246results about How to "Ensure comprehensiveness" patented technology

The invention discloses a base station site selection method, an electronic device, a storage medium and a computer program product, and relates to the technical field of wireless communication, in the application, a target area is divided into candidate grid areas, so that the granularity of site selection is refined. Meanwhile, according to the corresponding grid fusion features of the candidate grid areas, the area site selection fitness of the grids is determined, the area site selection fitness is used as a basis for subsequently determining a target grid area, and finally, the position of a target base station is determined from the target grid area to complete site selection. It can be understood that compared with a related technical scheme for determining the position of the base station according to individual dimensions, the method can generate the site selection basis of the base station based on the fusion data (namely the fusion result of the grids in all aspects) of the grids, greatly enriches the reference basis of the site selection of the base station, guarantees the comprehensiveness of the site selection basis of the base station, and improves the site selection accuracy of the base station. Therefore, the optimal base station position can be selected as much as possible.

The invention provides an Internet of Vehicles vulnerability knowledge graph updating method based on a cloud platform, and the method comprises the steps: monitoring vulnerability updating information, carrying out the popularity analysis, screening out the information with high popularity based on a popularity threshold value, and extracting potential entities from the information; expanding the potential entity; and updating the knowledge graph based on the potential entities. According to the method, the dispersed vulnerability information is integrated in a manner of establishing the knowledge graph, so that the problem of information fragmentation is eliminated, network security managers can understand and utilize the vulnerability information more quickly and accurately, and the efficiency of coping with vulnerabilities is improved. On the basis, in order to ensure the real-time performance and accuracy of the Internet of Vehicles vulnerability information knowledge graph, a plurality of data sources are further monitored in real time through technologies such as machine learning and data mining, and potential entities needing to be updated are screened out for updating the knowledge graph in real time.

The invention discloses a turnover device for carton conveying, and relates to the field of carton material conveying, the turnover device comprises a conveying line frame body and a plurality of first conveying rollers which are rotationally assembled in the conveying line frame body and are linearly distributed at equal intervals, and the first conveying rollers are in transmission assembly through transmission chain wheels and transmission wheels; a plurality of first conveying rollers are arranged on the conveying line frame body, a partition space is formed between the first conveying rollers, and a turnover unit is installed in the partition space, so that the turnover unit on the conveying line frame body can achieve the turnover effect on a conveyed box body, and therefore a worker can conveniently conduct all-around appearance detection treatment on the outer surface of the box body; detection dead angles on the outer surface of the box body can be effectively avoided, the comprehensiveness of box body detection is ensured, the buffer unit can be started through the trigger unit in the operation process of the turnover unit, the buffer unit is used for limiting other box bodies, accumulation of a plurality of box bodies can be avoided, and the working load of the turnover unit is reduced.

The invention provides a question and answer interaction virtual case development method for nurse inquiry training, which comprises an original case history module for constructing a virtual case text development framework based on a functional health form, a nursing inquiry teaching status and clinical nursing evaluation, and establishing an original case history; the initial response text module is used for determining the development sequence and inquiry elements of each unit, and constructing an initial response text with the guidance of cultivating clinical thinking ability, nursing science professional attainment and humanistic attainment; and the final response text module is used for constructing a final response text through the subject term and the subject term combination rule based on the initial response text. According to the method, all units of the virtual case text development framework are covered, and content comprehensiveness is guaranteed; an initial response text system is designed for cultivating clinical thinking ability, nursing science professional accomplishment and humanistic accomplishment, and educational guidance is achieved; on the basis of establishing a subject term library and designing a subject term combination rule, a response text is perfected, so that the response accuracy of the virtual patient is ensured.

The invention provides a cracking-resistant environment-friendly plastic woven bag detection device, and relates to the technical field of environment-friendly plastic woven bag production monitoring. The cracking-resistant environment-friendly plastic woven bag detection device comprises a detection table, a set of first sliding grooves are formed in the top of the detection table, and a sliding seat is slidably connected into each first sliding groove. According to the cracking-resistant environment-friendly plastic woven bag detection device, stretching detection is conducted on a woven bag by controlling two connecting plates to be far away from each other, the pulling force on the woven bag is recorded through an arranged pulling force sensor, pressure bearing monitoring is conducted on the woven bag through downward sliding of a pressure plate in the first detection mechanism, and the detection accuracy of the woven bag is improved. The bottom of the friction plate makes contact with the bottom of the woven bag, the friction plate is driven to slide left and right in a reciprocating mode under the action of the driving mechanism, abrasion resistance detection is carried out on the woven bag, the woven bag is detected in multiple detection modes, possible defects are effectively detected, and detection comprehensiveness is guaranteed.

