50 results about "Double weight" patented technology

The invention discloses a vehicle driving condition establishment method combining principal component analysis with fuzzy c-mean clustering. The method comprises the steps of extracting satellite positioning data of each road traffic condition in a vehicle dynamic monitoring system of a road transport enterprise, and calculating and dividing the data into small sections of micro-strokes; and performing calculation of characteristic parameters such as an average speed, an idle time proportion and the like for each micro-stroke, obtaining a matrix of a sample quantity (row) X the characteristic parameters (column), adopting mean normalization and principal component analysis for matrix data, selecting preorder principal components which meet the conditions that the cumulative contribution rate of characteristic values of the principal components is greater than 85% and the principal components can comprehensively reflect all the characteristic parameters, performing fuzzy c-mean clustering analysis on scores of the principal components, and clustering the micro-strokes into different groups, namely, screening sub-conditions. An initial synthesis condition is smoothed by adopting a filter with a double-weighted smoothing kernel function. According to the method, existing satellite positioning data is fully utilized; compliance testing is easily carried out on a dynamometer; relatively high universality is achieved; and the research cost of vehicle driving condition establishment is reduced.

The invention relates to a cyanobacteria biomass spatial-temporal change monitoring and visualization method based on a remote sensing image. The method comprises the following steps: (1) pre-processing the remote sensing image of a research region, and constructing a normalized difference cyanobacteria bloom index (NDI-CB); (2) optimizing characteristics of the remote sensing image by using a characteristic optimization model based on VPRS (Variable Precision Rough Set)-GID (Grey Incidence Decision), and obtaining an optimized multi-characteristic space; (3) establishing a double-weighted SVM (Support Vector Machine) classification model based on a wavelet kernel according to the multi-characteristic space, performing extraction identification and change detection on the spatial distribution information of cyanobacterial bloom, and performing comprehensive verification and precision analysis by combining field observation data; and (4) performing overlapping display on the processed remote sensing image, GIS (Geographic Information System) vector data and the field observation data, thereby realizing the analog simulation of spatial-temporal change processes and rules of erupting the cyanobacterial bloom. Compared with the prior art, the cyanobacteria biomass spatial-temporal change monitoring and visualization method based on the remote sensing image has advantages of high cyanobacteria identifying precision and reliability, and the like, and is beneficial to analyzing and judging of causes and distribution changes of the cyanobacterial bloom.

The invention discloses a variable-freedom-degree modular mechanical arm. According to the variable-freedom-degree modular mechanical arm, the modular design idea is introduced into the design of light mechanical arms, and modular mechanical arms with different freedom degrees can be obtained through splicing by means of multiple modular mechanical arm joints. The variable-freedom-degree modular mechanical arm comprises an output flange shaft, a harmonic reducer, a hollow shaft motor, a brake device and a double-weight disc positioning mechanism, wherein the output flange shaft is composed of an output flange and an output shaft, and the output shaft is sleeved with the harmonic reducer, the hollow shaft motor, the brake device and the double-weight disc positioning mechanism. The harmonic reducer is fixed to the output flange and is also fixed to a hollow shaft of the hollow shaft motor. The hollow shaft drives the output flange to rotate after rotating to be decelerated through the harmonic reducer. The brake device is used for conducting emergency brake when an emergency occurs. The double-weight disc positioning mechanism is used for obtaining the speed information of the hollow shaft and the position information of the output shaft. All the components are controlled through a servo driving circuit. The variable-freedom-degree modular mechanical arm has the advantages of being higher in environmental adaptability and high in functional expandability, flexibility and adaptability.

The invention relates to an offshore water chlorophyll a concentration remote sensing inversion method based on an improved random forest. remotely sensing image data by utilizing a time sequence; combining timing buoy observations, The method comprises the following steps of: establishing an intelligent remote sensing inversion model to carry out remote sensing inversion on the chlorophyll a concentration of an offshore water area by taking time continuous space sparse compensation as a modeling strategy and adopting an improved random forest-double-weight random forest method to obtain a very good inversion result, and visually and accurately displaying the spatial distribution of the chlorophyll a concentration of the offshore large range. The invention can provide a macroscopic, continuous and effective method for monitoring the concentration of chlorophyll a in the near-shore water body, can make up the deficiency of the traditional chlorophyll a concentration monitoring, and hashigher practical value.

