15 results about "Bubble sort" patented technology

The invention belongs to the field of slope engineering construction, and provides a slope blasting lumpiness prediction method based on a Buble Sort-GWO-ELM model to solve the problem that the construction quality and cost control are affected due to the fact that the slope blasting lumpiness cannot be accurately predicted in the slope construction process, and the slope blasting lumpiness prediction method comprises the steps that blasting control parameters are monitored; performing data preprocessing; constructing a blasting control parameter data set; the blasting control parameters are screened by using bubble sorting in combination with a square difference algorithm, and characteristic parameters which have the greatest influence on a prediction result are selected; training an extreme learning machine (ELM) model, and performing optimization and verification by using an improved grey wolf optimization algorithm model parameter; determining optimal parameters of an extreme learning machine (ELM) model, and establishing a blasting effect prediction model; and predicting by using the blasting effect prediction model. According to the method, the blasting parameters can be scientifically predicted and reasonably controlled, the accuracy of blasting construction can be improved, and the economical efficiency and safety of the whole project can be improved.

The invention discloses an intelligent vibration sensor layout method based on cooperation of physical field modeling and hybrid optimization. The method comprises the steps that a geometric model of a target mechanical structure is acquired, and a material parameter set is extracted; the curvature and stress of the surface of the mechanical structure are calculated, and a high-sensitivity area is recognized in combination with a vibration transmission efficiency matrix; curvature self-adaptive sampling is executed in the high-sensitivity area, a candidate point set is generated based on an improved greedy algorithm, and redundant candidate points are eliminated to obtain an effective candidate point set; calculating coverage weights of the effective candidate points; adding the candidate point with the maximum coverage weight selected through bubble sorting into a sensor set, and calculating the total coverage rate once when each effective candidate point is added until the coverage rate reaches a preset value; performing global optimization based on a simulated annealing algorithm, and performing crossover and mutation operation on the selected sensor individuals; calculating the contribution degree of each sensor, and removing low-efficiency sensors until the maximum iteration value is reached. According to the invention, efficient calculation and resource configuration optimization are realized.

The utility model discloses a bubble sorting algorithm demonstration teaching aid, which can grab balls to be sorted on one or two seat bodies through a grabbing mechanism, identify digital labels on the two grabbed balls through a machine vision system and compare the sizes of the digital labels. The controller of the machine vision system controls the driving mechanism and the grabbing mechanism to be matched, the balls are sorted according to the bubble sorting step and the size of the digital labels, the bubble sorting step is demonstrated, and therefore real object demonstration of the bubble sorting algorithm is achieved.

The invention relates to the technical field of network fault diagnosis methods, in particular to a fault diagnosis method based on a hypercube network, which comprises the following steps: determining a symptom set sigma generated by mutual testing among all nodes of the hypercube network Qn; obtaining a preliminary fault node set F and a counter value C (v) of any node v according to the symptom set sigma of the Qn; performing descending sorting on the counter values of all the nodes through a bubble sorting algorithm to obtain an ordered sequence C; a part of nodes, which are ranked in the foremost position, of the ordered sequence C of the counter values are diagnosed as fault nodes, the fault nodes are added into a fault point set F, and the remaining undiagnosed nodes of the Qn are added into a fault-free point set FF; according to the fault diagnosis method, the network topology structure property of the hypercube network Qn and the test property of the diagnosis strategy are utilized, the fault diagnosis capability of the hypercube network Qn is greatly enhanced under the condition that fault nodes are rarely misdiagnosed, and the fault diagnosis method is high in efficiency.

The invention belongs to the technical field of resistance detection, and provides an electronic atomization device and a resistance determination method thereof, a medium, a device and a product, and the method comprises the steps: waiting for a first preset duration under the condition of detecting that an atomizer is connected to the electronic atomization device; when it is detected that the access duration of the atomizer reaches a second predetermined duration, bubble sorting processing is performed on the obtained resistor array to obtain a processed array, the second predetermined duration is greater than the first predetermined duration, and the bubble sorting processing is used for arranging a plurality of measurement resistors in the resistor array according to a predetermined sequence; and averaging a predetermined array in the processed array to obtain a final measurement resistor, the predetermined array including a plurality of measurement resistors collected from the end time of the first predetermined duration. Resistance measurement data fluctuation caused by contact jitter is prevented, and the precision requirement of resistance detection is met.

