35results about How to "Fully consider the relevance" patented technology

The invention relates to a statistical downscaling model forecasting factor screening method. The method comprises the steps that 1 a positional relationship graph between a weather station and a gridin a river basin is established; 2 the correlation among measured rainfall of each station, temperature and other predictand and a reanalysis data atmospheric circulation factor is deduced, includingthe correlation with the grid of the weather station and the correlation with surrounding grids, and appropriate factors are selected according to a set correlation coefficient threshold; 3 the change of a criterion certainty coefficient in a calibration period on monthly, seasonal and annual scales is analyzed; and 4 according to different scales and different factor selection methods in the step 3, a model is analyzed and tested.

The invention discloses a coupled channel coding processing method, comprising: in each code unit of current frame transform domain of the coupled channel, determining a channel as main channel and calculating the relation parameters of another channel and the main channel; making quantization and coding processing on the main channel and the relation parameters. And the invention discloses a coupled channel decoding processing method, comprising: for the transform domain signal derived from inverse quantization and recovering the coupled channel according to the main channel and the relation parameters; besides, the invention discloses an audio coder and decoder. And the invention can effectively reduce coding and decoding redundancy rate and raise coding efficiency.

The invention provides a culture medium for germinating boletus spores, and the culture medium comprises a dried chroogomphus rutilus product, a PDA (Potato Dextrose Agar) culture medium and water. The invention also provides a method for preparing the culture medium and a method for germinating the boletus spores by adopting the culture medium. The culture medium provided by the invention has the advantages of simple formula, easiness for preparation, more spore germination, regular colonial morphology, thick and dense hypha, and the like.

The invention relates to a transmission line tower lightning strike warning method based on a neighborhood maintenance embedding algorithm, and belongs to the field of transmission line safety monitoring. According to the micro-topography and micro-meteorological information of the transmission line pole tower, such as the elevation of the pole tower, the calling height, the meteorology, the topography and geomorphology of the pole tower, the circumference situation of the pole tower 50m, the soil condition and the like, the implicit local model information is extracted by using the neighborhood preservation embedding algorithm (NPE). Before modeling, the data should be collected and sorted. For the existing historical micrometeorology, microtopography and tower ontology of transmission line corridor, the description of literal data in the information literature should be transformed into numerical data and stored in the database for historical data modeling by setting specifications.In the real-time monitoring, the newly acquired micro-meteorological data are stored in the database and micro-terrain after being processed by the above specifications, and the tower body data are used by the on-line monitoring module for processing.

The invention discloses an automatic court case division method, which comprises the following steps of: carrying out attribute analysis on a to-be-distributed case to obtain a case type of the to-be-distributed case; establishing an intelligent case division model according to the attributes of the legal officers; wherein the attribute of the legal officer comprises historical case data of each legal officer and actual factors of the current workload of each legal officer, and the actual factors comprise the number of cases distributed by the legal officer and the association relationship ofcase parties; and analyzing the case type of the to-be-allocated case according to the intelligent case division model, and automatically allocating the to-be-allocated case to the corresponding law officer. According to the automatic case division method and system for the court cases, the actual factors of case division can be fully considered, the cases are reasonably distributed to the most appropriate law officers, the situations that the trial time is long and the trial is unreasonable can be reduced, and therefore the trial efficiency can be effectively improved.

The invention discloses a multi-attribute optimal route selection method applied to a low orbit information network and belongs to the field of satellite communication. The method comprises the following steps of firstly, selecting N attributes capable of representing the network quality; secondly, computing evaluation functions of attribute values of all sides in an entire-network topological structure; thirdly, computing a Choquet fuzzy integral value Am of each side in the entire-network topological structure about the evaluation functions of N attributes capable of representing the network quality, wherein m is equal to 1-M; and lastly, taking the fuzzy integral value Am as a measurement weight of the sides in the network and utilizing a Dijkstra algorithm to compute to obtain an optimal route, wherein m is equal to 1-M. the method takes the Choquet fuzzy integral based on fuzzy measure as an integrated operator, multi-attribute parameters are transformed to a single synthesized attribute evaluation parameter, and then the Dijkstra algorithm is utilized to carry out route selection. The method has the following advantages that (1) the optimal route under the multi-attribute route conditions can be obtained; (2) the route selection algorithm of nodes has low complexity; and (3) the parameter adjustment is flexible and the adaptability is strong.