The invention discloses a structural reliability method based on dynamic weight response surface under mixed uncertainty. The invention is applied to the field of reliability technical field, and aimsat structural reliability problems under mixed variables. The method comprises the following steps of determining a fitted sample of a current iterative response surface; fitting and getting the response surface of the current iteration by weighted least squares; getting the reliability design point of the current response surface according to the hybrid variable decoupling method; stopping the iteration, when the value of the random variable part of the reliability design point obtained by two adjacent iterations satisfies the convergence criterion; calculating the failure probability of thestructure by Monte Carlo simulation according to the response surface obtained from the last iteration. The invention constructs the response surface, so that the limit state function in the standardnormal space is explicitly approximated in the form of a quadratic response surface, which facilitates subsequent reliability analysis. And a double weighting mechanism is introduced to effectively improve the accuracy and computational efficiency of the response surface method.

The invention discloses a lithium cobaltate batching system based production state prediction method. The method includes building a health status evaluation index of a lithium cobaltate batching system; and performing prediction on the health index of the batching system by using a double weighted based kernel principal component regression least squares support vector machine algorithm, whereinthe prediction step includes the following steps: firstly, extracting non-linear characteristics of an input variable, and extracting a main constituent from large to small according to contribution rates; then, processing a data set, and determining the correlation between an input vector and an output vector; and finally, performing modeling prediction, performing local weighing on a training sample and an input sample, and optimizing model parameters. The method adopts the defined health index, primary and secondary weighting matrixes can be built during a modeling process through the correlation between the input sample and an output sample and the distance between the input sample and a query sample; and the primary weighting can be performed before the sample is input to the model, the secondary weighting can be adopted to a model estimation error during the modeling process, and therefore, the influence brought by production data errors or omission on prediction algorithms can be reduced.

The invention provides a goods identification method. The goods identification method comprises the steps that the weight data and location information of a taken-out goods are compared with the goodsweight data and the position information stored in advance in an unmanned display cabinet built-in storage module to generate a comparison result; and the category and quantity of goods are identified according to the comparison result. The goods identification method uses gravity sensing for identification, and is not limited by the shape and size of the goods. As long as the goods can be placedon a tray, the goods can be identified, and the category number of the goods to which the goods identification method can be applied is greatly expanded. Since the position information of the goods is recorded at the same time, even the goods of the same weight can be accurately identified. The problem of the double weight is further effectively solved. Even if the weight of a plurality of goodsis the same as the weight of other goods, the identification can still be effectively and correctly realized by judging the position of the goods. The problem of identification of very similar goods is further solved. The goods identification method has the accuracy, efficiency and ease of use of goods identification. The invention further provides a goods identification device.

The invention discloses a frame rate up-conversion method based on the mixed matching of chromaticity, used for improving the visual quality of a video sequence. The method comprises the steps of firstly designing a block matching criterion by using a chromaticity mixed matching model, wherein the block matching criterion can reflect the level of a difference between the brightness of the video sequence and a chromatic aberration channel; then using an improved three-dimensional recursive search method to compute forward and backward initial motion vector fields, on the basis, providing a time-space motion vector purification method, implicitly adding time-space smooth constraint into the motion vector purification method, and thus obtaining a smoother motion vector field; then providing a high fault-tolerant motion vector smoothening method to inhibit abnormities existing in the motion vector fields; and at last, in order to reduce edge blurring and shielding problems, providing a double-weighted overlapped block motion compensation method, and using the forward and backward initial motion vector fields to jointly generate an interpolating frame. According to the method, the subjective and objective quality of the interpolating frame can be significantly improved, and the low computation complexity is ensured.

The invention provides a multiwave beam double-layer weighing parallel interference offsetting method, used in intelligent antenna-used CDMA system and including the steps: receiving antenna array cell signal and forming several wave beam signals of each user; searching and obtaining multipath time delay information of each user; making multistage parallel interference offset processing to obtain soft output signals of each user; by decoding, obtaining bit sequence sent by each user. It also provides a corresponding receiving device to the method, including: user wave beam forming unit to receive antenna array cell signal and generate user wave beam information; multipath searcher to obtain user multipaht time delay information; inference offsetting device; user decoder to decode to obtain the user-sent bit sequence. It can effectively overcome the influence of multiple access interference on CDMA system and further improves CMDA system capacity, covering range and property.

