2217results about How to "Improve portability" patented technology

The invention relates to the field of cloud computing and distributed computing, and discloses a cloud data processing system based on an artificial intelligence algorithm, which comprises a data input module, a task decomposition module, a resource scheduling module, a parallel computing module and a result reconstruction module, the data input module receives high-dimensional data and converts the high-dimensional data into a tensor structure; the task decomposition module decomposes the tensor, generates a core tensor and an orthogonal matrix, and generates a plurality of sub-tasks; the resource scheduling module is used for carrying out resource allocation and scheduling on the sub-tasks, and task execution time and resource consumption are minimized; the parallel computing module distributes subtasks to the computing nodes for execution, and the task execution sequence is guaranteed; and the result reconstruction module combines and verifies the execution results of the subtasks to generate a final calculation result. The cloud data processing efficiency and the resource utilization rate are effectively improved, the accuracy and consistency of calculation results are ensured, and the method is suitable for the fields of artificial intelligence training, large-scale data analysis, scientific calculation and the like.

The invention discloses a blind person auxiliary interaction method and system based on a multi-modal large model and a storage medium, and belongs to the technical field of artificial intelligence, and the method comprises the steps: obtaining a user voice instruction and an external environment image, and carrying out the preprocessing of the obtained data; inputting the preprocessed data into a pre-trained multi-modal large model to obtain an environment understanding result; integrating the environment understanding result into feedback information for voice output, and adjusting output intonations according to environment characteristics; the acquisition method of the pre-trained multi-modal large model comprises the following steps: acquiring historical multi-modal data; and inputting the historical multi-modal data into a pre-constructed multi-modal large model, carrying out fine tuning on the trained multi-modal large model through a base layer in a frozen model to obtain a trained multi-modal large model, fusing multi-modal information through the multi-modal large model, accurately identifying a user intention and a corresponding object in a complex environment, and carrying out real-time identification on the user intention and the corresponding object in the complex environment. Therefore, accurate scene description is fed back.

The invention belongs to the technical field of data generation, and discloses a virtual character training data generation method and system, and the method comprises the steps: analyzing a virtual character, and constructing the attribute, expression mode and application scene of the virtual character; based on the attribute, the expression mode and the application scene of the virtual character, training the large language model, and evaluating the generation effect after training; dynamically adjusting the proportion of the expression modes in the labeling data set according to the evaluation result, and updating the large language model based on the adjusted proportion; and according to the attribute, the expression mode and the target application scene of the target virtual character, generating corresponding dialogue content data by using the updated large language model, and obtaining virtual character training data. The method not only supports complex virtual character setting, but also has the advantages of high mobility and efficient preparation of multi-virtual character data.

The invention relates to the technical field of medium and small span bridge construction and control, in particular to a precast beam size matching method and system based on a three-dimensional laser scanner, and the method comprises the steps: obtaining precast beam point cloud data, carrying out the preprocessing of the precast beam point cloud data, carrying out the registration of the preprocessed precast beam point cloud data with a BIM model, and obtaining the size of a precast beam. The automatic detection of the structure size is realized; then, by obtaining interface angular points of the precast beams, conducting virtual splicing by aligning the cross section angular points of the adjacent precast beams, simulating the field splicing process and obtaining key construction details, accurate and reliable data support is provided for follow-up construction, it is ensured that each beam section can conform to design specifications during splicing, and therefore potential safety hazards are reduced; the controllability and scientificity of the construction process are improved, the construction efficiency is improved, the construction period is shortened, the service life of the bridge structure is prolonged, and the structural reliability is improved. The problems of low precast beam parameter detection efficiency, high operation difficulty and low accuracy in the prior art are solved.

