network topology to the corresponding optimal path in the storage environment, and sending the optimal path to a storage robot by radio communication through a PC to finish the packaging-taking and assignment task.

The invention relates to the field of intelligent driving, specifically discloses a driving assistance system-oriented dangerous target detection method and device, and aims at solving the problem oflow dangerous target detection precision under field complicated traffic scenes. For the aim, the dangerous target detection method comprises the following steps of: identifying a detection frame position of a dangerous target in an obtained vehicle body external image and a Cartesian product of a target type and a distance type according to a preset dangerous target detection model; obtaining a danger level of the target according to the Cartesian product and a danger level matching table; and marking a detection frame of the target in the image according to a color corresponding to the danger level. Meanwhile, the dangerous target detection device, a dangerous target storage device and a dangerous target processing device can execute the steps in the dangerous target detection method. Through above technical scheme, the accuracy of image-based dangerous target detection can be enhanced under real complicated traffic scenes, so as to prevent traffic accidents.

The invention relates to a method for searching an optimal execution plan in database query, comprising the following steps: execution plans which contain Cartesian product connection operation are not considered in the execution plan searching process (except that a query statement submitted by a user contains the Cartesian product connection operation); meanwhile, the connection relationship ofa relationship table in the statement is expressed in an image format; and finally, the optimal execution plan is searched in the image. The connection relationship of the statement expressed in the image format is as follows: points in the image represent the relationship in the query statement; two points are connected if the relationship corresponding to the two points in the image contains connection operation (including inner connection and outer connection); and the edge weight is the execution cost of the connection operation of two relationships. By using the structure, the optimal execution plan can be obtained in the concurrent execution environment.

The invention provides a shape matching identification system and the implementation method thereof, aiming at the problems in the prior art after the color and shape identifications are researched. Firstly, a digital camera is adopted to shoot the object adhered with an artificial label for the three-dimensional reconstruction and form the picture of the object; then the shape characteristic and the color characteristic of the picture are extracted through the characteristic extraction module; the shape characteristic and the color characteristic are written into a characteristic vector and normalized through the characteristic vector normalization module; finally, the normalized characteristic vector is recognized by a neural network module. The invention has the advantages that the system and the implementation method adopt the mixed matching method based on color and shape to avoid the gray-scale based matching and the multiple repeated matching acknowledgements with large computational complexity; based on the Cartesian product combination of the angle point number characteristic in the color category and the space characteristic, the artificial label point characteristics with enough quantity are generated to enable the matching operation to be finished in one-step, so as to improve the matching efficiency greatly.

The optimal strategy solution of mobile robot in dynamic environment includes the following steps: Firstly, according to the running environment of the robot, the improvement is constructed. Weightedswitching system, according to the task requirements, the task requirements are expressed mathematically by linear temporal logic (LTL), and the LTL task formulas are transformed into B u chi automataby LTL2BA toolkit. Then Cartesian product is used to get Product automata, which contains task requirement and environment information. The useless points on the feasible network topology graph are removed, and the availability of state points is further judged according to the double-label and behavior constraint criterion, thus the number of state points is simplified. The remaining points areconstructed as MDP model, and the optimal strategy is obtained by policy iteration. The invention not only solves the situation that there is no DRA, but also reduces the number of available points, reduces the complexity of the constructed MDP, and can obtain the optimal strategy more quickly.

The invention provides a method for analyzing the stability of a structural system under an uncertain information condition. The method comprises the following steps of (A) establishing a stability equation D=Func(x1, x2, ..., xi, ..., xn) of the structural system; (B) performing probability box modeling on uncertain information parameters in the structural system; (C) performing equal reliabilitydiscretization on probability boxes of the uncertain information parameters; (D) substituting the uncertain information parameters into the stability equation of the structural system and calculatinga Cartesian product; (E) obtaining a probability box model of a complete system; (F) defining a stability region and a risk region of the system; and (G) calculating areas of the corresponding regions to quantitatively analyze the stability of the structural system. The method has the beneficial effects that the probability boxes are adopted for expressing the uncertainty; not only random uncertainty of the parameters in the system but also cognitive uncertainty can be expressed; the problem of parameter uncertainty in the system model is better solved; and the stability of the structural system is analyzed in combination with the method, so that the accuracy of analyzing the stability of the structural system is improved.

The invention discloses a combined-feature extraction method of internet-of-vehicle big-data risk control. The method comprises the steps of: obtaining basic data of an internet-of-vehicle user, and generating an initial feature set according to the basic data; calculating Cartesian products of the initial feature set and the same, and generating a second-order combined-feature set; and then extracting second-order combined-features, which are in the second-order combined-feature set and accord with a preset condition, to form a second-order candidate feature set, and calculating Cartesian products of the second-order candidate feature set and the initial feature set to generate a third-order combined-feature set; and further, outputting high-order combined-features, which accord with a preset order number, according to the above iteration process. The invention also discloses a combined-feature extraction device of internet-of-vehicle big-data risk control and a storage medium. The method constructs linear and nonlinear features through a method of obtaining the Cartesian products to improve accuracy of risk control results.