The invention provides a flux linkage and current combined switched reluctance motor torque ripple suppression method and system. A reference flux linkage is obtained through flux linkage increment PID control of a flux linkage double-weight neural network based on deviation preprocessing, and reference current is obtained through current increment PID control of a current double-weight neural network based on deviation preprocessing; and three-phase reference current and flux linkage are obtained through flux linkage distribution and current distribution and cooperatively inputted to a two-dimensional hysteresis controller so as to obtain effective switching quantity under the constant torque. The signal processor of the system includes all the related operation modules and current and flux linkage distribution modules and the two-dimensional hysteresis controller. The signal processor receives current and position sensor signals, the switching quantity of the two-dimensional hysteresis controller is obtained through operation of all the modules and a power driver is controlled to drive the SRM to operate. The output current is converged to the reference current, and the output flux linkage is converged to the reference flux linkage so that effective control of the total torque ripple of the switched reluctance motor can be realized.

A method for double weighting parallel interference cancellation in CDMA mobile communication system, integrates ideas of both partial weighting method and weighting method based on Bayes rule. When making a decision on each symbol of the user, calculating reliability coefficient of a decision result on the symbol of the user according to the weighting algorithm based on Bayes rule; weighting regenerated signal of the symbol of the user with the reliability coefficient. During process of MAI estimating and removing, obtaining the MAI on the expected user from weighted regenerated signal of other users in chip level; and then setting a weight value, weighting the MAI with the weight value. Finally, removing weighted MAI from received signal, which means partially removing MAI produced by other users on the expected user. At the same time, the present invention also discloses a double weighting PIC method with simplified algorithm, which transfers weighting in chip level to weighting in symbol level, replacing a Hyperbolic tangent decision with a piecewise linear decision method or a look-up table method.

The invention discloses an automatic sugarcane squeezing control system. The automatic sugarcane squeezing control system comprises an automatic sugarcane conveying belt control system, an automatic header tank material level control system and an automatic seepage water and minced sugarcane weight matching control system. The weight of squeezed minced sugarcane is measured through a double-weight-measurement method, material level sensors are installed on header tanks and used for measuring the material levels of the header tanks, A DCS control system controls the speed of a presser and the speed of a quick conveying belt according to the material levels of the header tanks, stability of the header tanks is controlled, an electromagnetic flower meter and a control valve are installed on a seepage water pipeline, and seepage water is controlled. The automatic sugarcane squeezing control system can accurately and uniformly control the amount of the squeezed minced sugarcane and can accurately control the additive amount of the seepage water, the maximal efficacy of the presser can be exerted, serious consequences of production halts caused by damage to the presser due to frequent speed regulation are avoided, and meanwhile, the sugar extraction rate can be further increased, heat energy evaporated in the following process is reduced, and the most ideal effect of automatic squeezing control is achieved.

The invention discloses a double-slip tension wheel mechanism. The double-weight tension wheel mechanism is characterized by comprising a first slip, a second slip and a main motor, wherein the first slip and the second slip are transversely arranged at intervals; a rotation axis of the first slip is coincided with a rotation axis of the second clip; the main motor is used for driving the first slip. The double-slip tension wheel mechanism has the advantages that a material is pulled closely to prevent loosening through the respective slip unit under the matching actions of speed difference and friction force, the dislocation is avoided, the tension is uniform, and the product reliability is high.

The invention discloses a suspended adaptive weight reduction system for rehabilitation training. The system comprises a box body, a rope, a pre-weight-reducing system and a rope length adjusting device. The pre-weight-reducing system comprises a first pulley group, a first moving device, weight-reducing springs, hydraulic screw rods and a second moving device. The rope length adjusting device comprises a third moving device and a jacking device. The system has the advantages that the pre-weight-reducing effect is realized under the action of the weight-reducing springs and hydraulic screw rods, stretching movement of the rope between a movable pulley group and a fixed pulley group is achieved through the control of the jacking device, automated operation and quick and accurate adjustmentof the rope length are achieved, and a double weight reduction effect is achieved.