The invention relates to the technical field of computers, in particular to a model confidence evaluation method and device, equipment, a medium and a program product, and the method comprises the steps: obtaining an information evaluation set; inputting test questions in the information evaluation set into the first model and the second model respectively to obtain to-be-evaluated answers output by the first model and reference answers output by the second model; inputting the reference answers and standard answers of the test questions in the information evaluation set into a pre-trained evaluation model, and outputting first deviation information between the reference answers and the standard answers; when determining that the test question and the standard answer meet a preset confidence condition based on the first deviation information, inputting the to-be-evaluated answer and the standard answer into an evaluation model, and outputting second deviation information between the to-be-evaluated answer and the standard answer; generating a confidence evaluation report of the first model according to the second deviation information; according to the scheme, the confidence test of the test questions and the standard answers is realized, and the universality and the mobility of the evaluation method are improved through the arrangement of the evaluation model.

The invention relates to a lower limb diagnosis training system, and belongs to the field of medical diagnosis and rehabilitation training. The system comprises a detection part used for collecting data information related to the lower limbs of a patient; and the control unit is used for analyzing and processing the data information so as to calculate and obtain a diagnosis result. The control unit can calculate a neural function index based on the electroneurographic signal parameters, calculate a joint activity index based on the joint activity, calculate a muscle strength index based on the muscle strength evaluation value, and further calculate an initial lower limb function comprehensive score; the initial lower limb function comprehensive score is used as an initial diagnosis result to output a control signal of a numerical range of a combination of traction forces in multiple directions, so that electromyographic signal parameters and blood flow parameters acquired by a detection part in real time in the training process of a patient can be used by a control unit for correcting the initial lower limb function comprehensive score; and obtaining a dynamic lower limb function comprehensive score for adjusting the specific numerical value of each traction force distribution.

The invention provides a motor stator vibration suppression method and system based on an electromagnetic pad and deep learning, and relates to the field of electrical technology, and the method comprises the steps: collecting a vibration signal of a motor stator, and carrying out the preprocessing of the vibration signal; inputting the preprocessed signal into a deep learning model, and training and optimizing the deep learning model; fusing the features through a full connection layer to obtain a comprehensive feature vector; predicting the future vibration state of the motor stator by using the comprehensive feature vector; establishing an electromagnetic force model, and designing an adaptive control law based on the predicted future vibration state and the electromagnetic force model; electromagnetic force required by vibration suppression is calculated by using a self-adaptive control law and is converted into a control signal to adjust the electromagnetic pad; a multi-objective optimization algorithm is used to consider the vibration suppression effect and energy consumption at the same time, an adaptive control law is adjusted, and closed-loop feedback control is formed to continuously optimize the vibration suppression effect.

The invention discloses stable clamping and rotating equipment for a motor rotor shaft, and belongs to the field of motor rotor shaft clamping. A stable clamping and rotating device for a motor rotor shaft comprises a base and further comprises a vertical rod fixedly connected to the base. The hollow shaft is rotationally connected to the fixing ring, and a sliding plate is slidably connected into the hollow shaft; the arc-shaped clamping rod is fixedly connected to the sliding plate, and a first arc-shaped clamping plate is connected to the arc-shaped clamping rod in a sliding mode; the annular plate is slidably connected to the hollow shaft, a push rod is slidably connected to the annular plate, and the end, away from the annular plate, of the push rod is fixedly connected with a second arc-shaped clamping plate; a supporting rod is slidably connected to the fixing block, and an arc-shaped supporting plate is arranged at the end, away from the fixing block, of the supporting rod. The clamping rotating seat is used for clamping the bottom end of the motor rotor shaft; multi-point clamping is carried out through the first arc-shaped clamping plate and the second arc-shaped clamping plate, the clamping effect is better and more stable, the machining size and shape can be guaranteed during follow-up machining, and follow-up use is facilitated.

