57 results about "Sparrow" patented technology

The invention relates to the technical field of data driving and landslide surge disaster prevention and control, and discloses a landslide surge height prediction method and system based on a sparrow optimization random forest model.The method comprises the steps that for a target landslide area, a corresponding landslide surge physical model is built, and test groups with different landslide volumes and water depths are set for testing; a corresponding test data set is obtained, and equal-proportion scaling is carried out according to Froude similarity criteria; the method comprises the following steps: preprocessing test data to obtain a corresponding data set, and dividing the preprocessed data set into a training set and a test set; building a sparrow optimized random forest model, setting input values of various parameters, enabling the training set to train the sparrow optimized random forest model, and predicting the maximum height of the landslide surge by using the label data set and the trained sparrow optimized random forest model. The system comprises a data acquisition module, a data division module and a landslide surge prediction module. According to the method, the maximum height of the landslide surge can be accurately predicted.

The invention is suitable for the technical field of water resource management and evaluation, and provides a method for evaluating the toughness of a drainage basin water resource system, which comprises the following steps: analyzing the current situations of drainage basin water resources, social economy and ecological environment, and constructing an evaluation index system from three stages of resistance, restorability and adaptability of the toughness of the drainage basin water resource system; performing standardization processing on the index system by using a maximum and minimum value method; a projection pursuit model based on a sparrow search algorithm is adopted to calculate toughness indexes of each stage and the whole water resource system, and multi-dimensional data is converted into a one-dimensional projection value; constructing a projection index function to solve an optimal projection vector value; and a projection objective function is determined by adopting a projection pursuit model based on a sparrow pursuit algorithm, an optimal projection vector is found finally, and a comprehensive evaluation index of the toughness of the water resource system is calculated. According to the method, the authenticity of original data can be reserved to the maximum extent, the water resource system toughness is defined, and targeted measures are provided for improving the watershed water resource system toughness.

The invention belongs to the technical field of physiotherapy, and particularly relates to a household physiotherapy instrument which comprises a moxibustion head, a movement assembly, a telescopic assembly and a base. A first telescopic section of the telescopic assembly is arranged on the base, and a second telescopic section is connected with the first telescopic section through a steering telescopic joint; the motion assembly comprises a sparrow-pecking action mechanism and a reciprocating action mechanism, the power end of the sparrow-pecking action mechanism is detachably connected to the second telescopic section, and the power end of the reciprocating action mechanism is arranged at the execution end of the sparrow-pecking action mechanism; the moxibustion head is detachably connected to the execution end of the reciprocating action mechanism; at least one of the moxibustion head, the movement assembly and the telescopic assembly can be stored in the base, the physiotherapy instrument drives the moxibustion head to automatically achieve the physiotherapy means of a sparrow-pecking method and a reciprocating method through multiple actions of the movement assembly, and the physiotherapy instrument is closer to professional operation; the base not only has a supporting function, but also can at least accommodate part of components so as to reduce space occupation; the telescopic assembly, the movement assembly and the moxibustion head are detachably connected, dismounting and mounting are convenient, and the user experience is better.

The invention discloses a path planning method based on hybrid strategy sparrow simulated annealing, and belongs to the field of unmanned aerial vehicle navigation of automatic driving and low-altitude economy. The method comprises the following steps: firstly, performing population initialization processing on a sparrow algorithm, and initializing the position of a sparrow population by adopting a cross recombination mechanism and an elite reverse learning strategy of a class genetic algorithm, so that the sparrow population is more abundant in distribution in a matrix space; secondly, the diversity of position solutions, the search probability of optimal solutions and the overall fitness are improved through a'wisdom 'sparrow trust mechanism of a nonlinear convergence inertia factor; and finally, selecting a'wisdom 'sparrow group with higher fitness according to a proportion, and jumping out of local optimum by using a sequence disturbance simulated annealing algorithm to achieve the shortest path of path planning. According to the method, search precision and search efficiency are considered, and it is guaranteed that the simulation mobile robot or the unmanned aerial vehicle has better stability and convergence capacity in the path planning optimization process; and when the map environment is complex or multiple machines work cooperatively, a shorter optimization path is provided.