The invention relates to the technical field of navigation testing, and discloses an optimization method and system for adjusting an anti-interference gain of a navigation receiver, so as to avoid invalid frequent switching. The method comprises the following steps: calibrating an interference intensity threshold X and a weight matrix B of the switching gain of the navigation receiver, the weight matrix B being an M-order square matrix, and M being an integer greater than or equal to 3; segmenting the obtained group of M * M * N continuous sampling values of the external interference intensity according to a time sequence, and obtaining the median of each segment based on bubble sorting, N being the number of an odd number of sampling points greater than or equal to 5 in each segment; combining results obtained by subtracting the median of each segment from X into an M-order square matrix A according to a time sequence in an element arrangement mode from left to right and from top to bottom; performing non-filling convolution operation on the square matrix A and the square matrix B to obtain a scalar value C; judging whether the scalar value C is greater than a trigger threshold value or not, and if so, triggering a gain switching operation; otherwise, the gain switching operation is not triggered.

This invention belongs to the field of aviation electrical technology and discloses a bubble sorting method for serial-in and serial-out data based on FPGA. The FPGA uses a state machine for computation and sets a state jump pointer. At the end of each step, the state jump pointer is set to point to the state to which the next step is to jump. The sorting method includes the following steps: Step 1: Initialization; Step 2: Value retrieval; Step 3: Comparison of the last two bits; Step 4: Loop comparison; Step 5: Data output. This invention completes analog bubble sorting and filtering within the FPGA. For some smaller systems, it can eliminate the need for a CPU, saving costs while reducing the data transmission time between the CPU and FPGA, improving speed, and without affecting system stability.

The present invention belongs to the field of slope engineering construction. To address the problem of the inability to accurately predict slope blasting fragmentation during slope construction, which in turn affects construction quality and cost control, a slope blasting fragmentation prediction method based on a Bubble Sort-GWO-ELM model is proposed. The method comprises monitoring blasting control parameters; performing data preprocessing; constructing a blasting control parameter data set; screening the blasting control parameters using a bubble sort combined with a square error algorithm to select the characteristic parameters that have the greatest impact on the prediction results; training an extreme learning machine (ELM) model and optimizing and verifying the model parameters using an improved gray wolf optimization algorithm; determining the optimal parameters of the extreme learning machine (ELM) model, establishing a blasting effect prediction model; and performing prediction using the blasting effect prediction model. The present invention can improve the accuracy of blasting construction and enhance the economy and safety of the entire project by scientifically predicting and rationally controlling blasting parameters.

The invention belongs to the technical field of aviation electrical, and discloses a serial-in serial-out data bubble sorting method based on an FPGA (Field Programmable Gate Array), the FPGA adopts a state machine mode to carry out operation, a state jump pointer is set, and at the end of each step of operation, the state jump pointer is set to point to the state to which the next step wants to jump; the sorting method comprises the following steps of: 1, initializing; step 2, taking a value; 3, comparing the last two bits; 4, performing cycle comparison; and 5, outputting data. According to the method, analog quantity bubbling sorting filtering is completed in the FPGA, for some small systems, the use of a CPU can be omitted, the cost is saved, meanwhile, the transmission time of data between the CPU and the FPGA is shortened, the rate is increased, and meanwhile the system stability is not affected.

The invention discloses a CATIA-based multi-thickness plate groove automatic processing method, which comprises the following steps: extracting and decomposing a reference surface boundary curve of a plate, determining a cutting starting position and a plane translation direction, traversing a length and thickness list to generate a translation cutting plane list and a new surface list, calibrating a tail end cutting plane, and cutting to obtain a segmentation curved surface. And according to the thickness difference, the groove is processed through the groove slope ratio, and the plate with the groove is obtained through filling. The cutting position is positioned through bubble sorting and screening midpoints, the normal direction of a cutting plane is verified through a black box testing method, the groove plane distance is dynamically calculated, and a new plane is created to achieve groove transition. According to the method, the length, the thickness list and the groove slope ratio can be self-defined, the cutting starting point and the tail end boundary can be accurately positioned, the flat slide notch is automatically generated, the efficiency and precision of groove treatment of the multi-thickness plate are improved, and manual intervention and material waste are reduced.