The utility model discloses portable equipment for measuring the carbon emission rate of a fixed source. The portable equipment comprises a box body, a signal processing module, a first flue gas parameter measuring module and a second flue gas parameter measuring module, the first flue gas parameter measurement module comprises a pitot tube, a static pressure tube, a differential pressure sensor and a static pressure sensor, the differential pressure sensor is connected with the pitot tube, and the static pressure sensor is connected with the static pressure tube; the second flue gas parameter measurement module comprises a sampling pipe, a temperature sensor, a humidity sensor and a carbon dioxide concentration sensor, the temperature sensor is arranged in the sampling pipe and close to the sampling port, the humidity sensor is arranged in the sampling pipe, and the carbon dioxide concentration sensor is arranged in the sampling pipe and located at the end, without the sampling port, of the sampling pipe; a main discharge pipe is arranged in the box body, the main discharge pipe penetrates out of the box body, and one end, positioned in the box body, of the sampling pipe is connected with the main discharge pipe. According to the utility model, only one sampling hole is needed, the difficulty of insufficient sampling holes of the flue of the power plant is solved, the application scene of the detection device is expanded, and the environmental adaptability is improved.

The invention discloses a grassland nitrogen content inversion method and system, and relates to the technical field of grassland vegetation quantitative remote sensing. The method comprises the following steps: acquiring measured grassland hyperspectral data and environmental parameter data of a target area, and preprocessing the measured grassland hyperspectral data; according to the preprocessed grassland actually measured hyperspectral data, extracting mapping relation characteristics of hyperspectrum-leaf area indexes in vegetation; extracting a leaf area index-nitrogen content according to the environmental parameter data; and by taking the leaf area index as connection, coupling the extracted leaf area index-nitrogen content with the hyperspectrum-leaf area index, and carrying out inversion on the nitrogen content of the grassland. Through the method provided by the invention, the dynamic change of the nitrogen in the plant growth process can be better captured, and the method has higher stability and transportability so as to quickly and effectively invert the nitrogen content of the grassland, so that the nitrogen of the plant is stably and accurately extracted, and the generalization ability of the nitrogen extraction method is improved.

The embodiment of the invention relates to the technical field of fans, and particularly discloses an active noise reduction fan which comprises a shell which is a portable shell, a cavity is formed in the shell, and an air inlet and an air outlet which are communicated with each other are formed in the two ends of the shell respectively; the fan assembly is arranged in the cavity and used for rotating to generate wind pressure so that air can be sucked in from the air inlet, passes through the cavity and then is blown out from the air outlet; the noise reduction assembly is arranged in the cavity and used for collecting noise signals inside and outside the cavity in real time when the fan assembly operates and sending out noise reduction signals according to the noise signals; wherein the noise reduction signal is a dynamic comprehensive noise signal including air inlet noise, air outlet noise, fan blade noise and / or motor noise. Through reasonable design of functions of the noise reduction assembly, active noise control is performed on the noise signal by using the noise reduction signal, and the noise level during operation of the fan is reduced.

The embodiment of the invention provides a human motion capture system and method, the system comprises a virtual reality device and at least one inertial sensing module, and the inertial sensing module is in communication connection with the virtual reality device; wherein the inertial sensing module is used for acquiring first posture information of each key node, except the head, of a human body and sending the first posture information to the virtual reality equipment; and the virtual reality equipment is used for acquiring second posture information of the head of the human body, and determining a human body motion capture result according to the first posture information and the second posture information in combination with a pre-constructed posture prediction model. According to the system, the virtual reality equipment is used for replacing head inertia equipment and an external calculation module, so that the portability of the whole set of equipment is improved; and meanwhile, the six-degree-of-freedom function of the virtual reality equipment is used as reference data of the inertial sensing module, so that the precision of the inertial motion capture system is improved, and the problems that the original inertial motion capture precision is insufficient and inertial motion capture data drifts are solved.

