22results about How to "Maintain diversity" patented technology

The invention relates to a PDF extraction method and system based on deep learning and layout analysis, and the method comprises the steps: obtaining a PDF file, carrying out the element recognition of a scanning version file and a text version file through an OCR technology and a deep learning model, and enabling the elements to comprise a text, a picture, a table and a formula; dividing a page of the PDF file into a plurality of logic blocks according to the identified elements, and determining a hierarchical relationship and a sequence; deleting elements without substantial help from the identified elements, and extracting the content of the document; performing page layout analysis according to the document content, and reordering and organizing each logic block to obtain a layout; document contents are classified and analyzed, and then classified storage is carried out; and according to user requirements, splicing the classified and stored document contents in a corresponding layout to generate a document in a target format. Compared with the prior art, efficient and accurate PDF extraction is achieved, and meanwhile the important structure and content of an original document are reserved.

The invention relates to the technical field of education informatization, and discloses a digital teaching resource library intelligent management and application method and system. The method comprises the steps of constructing a digital resource library, constructing a resource application big data analysis model to calculate a resource quality index, a popularity index and an update index, performing intelligent resource sorting and elimination based on the indexes, analyzing the correlation between a user retrieval request and resources, and performing intelligent recommendation. According to the method, efficient management and accurate application of teaching resources are realized, the resource utilization rate and the teaching effect are improved, the storage space and the management cost are saved, and data support is provided for education decision making.

The invention discloses a reservoir group scheduling interval multi-target optimization method under an uncertain condition, and belongs to the technical field of reservoir optimization scheduling. The method comprises the following steps: firstly, establishing an innovative cascade reservoir group interval multi-target scheduling model; secondly, providing a double-population dynamic coordination interval optimization method for solving the interval multi-target scheduling model, and further obtaining an optimal scheduling scheme of the reservoir group; and finally, outputting an optimal scheduling scheme set of the reservoir group. According to the optimization method, through organic combination of a chaos-order mapping initialization strategy, a dynamic adaptive mutual promotion updating strategy and an elite guidance optimization strategy, optimization is rapidly and efficiently carried out to obtain a group of reliable and accurate scheduling scheme sets considering runoff uncertainty; an effective decision-making technical means for solving the cascade reservoir group optimization multi-target complex engineering problem is provided for a scheduling decision maker, the intelligent level and comprehensive benefits of water resource management are improved, and the capacity of a water resource system for coping with complex environments and uncertain factors is further enhanced.

The invention relates to the technical field of water quality monitoring, in particular to a distributed raw water quality real-time monitoring system which comprises an underground water sampling module, a sample analysis module, a water quality feedback terminal and a data storage terminal. And finally, the water body quality corresponding to the underground water quality in the target raw water body area is fed back to a system interface for interface display, the water quality evaluation can guarantee the safety and sustainability of the water resource, and the water quality evaluation efficiency is improved. Health risks and economic losses caused by water quality pollution are avoided, and underground water quality evaluation has direct influence on public health. Various health problems may be caused by drinking or using the water for a long time, the drinking water safety of residents can be guaranteed, health risks can be found and treated in time, and therefore the health of the residents is protected.

The invention provides a high-salinity high-tidal-flat mangrove forest ecological restoration method. The high-salinity high-tidal-flat mangrove forest ecological restoration method comprises the following steps of S1, soil improvement, S2, seedling cultivation, S3, seedling planting, S4, seedling reseeding, S5, bank protection device arrangement and S6, pest control. The soil conditioner is used for improving the soil structure and reducing the soil salinity. Salt-resistant domestication is performed on the seedlings by gradually improving the salinity of irrigation water, so that the salt resistance of the seedlings is improved. Organic fertilizer, ferriporphyrin, abscisic acid and brassinolide are used for providing nutrients for seedlings, osmotic equilibrium in plants is adjusted, opening and closing of air holes are adjusted, plasticity of cell walls is adjusted, and therefore the salt resistance of the plants is enhanced. According to the method, the roots of seedlings are inoculated with the halorhodobryum terbach and the proteobacteria, the halorhodobryum terbach and the proteobacteria terbach form a symbiotic relationship with the roots of plants, a microbial community is formed, and the absorption efficiency of the plants to nutrients in soil is According to the method, the planting survival rate and the plant growth rate are improved through the multi-way overall synergistic effect, and then the biological diversity is improved.

The invention discloses a task scheduling method based on an improved bat algorithm in a mobile edge computing environment. The method comprises the following steps: acquiring user task information and edge server information, and acquiring a to-be-unloaded task sequence according to a user track; the user track, the user task information and the edge server information serve as input, an optimal solution of a current population is solved through a bat search algorithm, and each individual in the bat population is mapped to a corresponding task sequence; judging whether the task sequence needs to be subjected to local search or not, and if yes, performing local search by utilizing local sensitive hashing to obtain a global optimal solution after the local search; and according to the searched global optimal solution, dynamically updating the individual positions of the bat population until a set stop criterion is met, and outputting a final task scheduling decision. According to the method, the task scheduling quality is improved while the calculation efficiency is ensured, and the method has relatively high universality and expandability.