The application discloses a kind of virtual avatar construction and memory iteration method based on multi-dimension user characteristics, it is related to virtual avatar technical field, including step one: real-time collection text data, and pre-processing;Step two: the module of distinguishing vector is calculated to the text data after pre-processing, and user portrait is constructed according to the module of distinguishing vector;Step three: according to the running law of user portrait, the running weight is calculated, and memory iteration is carried out according to the running weight.The application first quantifies semantics accurately by calculating the module of text distinguishing vector, and realizes the dynamic clustering and updating of user portrait according to the module value matching;Further, the running weight of each portrait is calculated using the Euclidean distance formula by combining the call frequency and duration;Finally, based on bubble sort and median method, high-weight memory is retained and iterated, so as to realize the continuous evolution and long-term personalized accompaniment of virtual avatar in limited resources.

The invention provides a dynamic mixing precision quantification method and system for a generative diffusion model, and the method comprises the steps: randomly distributing an initial quantification bit width for each activation layer of a core calculation unit of the generative diffusion model, and determining an initial mixing precision bit width configuration scheme; performing quantitative perception training on the generative diffusion model adopting the initial mixing precision bit width configuration scheme, and determining verification set loss of the converged generative diffusion model; according to the verification set loss and the initial mixing precision bit width configuration scheme of the generative diffusion model, an improved bubble sorting strategy and a dynamic bit width switching mechanism are adopted, the bit width configuration of each active layer of the core computing unit is circularly updated, and the optimal mixing precision bit width configuration scheme of the generative diffusion model is determined. By means of the method and device, additional hardware assistance is not needed, activation layer bit width optimization sorting and activation layer bit width difference adaptation of the automatic generative diffusion model are achieved, diffusion generation quality is improved, and computing resources are saved.

The application discloses an improved digital filter processing circuit which performs data processing on AD collected data, comprising an AD data collection module, a data processing core module and a data storage module. The AD data collection module collects data after AD conversion, outputs the data to a data processing core module for processing by a de-bounce filter algorithm, and then sends the data to a data storage module for storage. The data processing core module processes data after grouping and overlapping according to a bubble sorting form based on data stored in the data storage module. The data storage module realizes temporary storage of AD collected data and storage of data after sorting processing. The application realizes the function of data processing on AD collected data.

The present invention discloses a method for automatically processing the groove of multi-thickness plates based on CATIA. The method extracts and decomposes the boundary curve of the plate reference plane, determines the starting position of cutting and the direction of plane translation, traverses the length and thickness list to generate a translation cutting plane list and a new surface list, calibrates the end cutting plane, cuts to obtain a segmented surface, processes the groove with the groove slope ratio according to the thickness difference, and fills to obtain a plate with a groove. The cutting position is located by filtering the midpoint through bubble sorting, the normal direction of the cutting plane is verified by the black box test method, the groove plane distance is dynamically calculated and a new plane is created to realize the groove transition. The method can customize the length, thickness list and groove slope ratio, accurately locate the starting point of cutting and the end boundary, automatically generate a smooth groove, improve the efficiency and accuracy of the groove processing of multi-thickness plates, and reduce manual intervention and material waste.

The invention relates to the technical field of mining equipment, in particular to an unloading control method and system for a multi-point unloading trolley. The discharging control method comprises the steps that the material height of each stock bin is monitored in real time, and the monitored stock bin material height data are stored as a to-be-sorted sequence; executing a bubble sorting algorithm based on the to-be-sorted sequence, comparing the material heights of adjacent bins round by round and exchanging the sequence to generate a priority sequence from high to low; according to the priority sequence, the stock bins needing to be discharged preferentially at present are determined, the discharging trolley is controlled to move to the preset position of the target stock bin, and discharging operation is started; and after unloading is completed, the height of the materials in the stock bin is monitored again, and the sequencing and unloading processes are repeatedly executed. The problems of low unloading efficiency, poor dynamic adjustment capability, high energy consumption, insufficient safety and the like are solved, and the unloading precision and efficiency are improved by dynamically optimizing the unloading sequence and path.