The invention discloses a disk sweeping posture self-adaptive adjusting system and method based on a visual system and a storage medium. The disk sweeping posture self-adaptive adjusting method comprises the steps that S1, disk sweeping posture information is obtained; s2, the visual processing unit collects disk scanning attitude information and road surface information in real time by using a visual sensor arranged on the visual processing unit, and provides real-time disk scanning attitude data for the control system; s3, the control system receives the current disk scanning attitude data, calculates the deviation between the current disk scanning attitude data and the preset optimal disk scanning attitude data according to an intelligent algorithm, and issues a deviation correction instruction; s4, the multi-degree-of-freedom disk sweeping posture adjusting device adjusts the disk sweeping posture according to the deviation rectifying instruction; and S5, the control system judges whether the disk sweeping brush reaches the optimal posture according to the received disk sweeping posture real-time information, if not, the deviation is continuously calculated, a deviation correction instruction is issued, and if yes, deviation correction adjustment is ended. The sweeping postures of the sweeping disc are adjusted according to the road surface state and the sweeping abrasion degree, and the sweeping effect is improved.

The invention relates to an embedded operating system platform related code generation method based on an AADL model, and belongs to the field of automatic code generation. According to the method, the AADL model is traversed, acquired and analyzed through a writing algorithm, a mapping rule from the AADL model to an embedded operating system code is designed, and components, interfaces, performance attributes and connection information between the components in the model are automatically converted into the embedded operating system platform code. According to the method, the codes can be automatically generated, the complexity and uncertainty of manual writing are reduced, the reliability and platform adaptability of the codes can be improved, and a powerful tool is provided for development of an embedded system in the aerospace field.

The invention discloses a differential pressure time series data prediction method and device based on an improved ARIMA model, and the method comprises the steps: collecting and packaging voltage data of a single battery of energy storage equipment, obtaining time series data, carrying out the cleaning processing, and obtaining the cleaned time series data; carrying out ADF stability verification on the cleaned time sequence data; after the time sequence data passes the cleaning, carrying out Ljung-Box white noise detection on the cleaned time sequence data; generating prediction data after checking; constructing an ARIMA model and determining parameters; training the ARIMA model by setting a training data set; performing performance evaluation on the trained ARIMA model by setting a verification data set to generate an evaluation index; when the evaluation index reaches a set standard, training is completed, and a trained ARIMA model is obtained; and inputting the prediction data into the trained ARIMA model for prediction processing to obtain differential pressure prediction data. The accuracy of predicting the voltage difference of the single battery is improved, the voltage abnormity can be monitored, and then the stability of energy storage equipment is maintained.

The invention provides an aero-engine vibration phase testing device. The aero-engine vibration phase testing device comprises an optical fiber sensor, a photoelectric converter, a triaxial accelerometer, a vibration analyzer and a test computer. The vibration analyzer is responsible for collecting signals and performing related processing on the signals through a built-in data processing module; and the test computer is connected with the vibration analyzer through the Ethernet to realize data real-time transmission and program end data processing, and is accessed to a test run data monitoring interface. The invention discloses an aero-engine vibration imbalance phase test method. The method comprises the following steps: marking key phase blades; preparation before installation of the optical fiber sensor; installing an optical fiber sensor; performing photoelectric conversion; a triaxial accelerometer is installed; picking up a rotor key phase positioning signal; solving a vibration imbalance phase under multiple rotating speeds; and carrying out counter weight adding test run verification. The method has the advantage that the unbalanced phase is efficiently and accurately obtained. The reliability and accuracy of vibration phase test data are improved, and the follow-up engine balancing quality is further improved.

The invention relates to the technical field of welding devices, and discloses an anti-explosion valve rod welding device which comprises a welding table, a frame is fixedly connected to the top of the welding table, a fixing device is arranged at the top of the frame, a discharging device is arranged at the top of the welding table, and a slag removing device is arranged at the bottom of the welding table. When the explosion-proof valve rod starts to be welded, the explosion-proof valve rod is placed in a welding area, so that the surface of the explosion-proof valve rod can be fixed through an inner arc of an arc-shaped plate I under the condition that the circumferential surface of the explosion-proof valve rod needs to be welded, and the explosion-proof valve rod is fixed more stably during welding; according to the anti-explosion valve rod clamping device, the anti-explosion valve rod can be clamped more stably, the situation that the anti-explosion valve rod is damaged due to the fact that the force of the air cylinder is too large can be avoided through buffering provided by the first spring in the fixing process, meanwhile, the anti-explosion valve rod can be clamped more stably, and then the stability of the anti-explosion valve rod in the welding process can be further improved.