The invention relates to the technical field of unmanned aerial vehicle path planning in a complex environment, and provides a complex environment unmanned aerial vehicle path planning method based on Chebyshev chaotic mapping sparrow optimization. Under the constraint of flight distance and height, a total cost function is constructed, Chebyshev chaotic mapping is utilized to initialize a sparrow population, population diversity is improved, global search and local development capabilities in an exploration rate balance position updating process are introduced, a producer and follower step length adjustment strategy based on the exploration rate is adopted, and a sparrow swarm optimization algorithm is established. According to the method, the self-adaptability of the step length in the position updating process of the producer and the follower is improved, the minimization of the total cost function is realized in the process from the early global search of the minimization of the total cost function to the later focusing local search, the optimal solution of the total cost function is sought, and the flight path which is short in distance, low in energy consumption and capable of avoiding the threat source is planned for the unmanned aerial vehicle.

1. Name of the product in this design: Copper relief craft (Two sparrows bringing good fortune). 2. Purpose of this design: for interior decoration. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key features: the front view.

The present invention discloses a digital image tilt prediction and correction method based on an improved sparrow algorithm. The angle of adjustment is predicted to make the irregularly distributed tilted digital image reach an optimal position. Because the digital image has the characteristics of narrow and irregular shape, in order to increase the accuracy of adjusting the tilt angle, the ratio of the height change ratio to the width change ratio is used as the basis for adjusting the tilt angle. The ratio reaches the optimal value, thereby satisfying the optimal adjustment angle. The present invention improves the sparrow search algorithm, uses cubic chaos mapping to initialize the sparrow population, increases the diversity and randomness of the initial population of the algorithm; introduces nonlinear inertia weights to improve the global optimization ability; adds mutation factors to enable the algorithm to have the ability to jump out of the local optimum, optimizes the aspect ratio and predicts the optimal tilt angle through the improved algorithm, takes the root mean square error of the true value and the predicted value of the tilt angle as the fitness function, and optimizes the algorithm to find the optimal correction angle.

The present invention relates to an improved sparrow search method based on penalty function constraint optimization. This method is an improved sparrow search method based on penalty function constraint optimization that integrates the sine-cosine algorithm and the light-sensing strategy of fireflies. By generating the initial population in combination with Cubic chaotic mapping in the initial population initialization stage, the accuracy and distribution of the initial population are improved; in the iterative process of updating the position of the followers, the sine-cosine algorithm is added to improve the position update strategy of the followers, making the search mechanism of the followers more flexible, expanding the global exploration range, increasing the population diversity, increasing the probability of finding the optimal solution, and accelerating the convergence speed; finally, the light-sensing idea of the firefly algorithm is used to refine and optimize the method, helping the method to jump out of local extrema, providing a better parental population for the next iteration, providing an optimization direction for the method, avoiding blind search, accelerating convergence, and thus improving the optimization quality of the method.

The invention discloses a primer, a kit and a method for identifying species of a sparrow. The primer comprises a primer SEQ ID NO.1 and a primer SEQ ID NO.2 of a targeted COI region, a primer SEQ ID NO.1 and a primer SEQ ID NO.2 of a targeted COI region, and a primer SEQ ID NO.2 of a targeted COI region, the primers of the target D-loop region are shown in SEQ ID NO.3 and SEQ ID NO.4. The invention also discloses a kit for detecting the target D The invention also provides a corresponding kit and a method for identifying the species of the sparrow by using the primer. According to the specific PCR primer for the sparrow, a specific gene sequence of a targeted species is adopted, and accurate detection of DNA of the sparrow can be stably realized in a complex environment medium. The method has the advantages of being easy and convenient to operate, high in sensitivity, rapid in detection and the like, is suitable for scenes such as species identification and environmental DNA monitoring, provides a reliable technical means for ecological research, species protection and dynamic monitoring of the ecological environment of the sparrow, and has wide application prospects and practical values.