The utility model relates to the technical field of emulsifying devices, and discloses a collagen emulsifying device which comprises an emulsifying barrel, a barrel cover is mounted at the top of the emulsifying barrel, a stirring shaft is rotatably mounted on the barrel cover through a bearing embedded in the middle of the top of the barrel cover, and a stirring shaft is mounted on the stirring shaft. Stirring pieces are mounted at the bottom end and the outer wall surface of the stirring shaft, and an ultrasonic driving assembly is arranged at the top end of the stirring shaft. According to the collagen emulsifying device, the vibrating rod is in an ultrasonic vibration state, ultrasonic waves can generate violent vibration at the molecular level, the activity of emulsifier molecules can be improved, the emulsifier molecules can interact with grease molecules and water molecules more easily, the emulsifying effect is improved, meanwhile, the ultrasonic waves can generate tiny bubbles and cavities, and the emulsifying effect is improved. The tiny bubbles and cavities can increase the area of an emulsification interface, so that grease and water are easier to mix and emulsify, and the emulsification efficiency is improved.

According to the motor protector and the control method thereof, the motor fault knowledge base is constructed through the knowledge graph, and data reference is provided for prediction and optimization of the neural network model. And constructing multiple classes of neural networks to evaluate and predict different types of faults of the motor, multiplying probability values of the same fault class output by the classification neural networks by corresponding weight coefficients, adding the probability values to obtain fused fault class probability values, and selecting the fault class with the maximum probability value as a prediction result. And the advantages of various neural networks in processing different types of data are fully utilized. And comprehensiveness and accuracy of fault diagnosis and protection of the motor are ensured by integrating the accuracy of the knowledge graph database and the capability of the neural network for processing high-dimensional complex data. And a self-adaptive control strategy instruction is generated based on the fusion analysis diagnosis result, the operation of the motor is controlled, the effect after the control instruction is executed is monitored in real time, and the flexibility and effectiveness of the execution strategy are ensured.

The invention discloses an index construction method and system for multi-modal medical and health data, and relates to the technical field of medical and health, and the method comprises the steps: obtaining the multi-modal medical and health data containing at least one diagnosis and treatment activity of a single patient; performing semantic alignment in the multi-modal medical and health data of the single diagnosis and treatment activity, and after semantic alignment, based on medical domain knowledge, performing semantic association among different modalities of medical and health data of the multi-modal medical and health data of the single diagnosis and treatment activity to obtain a single diagnosis and treatment activity association map; based on medical field knowledge, setting a label for the single-time diagnosis and treatment activity association map, constructing a plurality of first-level indexes of the single-time diagnosis and treatment activity association map based on the label, and vectorizing the plurality of first-level indexes to obtain a plurality of first-level index vectors; a plurality of primary index vectors are stored in a vector label library, and a single diagnosis and treatment activity association map is stored in a map library, so that the constructed index can realize cross-modal data query.

The invention relates to the technical field of engineering detection, in particular to an unmanned aerial vehicle photovoltaic station geological settlement dangerous case rapid detection method and system. An unmanned aerial vehicle is used for periodically collecting and processing image data of a photovoltaic station area along an air route to obtain digital elevation models at different times; and comparing the digital elevation models at different times to analyze the settlement condition of the photovoltaic station area. By adopting the unmanned aerial vehicle photography technology, the whole-area monitoring of the photovoltaic station can be realized, the real situation of the ground feature and landform of the subsidence area can be clearly and intuitively reflected, the comprehensiveness of ground subsidence monitoring can be ensured, and the aerial photography efficiency, the modeling speed and the modeling precision are greatly improved; the problems that a traditional subsidence monitoring method is high in cost, low in efficiency and low in precision are solved.

The invention relates to the technical field of food additives, in particular to a food additive production heating device which comprises a supporting base. The processing box is arranged on the outer side of the supporting seat, a heating cavity is formed in the inner side of the processing box, and a heat preservation cavity surrounding the outer side of the heating cavity is further formed; the cyclic heating unit is connected with the supporting seat and is connected with the processing box; the automatic lifting unit is arranged between the processing box and the supporting seat and is connected with the cyclic heating unit; wherein the cyclic heating unit comprises an air blowing type stirring assembly, an air guide heating assembly, a synchronous air conveying assembly and a push-pull type supporting assembly, the cyclic heating unit is arranged and matched with the automatic lifting unit, additives on the inner side of the heating cavity can be longitudinally stirred in a reciprocating mode, stirring comprehensiveness is guaranteed, and the stirring efficiency is improved. And the additive can be heated from inside and outside at the same time, so that the additive is heated uniformly, the heating efficiency is ensured, and the production efficiency is improved.