The invention relates to an innovative bearing heat treatment result prediction technology, and the powerful capability of a deep learning network is fully utilized. The method is characterized in that key parameters, such as quenching time, quenching temperature and other conditions possibly influencing a heat treatment result, of the bearing in the heat treatment process are integrated to serve as a feature set of input data, and the physical or chemical attribute value of the bearing after heat treatment is completed serves as a target variable of model prediction. According to the characteristic that data is high in time sensitivity, a long short-term memory (LSTM) network is selected to learn a complex mapping relation between input features and output results, time sequence dependency in the data is effectively captured, and time sequence features of the data are grasped. The trained model not only can provide an accurate prediction result for an operator, but also can help the operator to understand how different parameters affect the quality of a final product, so that product loss caused by experiments is reduced.

The invention discloses a control point parallel manual measurement method for image aerial triangulation. The method comprises the following steps: firstly, performing aerial triangulation on original image data with initial positioning parameters under the condition of no ground control, and optimizing geometric positioning parameters; secondly, dividing the complete measurement area into a plurality of subareas, predicting an image where a control point is located and an image point position of the image according to coordinates of the control point and image positioning parameters, cutting a local image block by taking the position as a center, and storing the local image block into a plurality of integrated image point data files according to the subareas; then, distributing the image point data file to a plurality of operators for parallelized control point measurement; and finally, the measured control point image coordinates are exported and recovered to an original measurement area project, and parallel measurement can be completed. According to the invention, the data portability is improved, the single-point measurement efficiency is improved, and parallel measurement is supported, so that the efficiency of large-data-volume control point measurement is improved to the maximum extent.

The present application discloses a portable desktop range hood, comprising a range hood main body and a base main body, wherein the range hood main body is arranged above the base main body and is inclined; a filter group, an oblique flow impeller, a motor, a protective cover and a protective net are sequentially installed on the range hood main body along the airflow direction, and the oblique flow impeller, the protective cover and the motor are installed in the guide cover; the filter group comprises an oil-repellent and hydrophobic net, a condensation net and a deodorizing net, an oil box limiter and an oil box are installed in the base main body, and an oil receiving column is arranged above the oil box limiter; the range hood main body comprises an outer shell, an oil collecting groove is opened at the lowest end of the inner circumference of the outer shell, the oil collecting groove is located directly below the filter group, an oil guide column is connected below the oil collecting groove, and the oil guide column is plugged into the oil receiving column; the oil-repellent and hydrophobic net is installed in a fixed frame, and the fixed frame is detachably installed on the inner circumference of the outer shell.

The invention relates to the technical field of agricultural machinery, in particular to a multifunctional fruit huller. Comprising a case, and an eccentric rolling and screening device, a spiral screening and conveying device, a drying device and a collecting device which are mounted in the case from top to bottom; the eccentric rolling and screening device is provided with an eccentric rolling roller and a screening barrel and is used for rolling and screening fruits, then the fruits are conveyed to the drying device through the spiral screening and conveying device, and the drying device is used for drying the seeds and conveying the seeds into the collecting device; the motor and the transmission device are installed in the machine box, and the motor drives the eccentric rolling and screening device and the spiral screening and conveying device to operate through the transmission device. The device can be conveniently carried to mountainous areas where fruit trees live, fruits can be hulled on site after being picked, transportation is convenient, and the hulled seeds can be dried.