The invention discloses a wind power prediction method and system based on an improved sparrow algorithm, and relates to the technical field of wind power generation, and the method comprises the steps: collecting and preprocessing the historical operation data of a wind power plant, and constructing a wind power prediction model; the method comprises the following steps: introducing Tent chaotic mapping into a traditional sparrow search algorithm, and introducing adaptive parameters into the Tent chaotic mapping to obtain a preliminary improved sparrow search algorithm; integrating Gaussian mutation operation to obtain a final improved sparrow search algorithm; and using the final improved sparrow search algorithm to optimize the wind power prediction model, and using the optimized wind power prediction model to predict the wind power. According to the invention, through multi-level algorithm improvement and optimization strategies, the problem that a traditional sparrow search algorithm is easy to fall into local optimum is successfully solved; by introducing Tent chaotic mapping and adaptive parameters, the initial population position is optimized, and the global search capability is improved; gaussian mutation operation is integrated, population diversity is maintained, and the capability of jumping out of local optimum is enhanced.

The invention relates to the technical field of image processing, and discloses a medical image denoising method based on a 3D chaotic mapping dung beetle algorithm, and the method comprises the following steps: 1, inputting a to-be-processed original medical image, carrying out the noise adding of the original medical image, and generating a noisy image; step 2, inputting the noisy image into a hybrid filter used for denoising the image; 3, calculating an optimal parameter combination of each filter in the hybrid filter by adopting a dung beetle optimization algorithm, and configuring the hybrid filter by adopting the optimal parameter combination; step 4, performing denoising processing on the noisy image by using the configured hybrid filter to generate a denoised image; wherein in the step 3, the distribution position of the population is initialized by adopting 3D chaotic mapping; the technical problem of poor medical image denoising effect in the prior art is solved.

The invention relates to an online map construction method and system based on inverse perspective mapping and synchronous learning. A perspective image is obtained and preprocessed, a multi-scale inverse perspective mapping image is obtained through transformation, and global aerial view features are obtained through multi-scale strip convolution decoding, strip convolution residual connection in different directions, layer-by-layer decoding and feature fusion; obtaining perspective features of the preprocessed perspective image through a synchronous learning sequence and a semantic segmentation network; and converting the perspective features into a bird's-eye view coordinate system, aligning the perspective features with the global bird's-eye view features in space to obtain enhanced perspective features, fusing the global bird's-eye view features and the enhanced perspective features through convolution operation, and outputting the fused features to a current frame of the constructed map through a decoder. Inverse perspective mapping and synchronous learning are combined, multi-frame aerial view features and perspective features are fused, a road structure under an aerial view angle is reserved, and environmental details in a perspective image are supplemented in a perspective mode.

The invention discloses a multi-target thermal power output optimization method of a heliostat field based on a Monte Carlo algorithm and GP-GOMEA, and particularly relates to the field of heliostat field output power optimization, comprising the following steps: firstly, through step A1, establishing a proper coordinate system as an analysis basis; then, in the step A2, an accurate mathematical model of the heliostat field is constructed by using a GP-GOMEA algorithm; in order to predict and analyze the performance of the heliostat field, a Transform model is introduced in the step A3, and key data support is provided for optimization design; in order to further improve the optimization effect, the NSGA-II, the GP-GOMEA and the Transform are combined in the step A4 to form a multi-modal genetic model so as to solve the optimization design problem of the heliostat field; then, in the step A5, based on the evaluation function and the input data, an NSGA-II algorithm is used for solving, and a group of Pareto optimal solutions are obtained to serve as candidate schemes; finally, in the step A6, a final scheme is carefully selected from Pareto optimal solutions to serve as an optimization design result of the heliostat field.

The invention provides an economic management data analysis device and method, and the method comprises the steps: obtaining original data based on an original enterprise insurance management system and a crawler engine, carrying out the preprocessing of the original data, and carrying out the investment and asset data analysis based on the preprocessing of the original data; according to the method, the Boolean's rule and the multi-objective optimization algorithm are combined, maximization of benefits of enterprises is taken as an objective function, insurance premium related data, compensation and claim settlement data, investment and asset data, business scale and market share, customer satisfaction and employee satisfaction are adopted to optimize the NSGA-II algorithm, and decision making is carried out. According to the method, the existing data are fully utilized, the relevance between the data is mined, and the insurance premium strategy and the investment strategy are optimized, so that the maximization of enterprise revenue is realized. Meanwhile, through continuous monitoring and strategy adjustment, the enterprise can adapt to the continuously changing market environment, and the competitive advantages of the enterprise are kept.