1. Name of the product in this design: Ceramic Teapot (Pastel Black Ground Sparrow Stone Ladle Teapot). 2. Purpose of this design: For holding liquids. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The application provides a Hadoop parameter optimization method based on an improved sparrow search algorithm, and relates to the technical field of distributed computing. First, population parameters are set and the population is initialized, and the parameter value of each sparrow in the initialized population is taken as the value of the configuration parameter; a job is submitted to a Hadoop cluster, the execution time of the job is taken as the fitness of the sparrow, and each sparrow in the population is sorted according to the fitness value; the finder update formula is optimized, and the positions of the finder, the follower and the early warning person in the population are updated; the sparrow parameters in the iteratively updated population are taken as the configuration parameter values, the job is submitted to the Hadoop cluster again, the fitness of the sparrow in the population is obtained, and each sparrow in the population is sorted according to the fitness value; if the iteration termination condition is reached, the position vector of the sparrow with the optimal fitness in the current population is output as the optimal solution of the configuration parameter; if the iteration termination condition is not reached, the iteration is continued.

The invention discloses a fault feature extraction method of a flexible hand for a deep-sea submersible vehicle, belongs to the technical field of flexible hands for submersible vehicles, and aims to enlarge a search range and fuse a novel lens imaging inverse learning strategy in population initialization. In order to enhance the local search ability of the sparrow-jellyfish hybrid algorithm, a mutation mechanism is introduced in the local development stage of the jellyfish population. According to the hybrid algorithm, the search range is effectively expanded, the search capability is improved, and the problem of local optimum is avoided, so that the optimal combination of the penalty factor # imgabs0 # and the decomposition quantity # imgabs1 # is efficiently found. According to the hybrid algorithm, the accuracy of fault feature extraction is effectively improved, and the reliability of fault diagnosis is improved.

The application provides a farm load prediction method, device and equipment based on multi-source data, and relates to the field of power load prediction.The method comprises the following steps: obtaining historical load data, breeding animal growth data, environmental data and equipment data of a farm; decomposing the historical load data according to a variational mode decomposition algorithm to obtain a plurality of load components; wherein the variational mode decomposition algorithm optimizes parameters through a sparrow search algorithm, and the sparrow search algorithm establishes a fitness function about the load components according to the breeding animal growth data; after the plurality of load components, the breeding animal growth data, the environmental data and the equipment data are spliced, the spliced data is input into a preset Transformer model to obtain a power load prediction curve of the farm.The application can improve the accuracy and availability of the power load prediction result of the farm.

The utility model belongs to the technical field of machine manufacturing, and particularly relates to a chicken foot cutting table convenient to clean, which comprises a base, a cleaning mechanism is arranged at the top of the base, and a filtering mechanism is arranged on one side of the cleaning mechanism. The water pump in the cleaning mechanism can convey water to the hollow plate through the hose and the connecting pipe, and then the brush plate cleans the cutting table top on the net frame. By means of the design, automatic water spraying cleaning is achieved, compared with a traditional manual cleaning mode, manpower can be saved, the cleaning efficiency can be improved, and particularly under the conditions that the chicken foot processing amount is large and the cutting table needs to be cleaned frequently, impurities left on the table top in the cutting process can be rapidly and effectively removed.

1. Name of the product in this design: Pendant (Sparrow Screen Spreading Joy). 2. Purpose of this design: for wearing and decoration. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1. 5. The top view is shown in other views, so the top view is omitted; the bottom surface of this design product is a part that is not easily seen or cannot be seen during use, so the bottom view is omitted.

The application relates to a sewage treatment process optimization control method based on a multi-objective sparrow algorithm, which comprises the following steps: adopting a least square support vector machine to establish a soft measurement model of total energy consumption and effluent water quality, and taking the soft measurement model as an optimization objective function; improving the sparrow algorithm from five aspects of population initialization, finder position updating, alarm position updating, optimal position disturbance strategy and external archive updating mechanism to obtain a multi-objective sparrow algorithm; optimizing the optimization objective function by using the improved multi-objective sparrow algorithm, obtaining a Pareto solution set, and optimizing the set values of dissolved oxygen concentration and nitrate nitrogen concentration; the scheme is improved according to the sparrow algorithm, and is applied to the sewage treatment process to optimize the set values of dissolved oxygen concentration and nitrate nitrogen concentration, so that the effluent water quality is improved and the energy consumption is reduced.

