30results about How to "Realize optimal selection" patented technology

The invention relates to a structural design optimization method for a deepwater catenary mooring rope. The method aims at an 'anchor chain-steel rope-anchor chain' three-section combined deepwater catenary mooring rope, structural parameters of length of each section of the rope, top pretension, mooring horizontal radiation distance and the like are determined through iterative computation by giving consideration to specific requirements of design specifications on various indicators under the condition of given rope specifications, operating water depth and allowable limit horizontal offset of a floating body, and accordingly horizontal restoration characteristics of the rope reaches optimum under the condition of controlling total steel consumption and mooring load, and then structure types and stress situations of the rope under different states are computed to bring convenience to type selection of mooring equipment. Compared with existing commercial software such as mooring analysis software MOSES and SESAM, the method has the advantages of oriented design, high practicality, high convergence speed and the like, achieves optimal selection of various design parameters and can be used for preliminary scheme design and performance evaluation of deepwater floating type platform catenary mooring systems.

The invention relates to a virtual network mapping method for realizing the topology awareness based on historical data. The method comprises the following operation steps: (1) according to a historical data set which is accumulated by a bottom layer physical network and is successfully mapped by a virtual network, calculating a dependency matrix M between nodes of the bottom layer physical network; (2) according to the size requirement of virtual nodes in the virtual network on central processing unit (CPU) resources, sorting all the virtual nodes of the virtual network from big to small; (3) according to the dependency matrix M, sequentially carrying out node mapping from the virtual nodes to the bottom layer physical nodes according to a certain sequence; and (4) after completing the node mapping, realizing mapping from a virtual link of the virtual network to a physical path of the bottom layer physical network according to a set link mapping method. The method disclosed by the invention realizes the scientific evaluation on the resource capacities of the bottom layer physical network and the optimization selection of the node mapping by sensing a topological structure of the virtual network, and improves the long-term average success rate of the virtual network mapping.

The invention belongs to the technical field of image processing, and specifically relates to a lightweight incisional hernia patch three-dimensional ultrasonic image feature extraction method. The method comprises the steps of firstly extracting related textural feature parameters of regions to be classified in three-dimensional volume of interest (VOI) of an automated three-dimensional breast ultrasound (ABUS) image in automatic quantification manner by using textural feature extraction algorithm so as to be used for differentiating a patch and a fascia; then introducing three-dimensional textural parameters and three-dimensional location parameters to improve the robustness of a lightweight patch classification and recognition algorithm in allusion to a problem that two-dimensional textural parameters are sensitive to spatial transformation such as post-operation curling and contraction of an incisional hernia patch; and finally performing feature selection by using a distance-between-class algorithm and a sequential forward selection method. The method provided by the invention is good in feature selection effect, high in efficiency, capable of effectively improving the classification accuracy of lightweight incisional hernia patch three-dimensional ultrasonic images, and convenient for automatic classification and recognition.

The invention discloses a transformer top oil temperature anomaly monitoring method based on multi-dimensional information, which comprises the following steps: A, initializing a CS algorithm, establishing a fitness evaluation model of a bird nest position, and initializing a fitness value; B, calculating a global optimal solution and a local optimal solution of each bird nest position; C, respectively constructing a Susa thermal circuit calculation model and an SVR regression compensation model according to the identified parameters; D, based on the Susa thermal circuit calculation model, obtaining a preliminary top oil temperature prediction value; E, based on the SVR regression compensation model, obtaining a final prediction value of the top oil temperature; and F, carrying out short-term trend prediction on the residual error after moving average by adopting an ARIMA method. According to the scheme, the environmental conditions of the transformer are fully considered, and the keyparameters in the temperature rise model are identified and corrected, and the residual error of the top-layer oil temperature is subjected to trend prediction, and the monitoring precision of the top-layer oil temperature of the transformer is improved.

The invention discloses a method for adjusting the surface luminosity of a mold on the basis of a laser-engraving technique. The method comprises the steps that firstly, a set of pattern grayscale drawing file adopting lasers for luminosity adjusting is developed, the pattern grayscale drawing file comprises a plurality of different luminosity adjusting layers, miscellaneous points are arranged onall the luminosity adjusting layers in a distributed mode and are even, and color gradation is accurate; and then, the pattern grayscale drawing file is downloaded to a laser engraving machine, by combining with the laser-engraving technique, engraving parameters of the laser engraving machine are set again, and the different luminosity adjusting layers are applied to an existing main pattern tochange the surface luminosity of a cavity. After luminosity adjusting through the method, the luminosity of a product can be reduced, thus the plastic feeling of the product is weak visually, the leather feeling is stronger, and thus the grade of the product is improved; and additionally, the luminosity in the cavity of the mold is evenly distributed through the luminosity adjusting mode, consistency of the luminosity is ensured, and the service life can be prolonged.