The embodiment of the invention discloses a transformer fault diagnosis method and device, equipment and a storage medium. The method comprises the following steps: constructing a simulation model of a transformer; collecting simulation operation data of the simulation model under different working conditions; taking the simulation operation data as a training sample, training a preset prediction model according to the training sample, and obtaining a transformer fault prediction model; and acquiring actual operation parameters of the transformer, and inputting the actual operation parameters into the transformer fault prediction model to obtain a fault type corresponding to the actual operation parameters output by the transformer fault prediction model. The simulation operation data generated through the simulation model is used for training the transformer fault prediction model so as to ensure the comprehensiveness of the training data; secondly, the actual operation data are input into the transformer fault prediction model for prediction, potential fault signs and fault possibility of the transformer can be identified, and maintenance and protection measures can be taken in advance, so that the fault time and the downtime of the transformer are reduced.

The invention provides an embankment anti-seepage treatment method based on water conservancy construction, and relates to the field of water conservancy projects, and the method comprises the following steps: A, excavating at an embankment position needing to be implemented according to a construction drawing to form an embankment foundation, constructing on the embankment foundation to form anti-seepage geotechnical cloth, and compacting the anti-seepage geotechnical cloth; b, an anti-seepage panel is constructed on the anti-seepage geotechnical cloth, and the anti-seepage panel is compacted; c, paving a cushion layer and a transition layer on the anti-seepage panel according to construction requirements; d, burying different intelligent sensors at different parts of the constructed dike, and constructing a real-time monitoring network; and E, transmitting the data acquired by the sensor to a remote monitoring platform through the Internet of Things technology, and analyzing and processing the data. A traditional water conservancy construction dike anti-seepage method is improved, a physical anti-seepage structure and an intelligent monitoring technology are combined, leakage problem early warning can be timely and accurately carried out, effective repairing measures are rapidly taken after early warning, and the dike anti-seepage treatment performance is greatly improved.

The utility model relates to the technical field of desulfurization, and discloses a multi-tube type high-efficiency desulfurization device, which comprises a bottom bin, a desulfurization part and a discharge bin, the desulfurization part is formed by vertically stacking and fixing a plurality of desulfurization components together, the lowest desulfurization component is fixed at an opening at the top of the bottom bin, and the discharge bin is fixed at the bottom of the bottom bin. And the discharge bin is fixedly mounted at an opening in the top of the uppermost desulfurization assembly. According to the multi-pipe type efficient desulfurization device, as the mounting shaft is in a reciprocating forward and reverse state, the spraying pipe can be driven to rotate clockwise and then rotate anticlockwise to reset, so that the atomizing nozzle is in a small-angle swinging state, and spraying corners and dead angles existing when the atomizing nozzle is in a fixed state can be supplemented in the moving process of the atomizing nozzle; the atomizing nozzle is free of corners and dead corners during spraying, sufficient and uniform contact between flue gas and lime emulsion is guaranteed, and the desulfurization effect on the flue gas is improved.

The invention relates to a device and method for collecting root exudates in the initial stage of plant growth, and belongs to the technical field of collection of root exudates, the device comprises a square vessel, a central incubator and a seed container which are in lap joint together, and a liquid injection pipe is further integrally formed on the side wall of the central incubator. In the operation process, different appropriate culture modes can be adopted for different growth stages of the plant from the seed germination stage, influences of various interference factors such as culture conditions and operation methods in the root exudate collection process are avoided, and meanwhile the function of observing the growth state of the plant root system is achieved. Plant root exudates at different parts in different stages can be collected, and comprehensiveness, accuracy and matching of collection of the root exudates in the initial growth stage of plants are guaranteed. And meanwhile, the device is designed into a simple detachable structure and has the characteristics of high operability and convenience in disassembly and maintenance.