The invention relates to a coprocessor based on an RISC-V architecture and a processing system thereof. The coprocessor comprises a decoding unit, a control unit, an arithmetic unit, a cross-clock transmission unit and a cache unit. The decoding unit receives the value of the source register sent by the main processor and decodes the value to output an operation parameter, the control unit controls the working process of the operation unit based on the operation parameter, and the cross-clock transmission unit communicates with the main processor and comprises transmission of configuration parameters and feedback signals. Therefore, the main coprocessor can run in different clock domains; the cache unit is used for caching part of weight data and all bias data required in single operation, can be used for realizing operation of an expansion instruction, does not occupy the storage space of the main processor, and greatly improves the operation efficiency of the neural network.

The invention discloses a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization method and a photovoltaic-energy storage-charging multi-stage scheduling and market bidding optimization device. The method comprises the following steps: constructing a data-driven random environment model reflecting photovoltaic output, electricity price fluctuation and charging load uncertainty by adopting a mode of combining time sequence clustering and a non-homogeneous Markov chain based on historical operation data; modeling a scheduling and bidding problem of the optical storage and charging integrated station into a multi-stage Markov decision process model which comprises day-ahead decision and joint optimization of multiple intra-day rolling adjustment; a deep reinforcement learning algorithm is utilized to train the network, and a strategy regulation and control network which can adapt to various uncertain scenes and meet equipment physical constraints is obtained; and deploying the trained strategy regulation and control network in an energy management system to realize global coordinated scheduling and bidding of the optical storage and charging integrated station. According to the method, the economic benefit is remarkably improved, the robustness is greatly enhanced, the decision is globally coordinated and optimized, the real-time decision capability is strong, and the expandability and portability are good.

The utility model relates to an eye hot compress treatment device which comprises a supporting frame, and the supporting frame is provided with an arc-shaped part matched with the outline of the head and ear hanging parts used for being hung on ears. The two eye hot compress pieces are arranged at the left end and the right end of the front side of the supporting frame respectively, and each eye hot compress piece comprises a heating film; the device further comprises a control host, and the heating film is electrically connected with the control host. The portable earphone is simple in overall structure, small and exquisite in size, light in weight, convenient to wear and high in adaptability, and compared with a traditional structure, the portable earphone greatly improves portability and experience of a user.

The invention discloses an intelligent fry specification, color and gender screening system based on morphological measurement feature recognition. The screening system comprises a fish fry sequencing batch module, a shunting and conveying module for processing fish fries fed by the fish fry sequencing batch module, and a fish fry characteristic specification judging module located above the shunting and conveying module. Wherein the fry feature specification judgment module obtains fry feature information according to the fry image to provide a shunting basis. The fish fry characteristic specification judging module comprises a shell, a high-definition camera and an illuminating lamp which are embedded in the shell and face the shunting slide way, and an image processing assembly arranged in the shell. A multi-angle screening system of the fish fry specification, the fish fry body color and the fish fry gender is designed, three key difficulties of specification screening, color screening and gender screening in the fish fry breeding process are overcome, the problems of feeding of large and small fishes, selection of ornamental fishes and male and female screening in the fry stage in the fry breeding process are effectively solved, the artificial breeding process is accelerated, and the breeding efficiency is improved. The production efficiency is improved.

The invention discloses a method, device and equipment for performing man-machine interaction with a desktop virtual image, a medium and a product. The method comprises the following steps: in response to a trigger request for a target client for realizing a desktop virtual image function, displaying a client interface with a full-transparent background of the target client in a set screen area of a computer desktop; loading a target Web page with the full-transparent background in the client interface with the full-transparent background; performing dynamic rendering display on the desktop virtual image in the full-transparent background target Web page; and performing man-machine interaction with a user through the desktop virtual image. According to the technical scheme provided by the embodiment of the invention, the desktop interaction effect of the virtual image can be realized only by using the drawing rendering function of the target Web page integrated in the target client without deep cooperation of codes of a computer operating system, so that the development difficulty of developers is effectively reduced, and the development efficiency is improved. And the development efficiency of the desktop virtual image function software is greatly improved.