The embodiment of the invention discloses a facial expression recognition method and device, equipment and a medium, and the method comprises the steps: carrying out the marking of key points on eachexpression image in at least one expression image group, wherein each expression image group comprisse two images of different facial expressions of the same user; based on each marked expression image group, extracting an original feature set related to the facial expression by using a height deformation differential homoembryonic metric mapping curve registration algorithm; determining a targetfeature subset from the original feature set by using a support vector machine recursion feature elimination algorithm accompanying correlation deviation elimination; and training an identification model for identifying the facial expression based on the target feature subset. According to the embodiment of the invention, the method solves a problem that the facial expression recognition accuracyis relatively low due to the existence of relatively numerous redundant and noise in the extracted facial features in the existing method, and improves the facial expression recognition accuracy.

The invention provides a rove vertical transmission feeding and spinning device and method. The spinning device comprises a rear drafting roller pair composed of a rear roller and a rear rubber roller, a middle drafting pair composed of a middle roller and a middle rubber roller and a front drafting pair composed of a front roller and a front rubber roller. The rear roller adopts a roller sleeve which is connected to a roller shaft through a separating bearing, the rear rubber roller adopts a rubber roller sleeve which is connected to a rubber roller shaft through a separating bearing, and retractable gears with retractable teeth on the surfaces are installed at head ends of the rubber roller shaft and roller shaft. Separate servo motors are connected with the retractable gears through gear groups, so that optional driving of the rubber roller shaft and the roller shaft is achieved, selection between active feeding of rove under driving of the roller sleeve and active feeding of the rove under driving of the rubber roller sleeve is achieved, selection of vertical transmission feeding of the rove according to different rove features is correspondingly achieved, and thus optimized selection of a spinning process is achieved.

The invention discloses an efficient milling parameter optimization method for rough machining of a difficult-to-machine material fused with tool wear monitoring. The method comprises the steps that firstly, an optimization problem characterization model with the machining efficiency as a target and the spindle rotating speed, the radial cutting width and the axial cutting depth as optimization variables is established, and multiple constraint conditions such as a basic parameter feasible region, stability, spindle torque and power are considered; secondly, the problem of tool abrasion caused by the difficult-to-machine material is considered, the quantitative relation between the three-phase current of the main shaft and the milling force is established, and real-time estimation of the tangential specific shear force coefficient is achieved; furthermore, a numerical solution method based on random vector search is provided, an optimization process integrating offline optimization and real-time monitoring is given, and optimal processing parameters are obtained. According to the parameter optimization method provided by the invention, the rough machining efficiency of the difficult-to-machine material can be greatly improved, and efficient flutter-free milling machining is realized.

The invention belongs to the technical field of unmanned aerial vehicle photogrammetry and power transmission line path selection, and particularly relates to a power transmission line automatic lineselection method based on unmanned aerial vehicle photogrammetry. The method comprises the basic steps of making an image of a planning area, automatically classifying image feature ground objects, automatically searching a power transmission line path, evaluating a pre-selected search scheme result and the like. According to the invention, the unmanned aerial vehicle is used for carrying out real-time flight processing on the planned area and key ground objects thereof; High-resolution image data of related areas are obtained efficiently, the optimization degree of power transmission line path selection and the reasonable effectiveness of paths can be effectively improved through an image processing technology and an automatic power transmission line path searching and selecting algorithm, and optimal selection of power transmission line paths is achieved.

The invention discloses a current harmonic suppression device and method of a motor and the motor. The device comprises a first control module and/or a second control module, and further comprises: acontrol circuit used for controlling the motor. The control circuit of the motor comprises a rotating speed outer loop control circuit and a current inner loop control circuit, wherein the first control module is used for suppressing current harmonics in the rotating speed outer loop control circuit and/or the current inner loop control circuit by adopting a mode of optimizing parameters of a PI controller in a control circuit of the motor; and/or the second control module is used for suppressing current harmonics in the rotating speed outer loop control circuit and/or the current inner loop control circuit by adopting a mode of adding a time delay link and adding phase compensation to a repetitive controller in the control circuit of the motor. According to the scheme, the problem that the current harmonic suppression capacity of the permanent magnet synchronous motor is weak can be solved, and the effect of improving the current harmonic suppression capacity of the permanent magnet synchronous motor is achieved.

The invention provides a goods selection method, a goods selection system and electronic equipment. The goods selection method comprises the following steps: determining the number of distributable goods corresponding to each category in preset categories according to shelf resources; the selectable commodities in each category are associated with corresponding commodity identifiers; the commodity identifier comprises at least one of a potential new product, a commodity which must be covered, a differentiated demand commodity and a commodity without a special identifier; determining the commodity expressive force of each selectable commodity according to a preset evaluation index, and obtaining the commodity expressive force ranking of the selectable commodities; and according to a preset priority order of the commodity identifiers, determining the shelf commodities of each category from the commodity expressive ranking according to a descending order of the priorities until the number of the selected shelf commodities reaches the number of distributable commodities corresponding to the category, and obtaining a shelf commodity list, thereby analyzing consumer demands through richer dimensions, and improving consumer experience. The unified management operation of the headquarters is met, the differentiated category requirements of the stores are reflected, and the optimal selection of the commodities is realized.