The utility model relates to the technical field of agriculture, in particular to an auxiliary pollination device in an agricultural greenhouse, which comprises a slide rail, an adaptive electric slider sleeved on the outer wall of the slide rail, a first adjusting plate fixedly connected to the bottom of the electric slider, a second adjusting plate connected to one side wall of the first adjusting plate, and a movable plate connected to one side wall of the second adjusting plate. The lower side of the outer wall of the movable plate is fixedly connected with a carrying plate, and the bottom of the carrying plate is connected with a fan. The first adjusting plate can drive the second adjusting plate to descend, meanwhile, the second adjusting plate can drive the movable plate to descend again, so that the fan can descend to crops, wind power can be accurately blown to the crops through the fan, the first servo motor is used for driving the fan to rotate and reverse, and the fan can be driven by the first servo motor to rotate and reverse. Meanwhile, the electric sliding block slides along the sliding rail, so that the fan can be driven to perform transposition air blowing, and the comprehensiveness of air blowing supplementary pollination on the plants in the greenhouse is guaranteed.

The invention discloses an accurate rejecting device for a bag making machine, which comprises a control element, a detection assembly arranged above a feeding device, a buffer rack arranged between a turnover material turning device and an edge sealing device, a plurality of conveying rollers arranged on the buffer rack along a material conveying path, and a buffer rack rotatably mounted on the buffer rack, a stroke feedback element used for detecting the overturning stroke of the buffer frame is installed on a rotating shaft of the buffer rack, and the stroke feedback element, the detection assembly and the control element are in signal connection. The detection assembly is arranged on the feeding section, the rotation angle of the buffer frame is detected in real time, the self-adaptive rotation angle of the buffer frame in the material conveying process is obtained, and compensation calculation can be conducted on the length of materials conveyed between the detection assembly and the removing device according to the rotation angle of the buffer frame; according to the material detection device, the position detected by the detection assembly is ensured to be consistent with the cutting position of the removing device, the comprehensiveness of material detection is ensured, meanwhile, errors caused by conveying are reduced, waste caused in the removing process is reduced, and the cost is saved.

The invention discloses an analog circuit fault detection method and device based on CNN-LSTM, readable storage equipment and a program product, and relates to the technical field of deep learning for circuit fault diagnosis. The problems that an existing fault diagnosis method based on deep learning is difficult to effectively deal with complex characteristics of high-dimensional data and cannot fully capture key characteristic information related to faults, so that the diagnosis effect is poor, and the comprehensiveness and reliability of diagnosis results are poor are solved. By constructing the CNN-LSTM fault detection model, spatial features and time sequence features in circuit fault signals can be processed at the same time, and accurate detection and classification of faults can be realized without depending on an accurate mathematical model. The method is mainly used for fault diagnosis of the analog circuit.

The invention provides a green channel traffic management method and device based on big data, equipment and a storage medium, and belongs to the technical field of data processing, and the method comprises the steps: determining a green channel suspiciousness degree based on the transportation behavior of a target vehicle; determining a target inspection standard based on the green channel suspiciousness; and sending the target inspection standard to the target inspection equipment, obtaining a green channel inspection result based on the target inspection equipment, and determining whether the green channel inspection result meets a green channel condition based on the green channel inspection result. According to the big data-based green channel traffic management method and device, the equipment and the storage medium provided by the invention, the accuracy and reliability of green channel traffic management can be improved.

The invention discloses a data processing method, device and equipment and a computer readable storage medium. The method is applied to a first participant, and comprises the following steps: acquiring a joint identifier set which is a union set of a first identifier set and a second identifier set; encrypting the first transaction data corresponding to each joint object identifier in the joint identifier set to obtain a first transaction data ciphertext; sending the joint identifier set and the first transaction data ciphertext corresponding to the joint identifier set to the second participant; receiving a first joint data ciphertext sent by the second participant, the first joint data ciphertext being obtained by encrypting joint transaction data by using a random number, and the joint transaction data being determined based on the first transaction data ciphertext and the second transaction data; and performing joint calculation on the first joint data ciphertext to obtain a first joint calculation result. According to the embodiment of the invention, the safety of the transaction data can be ensured, and the joint calculation mode of the accuracy of the joint calculation result can be ensured.

The invention relates to the technical field of community operation, and discloses a community operation data analysis method and device, computer equipment and a storage medium. According to the community operation data analysis method, to-be-analyzed attribute data of a to-be-analyzed community and sample attribute data of sample communities are obtained and subjected to clustering analysis processing, and similar clustering communities and street clustering communities corresponding to the to-be-analyzed community in the sample communities are determined; obtaining similar operation index data of the similar clustering communities and street operation index data of the street clustering communities in a preset time window, and determining an index early warning threshold according to the similar operation index data and the street operation index data; and obtaining to-be-analyzed operation index data in a preset time window, judging whether the to-be-analyzed community is an abnormal community according to the to-be-analyzed operation index data and the index early warning threshold, and generating abnormal early warning information when it is confirmed that the to-be-analyzed community is the abnormal community. According to the invention, the comprehensiveness of anomaly monitoring is ensured, and the monitoring accuracy is improved.