The embodiment of the invention discloses an occultation data quality control method, device and equipment and a storage medium, and the method comprises the steps of dividing the matched occultationdata and the corresponding sounding data according to an air pressure layer and a region, and obtaining the target occultation data and the target sounding data; determining the first error data and the first suspicious data based on the double-weight coefficient of the target occultation data; removing the first error data in the target occultation data to obtain first residual data, and determining the deviation data of the first residual data and the target sounding data; determining the second error data and the second suspicious data based on the double-weight coefficient of the deviationdata; removing the occultation data corresponding to the second error data in the first residual data, and obtaining the second residual data; and determining a correlation coefficient of the secondresidual data and the target sounding data, and determining the correct data in the target occultation data based on the correlation coefficient. According to the embodiment of the invention, the reliability of the background field data and the accuracy of quality control of the occultation data can be improved.

The embodiment of the invention discloses a quality control method and device, equipment and a storage medium, and the method comprises the steps: determining a double-weight coefficient of target occultation data, and determining first error data and first suspicious data in the target occultation data based on the double-weight coefficient of the target occultation data; removing first error data in the target occultation data to obtain first residual data, and determining deviation data between the first residual data and corresponding data in the target background field data; determining adouble-weight coefficient of the deviation data, and determining second error data and second suspicious data in the deviation data based on the double-weight coefficient of the deviation data; the occultation data corresponding to the second error data in the first residual data are removed, and second residual data are obtained; and determining a correlation coefficient of the second residual data and the target background field data, and determining correct data in the target occultation data based on the correlation coefficient. According to the embodiment of the invention, the quality control accuracy of the occultation data can be improved.

The mobile application malicious software detection method for the power enterprise is characterized by comprising the steps that to-be-detected software is acquired, and decompilation is conducted onthe to-be-detected software to obtain a source code of the to-be-detected software; Extracting a feature vector of the source code, inputting the feature vector of the source code into a pre-constructed SVM classification model for comparison, and determining whether the to-be-detected software is malicious software or not; Wherein the SVM classification model comprises an SVM classifier, and theSVM classifier performs iterative updating based on a double weight increment method. According to the technical scheme, the problem that a support vector machine is not suitable for classified learning of a large number of samples is solved, the SVM incremental learning algorithm based on the double-weight function is provided for learning and classifying the application samples, and the methodcan reduce the learning time to the maximum extent and improve the learning efficiency on the premise that it is guaranteed that the application classification precision is not reduced.

The invention provides a method for expanding a software defined network based on a heap structure. The method comprises that step 1, a data layer in a network system is abstracted into a multi-layer Fibonacci heap structure; and step 2, a shortest routing path is acquired by performing analysis in the acquired multi-layer Fibonacci heap structure according to the sequence from top to bottom by using a double weight extended Dijkstra routing algorithm. According to the method, the expansion process of the software defined network is effectively simplified, the shortest routing algorithm in the network is improved by combining the heap structure, and the burden of computing equipment of each node is effectively reduced at the same time.

The invention discloses convenient instant staple food with various flavors. The convenient instant staple food is produced by the following preparation method: selecting insect-free, mildew-free, fresh and clean cereal grains; and cleaning and removing impurities from the screened cereal grains; putting the cleaned cereal grains subjected to impurity removal into a hopper of a smashing machine for smashing, and screening through a screen of 10 meshes; adding water and oil into the smashed and screened cereal grains at a ratio for uniform mixing; adding water with double weight, heating to 95 to 100 DEG C, and keeping the temperature for 40 minutes, thus obtaining hot food; cooling the food, laying the food in a freezing plate, putting the freezing plate into a freeze-dry machine, starting a vacuum pump after the temperature of the material is below -35 DEG C and the cold-trap temperature is below -55 DEG C, starting to heat a shelf in a gradient manner if the pressure is below 20 Pa, and setting the initial temperature of the shelf to be -35 DEG C and the final temperature of the shelf to be 40 DEG C; controlling the vacuum pressure of the whole freeze-dry process to be 10 to 20 Pa to obtain a freeze-dried core structure; and filling a capsule layer with the freeze-dried core structure to obtain the convenient instant staple food. The convenient instant staple food is convenient to use and prepare, has various flavors, is long in storage life, guarantees sufficient nutrition, has digestion resistance and fitness effects, and is particularly suitable for being eaten by female, old people and diabetic patients.