The invention discloses a quick channel simulation method and a quick channel simulation device of an amplify-forward relay system. The quick channel simulation can be performed for the amplify-forward relay system, a general simulated channel from a transmitting terminal to a receiving terminal can be rapidly generated after number of antennas and correlation coefficient of the transmitting terminal, a relay terminal and the receiving terminal and independent average of Rayleigh channels and variance are acquired. Correlation channels are established from a transmitter to the relay terminal and the terminal to a receiver, then correlation matrix of the general simulated channel is calculated according to the correlation coefficient of the transmitting terminal, the relay terminal and the receiving terminal; and finally a channel model is established according to the correlation matrix of a general channel. The quick channel simulation method for the simulations of the amplify-forward relay system has the advantages that correlation of a base station terminal, the relay terminal and the receiving terminal and transceiver link correlation are fully taken into the consideration of the established model, and an entire link can be simulated truly and accurately by the model; definition is strictly abided in cultivating the correlation coefficient to make the same accurate and reasonable; and the whole link can be simulated from the transmitter to the receiver to achieve effects of convenience and conciseness.

The invention relates to a method and device for obtaining an identification model, electronic equipment and a storage medium, and belongs to the technical field of deep learning, and the method comprises the steps: determining a first identity category to which each piece of sample data belongs according to a first identification model in the process of training the identification model; according to a first identity category and a second identity category to which the sample data belongs, determining the weight of a first probability in the model training process, the first probability beingthe probability that the sample data belongs to the second identity category, and the second identity category being the identity category to which the sample data actually belongs; and performing iterative training on the first recognition model according to the first probability and the weight of the sample data to obtain a second recognition model. According to the method and the device, the loss value of the sample data is calculated through the weighted first probability to carry out model training, and the correlation between classes in the model training process is fully considered, sothat the accuracy of identifying the model is improved.

The invention discloses a rolling bearing fault diagnosis method under an incomplete sample condition. The method comprises the steps that firstly, collecting vibration acceleration signals of a rolling bearing through an acceleration sensor, conducting frequency domain feature extraction on vibration acceleration, selecting extracted frequency domain features, and constructing and an input feature vector of a fault diagnosis model; secondly, constructing a reference evidence matrix table and a joint reference evidence matrix table; determining the correlation between different reference evidences according to the joint evidence matrix table; fusing a plurality of reference evidence combinations activated by an input sample vector, further fusing fusion results by adopting an evidence reasoning rule to determine a parameter optimization model, and finally performing fault diagnosis on the rolling bearing based on an optimal parameter set. According to the method, correlation between evidences is fully considered, sample fault features are effectively recognized, and effective diagnosis of the typical fault mode of the rolling bearing under the condition that missing values exist insample data can be well achieved.

The invention relates to the technical field of health management, in particular to a health monitoring system for a smart bracelet which comprises a bracelet body, and a sleep monitoring module, a pulse detection module, a body temperature detection module, a sweat detection module and a main control module are arranged on the bracelet body; wherein the sleep monitoring module, the pulse detection module, the body temperature detection module and the sweat detection module respectively collect sleep data, pulse data, body temperature data and sweat of a user and respectively generate a sleepanalysis conclusion, a pulse analysis conclusion and a sweat analysis conclusion; and the main control module analyzes the sleep analysis conclusion, the pulse analysis conclusion, the body temperature data and the sweat analysis conclusion to generate a health detection conclusion. By adopting the scheme, various data of the user can be accurately collected and analyzed, and the user condition iscomprehensively reflected through the analysis result.

The invention discloses a main shaft bearing and cutter composite fault diagnosis method and system based on multiple labels and multiple classifications, and belongs to the technical field of machine tool main shaft fault diagnosis. The method comprises: marking collected vibration signals during the machining of a machine tool main shaft in a mode that one sample corresponds to a plurality of fault labels; inputting the marked multi-label samples into a multi-label multi-classification model to obtain the probability of each fault classification; and calculating a loss function of the multi-label multi-classification model based on the probability of each fault classification, training the multi-label multi-classification model by using the loss function, and realizing compound fault diagnosis of the machine tool main shaft by using the trained multi-label multi-classification model. Therefore, the number of health conditions during sample marking can be reduced, and the complexity of problems and the calculation amount of model training can be reduced. In addition, the invention further provides a health index weighted calculation method, which considers the influence degree of different parts on the performance of the machine tool main shaft, and is more comprehensive, scientific and reliable in the evaluation result.