The invention discloses an industrial visual inspection data processing method, which comprises the following steps of: extracting product appearance data through a product inspection image, constructing a product appearance preliminary screening model, comprehensively evaluating product quality from two angles of color and geometry, preliminarily screening products, ensuring the comprehensiveness of data processing, re-inspecting the preliminarily screened products, and determining the quality of the products. Image acquisition precision is analyzed and evaluated through a product detection image, image acquisition performance is comprehensively evaluated through periodic data, then the image acquisition performance is combined with a product reinspection result, visual detection efficiency is deeply evaluated, a visual regulation and control signal is generated, a visual acquisition mode is dynamically adjusted, and visual detection requirements in an environment abnormal change state are met. Therefore, the continuous stability of the visual detection efficiency is ensured, the product appearance preliminary screening model is optimized and upgraded by evaluating the preliminary screening detection efficiency of the product appearance preliminary screening model and generating a model optimization signal, the self-growth of the model is realized, and the preliminary screening detection accuracy of the model is improved.

The invention relates to the technical field of food safety management, in particular to a food quality safety traceability method, which comprises the following steps of: acquiring image information of a food surface, intercepting image information with an identification code, and preprocessing the image information with the identification code to acquire identification code information; the identification code information is identified to obtain tracing information for the food, the tracing information comprises a plurality of tracing items used for determining whole-process information of the food, whether tracing query for the food is completed or not is judged on the basis of content in each tracing item, and an uncompleted reason is determined when it is judged that the tracing query is not completed; according to the method and the device, the corresponding processing mode is generated, the corresponding instruction is generated based on the determined processing mode, the instruction is transmitted to the corresponding component so that the component receiving the instruction determines the corresponding operation parameter again, the tracing information is output when it is judged that the tracing query for the food is completed, and the tracing efficiency for the food is effectively improved.

The invention discloses a data governance method and device and a storage medium, belongs to the technical field of data processing, and is used for solving the technical problems that a data governance tool cannot solve the special data problem in actual business and cannot process unstructured data. The method comprises the following steps: reading original data in a data source; for the structured data, after the verification process based on the general verification rule is passed, secondary verification is carried out by using the service verification rule, and a data quality report is generated according to a verification result; and aiming at the unstructured data, checking by utilizing an image checking rule, and generating a data quality report according to a checking result. According to the technical scheme, the technical effect that the special data problem in the actual service can be solved on the basis that the unstructured data can be processed can be achieved.

The invention provides a diversified attack behavior recognition method and system based on a fusion recognition model, and the method comprises the steps: constructing an original training data set based on an attack received by a local end, and determining the type of missing training data based on the number of all types of labels in the original training data set; on the basis of a pre-trained data generation model, supplementing the training data of the missing training data category, and updating a local training data set; performing local training on the attack recognition model based on the updated local training data set, uploading model parameters of the trained local model to a cloud, and determining a model weight by the cloud based on the number of training data in the uploaded original training data set of the local model; and carrying out weighted calculation on the uploaded model parameters of each local model based on the model weights, issuing the updated model parameters to each local end to construct an aggregation model, and carrying out attack identification on data received by the local ends based on the aggregation model.

The application discloses a lining cloth dyeing control method and system based on artificial intelligence, and is used for the control field, and the method comprises the following steps: real-time monitoring of multi-source data in the lining cloth dye vat, capturing the video stream inside the lining cloth dye vat; using a Gaussian mixture variational autoencoder model to extract features from the multi-source data, obtaining multi-source feature data; obtaining the changing moment of the fabric state in the video stream, and extracting the fabric state change feature data according to the observed fabric color change and the heterogeneity of the dye distribution in the video stream; fusion of multi-source feature data and fabric state change feature data; introducing a model predictive control layer, predicting the result to adjust the dyeing parameters in real time; establishing an intelligent feedback mechanism. The Gaussian mixture variational autoencoder model is trained and optimized through the small-batch stochastic gradient descent and back propagation algorithm, important features are learned and captured from the data.