The invention provides a maximum power point determination method and device based on an improved sparrow search algorithm. The method comprises the following steps: acquiring operation data of a photovoltaic power generation system; based on Logistic chaotic mapping and operation data, determining positions of elite individuals in the sparrow population and fitness corresponding to the positions; executing the following iterative operations, and outputting the target fitness corresponding to the current optimal individual when the number of iterations reaches the set number of iterations; determining the maximum power point of the photovoltaic power generation system according to the target fitness; the iterative operation comprises the steps of updating positions of a plurality of common individuals except elite individuals in the sparrow population based on a cosine convergence factor, and determining fitness corresponding to the plurality of common individuals according to the updated positions; determining a target elite individual in the plurality of common individuals; the elite individual with the smaller fitness and the target elite individual are determined as the current optimal individual; and determining the sparrow population of the next iteration. Therefore, the determination precision of the maximum power point is improved.

1. Name of the product in this design: Comb (Sparrow's Song in the Clouds). 2. Purpose of this design: A comb for combing hair. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The utility model discloses a container type generator set, which relates to the technical field of container type generator sets, and comprises a base, the upper surface of the base is fixedly connected with a shell, and both sides of the front surface of the shell are provided with communicating grooves. According to the container type generator set, the short circuit sensor sends the short circuit information to the controller through the line, and then the controller sends the short circuit information to the remote PC port, so that workers can conveniently inform maintenance personnel of the short circuit information; therefore, maintenance personnel can timely maintain the generator which breaks down, insects such as bees and birds such as sparrows can be effectively prevented from entering the shell from the vent groove, and the purpose of preventing the insects and birds from entering the shell is achieved. Therefore, the problem that in the using process of a traditional container type generator set, due to the fact that a corresponding partition structure is not arranged, insects, birds and other animals enter the shell, and electronic devices in the shell are damaged is solved.

The application discloses a short-term load combined prediction method based on adaptive chirp mode decomposition and SSA-BiLSTM, which comprises the following steps: S1, setting the sparrow population number of SSA, the proportion of sparrows with different task division and the maximum iteration number; S2, initializing the to-be-optimized parameters in the solution space; S3, training the sample by constructing a BiLSTM model corresponding to the parameter value, and calculating the fitness value; S4, updating the sparrow population position according to the fitness value output by the BiLSTM, obtaining a new solution, and transmitting the corresponding solution, i.e., the parameter value, to the BiLSTM for training; S5, repeating the step S2 and the step S3 until the maximum iteration number is reached and the iteration is completed; and S6, outputting the optimal parameter value combination and establishing an optimal BiLSTM prediction model. The short-term load prediction precision is effectively improved by solving the technical problems, such as slow convergence, complicated parameter adjustment, poor stability and low prediction precision, of the load prediction method in the prior art.

1. Name of the product in this design: Brooch (Auspicious Sparrow Embracing the Heart). 2. Intended use of this design: for wearing, decoration, etc. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The present invention discloses a PID control method, system, equipment and storage medium for a bridge crane, comprising obtaining a parameter vector of a bridge crane PID controller, calculating a fitness function value according to the parameter vector, dividing sparrows in an optimization model into finders and joiners that snatch food from the finder according to the fitness function value, updating the finder position according to a finder position update formula, introducing normal variation into the joiner position update formula to update the finder position, updating the joiner position update result using an orthogonal opposition learning strategy, randomly selecting some sparrow individuals to calculate according to a detection formula, and obtaining optimal PID control parameters according to the optimal value sparrow position, thereby realizing intelligent operation of a large-scale operating machine bridge crane, overcoming the problems of large swing angle amplitude and slow positioning response of the bridge crane during operation, and improving work efficiency and safety performance.

1. Name of the product in this design: Hair clip (small bird beak pointed big tail clip). 2. Purpose of this design: For decorating and styling hair. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention is suitable for the technical field of wind power generation, and provides a sparrow optimization algorithm-based wind turbine arrangement optimization method, which comprises the following steps of: respectively determining initial position matrixes of wind turbines in a flush arrangement mode and a staggered arrangement mode in a wind power plant area; optimizing the arrangement position of each wind turbine in the wind power plant area by using a sparrow optimization algorithm to obtain the optimal arrangement position of each wind turbine in the wind power plant area; an updating formula of a discoverer in the sparrow optimization algorithm is determined based on a dynamic weight strategy, the fitness of individuals in the sparrow optimization algorithm is obtained through calculation based on a wind turbine wake flow model, and individuals of an initial population of the sparrow optimization algorithm are obtained based on an initial position matrix and a heuristic initialization mode. Each individual of the initial population comprises coordinate values and yaw angles of all wind turbines in the wind power plant area in a preset coordinate system. The optimization efficiency of the arrangement position of the wind turbine can be improved.