The invention discloses an improved fuzzy comprehensive evaluation selection method and system for a charging facility access point, and a medium. The method comprises the following steps: determining an index system; the influence indexes are converted into Vague value data; constructing an index layer fuzzy evaluation matrix based on a Vague value; carrying out weight calculation on the basis of the value; calculating a fuzzy comprehensive score of the time period tau; and calculating a fuzzy comprehensive score considering the time sequence weight. According to the method, the index values and the initial weights are represented by the vague values, the schemes are selected based on the Vague value similarity, the relevance between the indexes is fully considered, the ranking of the scores of the access schemes is obtained by comparing the similarities between the candidate schemes and the ideal schemes, and support is provided for selection of the charging facility access points. Besides, the comprehensive evaluation process is perfected from a time sequence perspective, time sequence weights are set based on a typical charging station load curve and artificially divided charging time periods, and weighted combination is carried out on evaluation results based on the time sequence to obtain a corrected comprehensive score.

The invention relates to an audio signal processing method, computer equipment and a computer program product. The method comprises the following steps: acquiring a plurality of wave crest points in a time domain sampling sequence of an audio signal, and determining a current to-be-analyzed wave crest point in the plurality of wave crest points; determining a plurality of candidate wave crest points associated with the current to-be-analyzed wave crest point; obtaining a periodic point probability of each candidate wave crest point, and determining a target wave crest point of which the periodic point probability meets a preset probability condition from the plurality of candidate wave crest points; taking the target wave crest point as a current to-be-analyzed wave crest point, and returning to execute the step of determining a plurality of candidate wave crest points corresponding to the current to-be-analyzed wave crest point until the wave crest points in the time domain sampling sequence are traversed to obtain at least one determined target wave crest point; the fundamental frequency period of the audio signal is determined based on the interval between the at least one target wave crest point, accurate identification of the period point is realized, and the fundamental frequency period of the audio signal can be determined efficiently and accurately.

The invention relates to planning construction evaluation, in particular to a power distribution network planning construction evaluation method, which comprises the following steps of: establishing an index system structure reflecting the quality of a planning scheme, evaluating the index system structure through a priority weight method, performing dimensionless processing on an evaluation result to obtain a factor set, establishing fuzzy mapping from the factor set to a planning evaluation set, and evaluating the planning construction of a power distribution network. The method comprises the steps of obtaining a planning evaluation result, evaluating the risk event occurrence possibility based on historical data, evaluating the influence degree of the risk event on construction work, and obtaining a construction evaluation result according to the risk event occurrence possibility and the influence degree of the risk event on the construction work; according to the technical scheme provided by the invention, the defect that the planning and construction of the power distribution network cannot be comprehensively and effectively evaluated in the prior art can be effectively overcome.

Embodiments of the present specification describe a method and apparatus for predicting a first attribute of a first node in a graph network. According to the method of the embodiment, the time sequence representation of the first node and the time sequence representation of the second node are determined based on the historical value of the first attribute of the first node and the historical value of the first attribute of the second node serving as the neighbor of the first node, and then the time sequence representation of the second node is aggregated into the time sequence representation of the first node. A final characterization capable of reflecting the timing offset between the first attributes of the first node and the second node is obtained. A future value of the first attribute of the first node can be further predicted based on the final characterization. In this way, the relevance and dependency between the nodes are fully considered, so that the accuracy of predicting the first attribute of the first node can be improved.

The invention discloses an image quality evaluation method and system based on gray characteristics, and the method comprises the following steps: S1, carrying out the partitioning of a reference image and a to-be-evaluated image, and respectively dividing the reference image and the to-be-evaluated image into a first sub-block image and a second sub-block image with preset sizes; s2, calculatinggray characteristic indexes of each first sub-block image and each second sub-block image; s3, dividing the first sub-block image and the second sub-block image into a first category and a second category according to the gray characteristic indexes; s4, respectively extracting a first feature of each first sub-block image and a second feature of each second sub-block image in the first category;and S5, respectively extracting a third feature of each first sub-block image and a fourth feature of each second sub-block image in the second category. According to the method and system, the quality of the image can be accurately evaluated, the algorithm is simple, the correlation between pixels is fully considered, and the method and system have very high practical value.