The invention belongs to the field of parameter optimization algorithms, discloses a meta-heuristic parameter optimization algorithm based on variation chain search, and particularly relates to a meta-heuristic evolutionary parameter optimization algorithm for variation chain search based on individual characteristics of sample points and overall generality of a sample point set. The method comprises the following specific processing steps: (1) hydrological model parameter determination and hierarchical division; (2) collecting an initial sample group; (3) extracting the optimal evolution direction (acceleration) of the individual; (4) optimizing subgroup division; (5) generating an optimization speed vector; (6) determining a search direction; and (7) convergence conditions. According to the method, on the basis of the similarity and anisotropy between the sample points in the hydrological model parameter optimization process, the sample points are updated and iterated through similarity analysis and a spatial clustering method, and a new thought is provided for the optimization method of the hydrological model.

The invention discloses a storage cabinet for computer data management, which relates to the technical field of cabinets and comprises a storage cabinet body for computer data management. Through the arrangement of the detection part, the standby heat dissipation mechanism and the alarm mechanism, the detection part can monitor the temperature in the cabinet body in real time, and when the situation that the temperature is too high is monitored, the alarm part can be started in time to give out an alarm sound to remind a user to maintain and check reasons in time; the problems that heat dissipation in daily use of a storage cabinet is an indispensable function, and when an existing cabinet is used, due to the fact that the existing cabinet is lack of a structure for monitoring the internal temperature, once the internal heat dissipation function is used along with time, aging occurs, and the heat dissipation efficiency is insufficient, alarming cannot be conducted in time are solved. Therefore, the problems that the service life is affected, the performance is reduced, and certain limitation exists are solved.

The application provides a steel bridge part manufacturing method, device, equipment and medium, and relates to the technical field of bridge manufacturing. The method comprises the following steps: acquiring basic information corresponding to each plate part in a steel bridge; generating a contour map of the plate part based on a three-dimensional model of the plate part, determining a target allowance corresponding to the plate part by using process attribute information and a preset allowance addition rule library, and modifying the contour map to obtain a target contour map according to the target allowance; generating a layout scheme based on the target contour maps corresponding to all plate parts; generating a processing instruction according to the layout scheme, and sending the processing instruction to a corresponding preset processing equipment, so that the preset processing equipment processes a mother plate according to the processing instruction. The application can realize integrated operation of each manufacturing link of the steel bridge part, and effectively improve the efficiency and quality of the steel bridge part manufacturing.

The invention relates to the field of image processing, and discloses a remote sensing image-text retrieval method, system and device based on deep learning and a medium, and the method comprises the steps: inputting a remote sensing image or remote sensing text data to be retrieved, and extracting the multi-scale features of the image and the multi-scale features of the text at the same time through a cross-modal multi-scale extraction network, through a cross-modal multi-scale alignment network, image features of different scales are utilized to guide the joint text features, text features of different modals after scale alignment are obtained, and a plurality of subspaces after scale alignment are constructed; the image features and the text features are updated in the global space and the constructed multiple subspaces through the subspace updating network and the global space updating network, and a retrieval result is generated through the similarity matching network according to the similarity matching degree. According to the method, multi-scale modeling of the remote sensing data and scale alignment among different modals are realized, irrelevant modeling among different modals is ensured, and the relationship of data of different modals is enriched.

The invention relates to the technical field of fishery light complementation automatic feeding, in particular to a fishery light complementation-based photovoltaic device capable of automatically feeding and a use method of the fishery light complementation-based photovoltaic device capable of automatically feeding, and the fishery light complementation-based photovoltaic device capable of automatically feeding comprises an I-shaped mounting plate and a plurality of photovoltaic panels arranged on the inclined surface of the I-shaped mounting plate; the device comprises a pair of reinforcing plates, the inclined surfaces of the lower ends of the pair of reinforcing plates are fixedly connected with the same L-shaped loading rod, the L-shaped loading rod is provided with a pair of symmetrical feeding devices, each feeding device comprises a feed containing box, and the lower surface of each feed containing box is communicated with a discharging pipe in a penetrating mode. According to the automatic fish feeding device, through mutual cooperation of the power-on relay, the driving motor and the small inverter, the automatic fish feeding mode is achieved, the fatigue degree of manual fish feeding and the defect of incomplete fish feeding are reduced, the total amount of the feed containing boxes of the device can guarantee that fish is fed for four days, only feed supplementing is needed in the fish feeding aspect, and the fish feeding efficiency is improved. In this way, the situation that the feed is thrown to the surface of the photovoltaic panel and pollutes the photovoltaic panel is avoided.