The invention discloses a resource prediction method, device and equipment and a readable storage medium in the technical field of information processing, and the method comprises the steps: obtaining resource load data of a cloud computing platform, and creating a sparrow population matched with hyper-parameters in a long-short-term memory network model through the resource load data; optimizing the initial positions of sparrows in the sparrow population to obtain a target sparrow population; performing iterative search on the target sparrow population to determine an optimal hyper-parameter; and obtaining target resource load data of the cloud computing platform, and inputting the target resource load data into the long-short-term memory network model with the optimal hyper-parameter for resource use prediction to obtain a resource demand prediction result. By means of the long-short-term memory network model with better hyper-parameters, prediction analysis is carried out based on the resource load data, so that the accuracy of resource demand prediction is improved.

A bearing fault detection method based on an improved sparrow search algorithm is proposed. In the population initialization stage, an improved Chebyshev chaotic map is introduced to increase the diversity of the population and improve the ergodicity of individual sparrows, so that the population can be distributed as evenly as possible in the search space, achieving better population initialization effect. An inertia weight is added to improve the update position of the discoverer to reduce the probability of falling into the local optimum too early. An adaptive selective mutation strategy is proposed to enable the sparrows to escape from the local optimum, avoiding the problem of falling into the local optimal solution that is prone to occur in existing technologies.

The invention provides a direct-driven fan parameter identification method based on an improved sparrow algorithm, and relates to the technical field of wind power generation control, and the method comprises the steps: S1, determining a to-be-identified control parameter in a low-voltage ride-through control strategy according to an active power model and a reactive power model of a direct-driven fan; s2, identifying the to-be-identified control parameters of the direct-driven fan by adopting a sparrow algorithm; wherein in the step S2, the sparrow algorithm is improved by optimizing the search step sizes of the discoverer and the subscriber, the search step size of the predator and the initial position of the population and introducing a dynamic migration strategy. According to the scheme, the defects of optimization capacity and convergence speed can be improved, and the parameter identification efficiency is improved.

The present invention discloses an optimization method for an intelligent prediction model of electric load, comprising: establishing an intelligent prediction model, setting required optimization parameters and the optimization range of each parameter; initializing the parameters and population of a global sparrow optimization algorithm; iteratively updating the sparrow positions to obtain the optimal parameters; and applying the obtained optimal parameters to the intelligent prediction model for load prediction. The present invention initializes the population using a tent chaotic sequence, which can make the population more evenly distributed in the solution space and increase the global search capability of the population in the early stage; the present invention adds a step-size control factor, which gives the population a larger search range in the early stage of iteration, enhancing the global search capability in the early stage. As the number of iterations increases, the step-size control factor decreases, allowing for better local search and improving the convergence speed; the present invention improves the prediction capability of the model by optimizing the parameters of the intelligent prediction model.

The embodiment of the invention discloses a sparrow TaqMan real-time fluorescent quantitative PCR (Polymerase Chain Reaction) probe primer combination, a kit and application. Comprising a probe, an upstream primer and a downstream primer, the nucleotide sequence of the probe is 5 '-FAMTGAGCTGTAACTACTAC-MGB-3', the nucleotide sequence of the upstream primer is 5 '-CTTCCTAGGAGATGACCAAGTTTAC-3', and the nucleotide sequence of the downstream primer is 5 '-CAGTTTCCGAATCCTCCGATC-3'. The probe and the primer based on TaqMan real-time fluorescent quantitative PCR provided by the invention have the advantages of strong specificity, high sensitivity, good accuracy and simplicity and convenience in operation in the aspect of identifying sparrow species, meanwhile, the detection time is shortened, the detection cost is reduced, and a powerful technical support is provided for deeply exploring the fields of genetics, ecology and the like of sparrows.