The invention relates to the technical field of switch cabinet nuclear phase equipment, in particular to an adjustable switch cabinet nuclear phase auxiliary tool which comprises a scissor type telescopic frame, mounting plates are symmetrically mounted on the opposite side walls of the scissor type telescopic frame, and fixing assemblies are mounted on the outer walls of the mounting plates. Wherein the fixing assembly is more stable when the scissor type telescopic frame transversely moves; the distance of the device can be adjusted through the scissor type telescopic frame, and the operation safety is improved through the push-pull rod; by pushing the sliding shell to move, when the side wall of the inner cavity of the sliding shell is attached to the sliding rod, only the sliding shell needs to be rotated, then the sliding shell is unfolded, and then the sliding shell is magnetically adsorbed to the outer wall of the magnetic adsorption block to be fixed; the opening shells move on the outer walls of the positioning rods along the 45-degree inclination direction through the limiting sliding grooves, then the distance between the opening shells is adjusted, meanwhile, the distance between the opening top plates located at the end openings of the opening shells is correspondingly adjusted, and practicability is better.

The invention discloses a wheel folding and unfolding mechanism applied to a power-assisted tractor and a using method. The wheel folding and unfolding mechanism comprises a chassis shell. The upper bearing is connected with the chassis shell; the folding device is arranged on the chassis shell; and the wheels are connected with the folding device. An original welding mode is upgraded into a foldable mechanism, rapid folding and storage of the power-assisted tractor are achieved, the storage size of the whole tractor is reduced, and single-person operation is facilitated. When the motor extends, the gear and the rack act to tighten the tractor, when the motor retracts, the wheels are opened, and folding storage of the power-assisted tractor is automatically achieved. And linear motion of the electric cylinder is converted into rotation of folding storage through the gear and the rack, manual operation is not needed, and only one-key folding is needed. The folding storage mechanism has the advantages that the folding storage function of the upper half vehicle and the folding function of the wheels are achieved, the overall storage size is further reduced, carrying and mounting are convenient, and the practicability and portability of the mechanism are improved.

The present invention discloses a method for improving the load estimation of the output-into-river coefficient model in a large watershed. A nested sub-basin is set for the measured watershed, a Latin hypercube sampling method is used to initialize the population, and a genetic algorithm is used in combination with relevant data of the nested watershed to solve the optimized watershed pollution equation to calculate the land use output coefficient of different sub-basins; the surface runoff factor, soil water leaching factor, landscape interception factor and soil erosion factor of the corresponding watershed are coupled to calibrate the output coefficient of pollution sources in different spatial units. At the same time, the ratio of the product of the rainfall erosivity factor and the terrain influence factor to the product of the cost distance factor and the vegetation coverage factor is used to calibrate the river inlet coefficient of pollution sources in different spatial units; a large watershed non-point source pollution load estimation model is constructed based on the calibrated output coefficient and river inlet coefficient, and the pollutant output and river inlet under various land use types are calculated to improve the accuracy of the estimation of non-point source pollution in large-scale watersheds.

The invention discloses an immunodetection method based on holographic imaging mode conversion and deep learning, and belongs to the field of immunoassay detection. The deep learning holographic mode conversion system constructed based on the non-paired data set reduces the influence of diffraction interference on target quantification to the greatest extent, so that holographic super-resolution imaging is realized, and challenges in paired data set generation are overcome; besides, a functional glass slide is designed, and rapid and sensitive holographic imaging detection is realized in combination with a click reaction signal amplification strategy; the functionalized glass slide is combined with the portable holographic imaging equipment, so that the detection efficiency of the system is greatly improved while accurate signal amplification is carried out, the application scene is expanded, and antibiotic residues can be rapidly and sensitively detected. The invention opens up a new research direction for high-sensitivity on-site convenient detection of trace target objects in portable equipment and complex samples.