This application belongs to the field of artificial intelligence and healthcare technology, specifically disclosing a multi-memory large model enhancement method and system based on adaptive resonance theory. The method includes: obtaining memory units from the plot memory module based on a new medical dialogue event; processing the new medical dialogue event through a large model based on multi-source memory; multi-source memory is constructed based on information stored in memory units, working memory modules, and semantic memory modules; the plot memory module is used to: determine candidate plot prototypes by analyzing attribute similarity; determine whether there is resonance between the new medical dialogue event and the candidate plot prototype; if there is resonance, use historical dialogue events in the event set of the resonant plot prototype as memory units and update the resonant plot prototype; if there is no resonance, create a new plot prototype. This application enables effective memory management and improves the stability and accuracy of large model reasoning in medical dialogue scenarios.

The present invention relates to the technical field of model optimization, and in particular to a method and system for optimizing a large model of a Wensheng graph based on multi-objective optimization. The method comprises: acquiring text data; constructing a large model of a Wensheng graph based on a diffusion model; constructing a multi-objective optimization problem based on optimization variables, optimizing parameters of the large model of the Wensheng graph based on the multi-objective optimization problem and using the NSGA‑II algorithm; based on parameter optimization, using the large model of the Wensheng graph to perform reverse diffusion to generate a final user demand image. The Wensheng graph optimization fine-tuning method proposed in the present invention can optimize multiple conflicting objectives at the same time. For the fine-tuning of the Wensheng graph model, the clarity, color fidelity and detail expression of the image can be improved at the same time. At the same time, it is ensured that the generated image is highly consistent with the input text in semantics.

The present invention belongs to the technical field of black soil hydraulic erosion risk assessment, and relates to a black soil hydraulic erosion risk assessment method based on daily precipitation. The present invention realizes accurate assessment of hydraulic erosion conditions of each sub-region of the target black soil by analyzing hydraulic erosion feedback indicators of each sub-region to which the target black soil belongs, which helps to give early warning to high-risk areas, give priority to their governance, reduce the occurrence of erosion disasters, improve governance efficiency and effect, ensure food security, maintain ecological balance, and promote ecological security. By analyzing the hydraulic erosion risk indicators of each sub-region to which the target black soil belongs, it helps to scientifically plan land use and agricultural production activities, effectively protect the ecological environment of black soil, maintain biodiversity, and facilitate early discovery of potential hydraulic erosion risks and taking preventive measures to reduce economic losses caused by soil erosion.

The invention discloses a remote sensing image target detection method based on an improved YOLOv8 model, and the method comprises the steps: replacing a C2f layer of a Backbone network in the YOLOv8 model with an RFN composite convolution module, and additionally arranging an ASCPA adaptive spatial correlation pyramid attention module at a connection part of an SPPF module and a Neck feature enhancement network of the Backbone network, thereby obtaining the improved YOLOv8 model. And performing target detection on the remote sensing image by using the improved YOLOv8 model. By adopting the remote sensing image target detection method, a network can efficiently fuse local and global features, the diversity and integrity of the features are kept, meanwhile, multi-scale spatial information on a feature map can be effectively extracted, effective features are selectively enhanced through spatial correlation feature re-calibration, and the target detection accuracy is improved. And the attention capability to the small target is improved.

The utility model discloses a control circuit of cutting color temperature and cutting lamp board simultaneously cutting power, including LED power supply, switch board and lamp board, LED power supply is connected with switch board, switch board is connected with lamp board, and switch board includes dial switch. Through the implementation control circuit of the utility model embodiment can realize the change trend of better adaptation market demand while keeping existing function, and the production cost is reduced greatly and the system architecture is simplified, thereby.

The invention discloses a medical prevention and control resource scheduling method based on a group dynamic deduction mechanism, relates to the field of medical prevention and control resource scheduling, and aims to solve the problem that the medical prevention and control resource scheduling is not required under the conditions of meeting resource balance constraint and node resource demand constraint for a highly infectious outbreak region. Reasonable resource allocation needs to be carried out on each node by taking day as a period, so that the prevention and control resource usage amount, the prevention and control duration and the number of infected people are minimized. For the problem, the invention provides a method based on a group dynamic deduction mechanism, which covers the following aspects: abstracting characteristics and models of group dynamic deduction by integrating factors such as a continuous improvement mechanism of group dynamic deduction, matrix sequence coding of resources and the like. Based on the model, the invention provides an algorithm for processing the medical prevention and control resource scheduling problem. The algorithm design comprises individual self-deduction and collaborative deduction based on group dynamic deduction, continuous improvement processing and matrix sequence coding.

The invention relates to the technical field of data processing, and provides a rural cultural heritage protection method, which comprises the following steps: acquiring historical rural cultural heritage data, constructing a standard digital image, acquiring and processing the cultural heritage data in real time, performing feature extraction and coordinate data matching, comparing error information and determining an error region. And finally, performing field inspection by using inspection equipment. And when it is detected that the cultural heritage changes significantly, early warning information is generated in time. According to the method, the problem that the rural cultural heritage protection data cannot be dynamically detected in the prior art is solved, the protection efficiency and accuracy are improved, and powerful support is provided for sustainable development and inheritance of the rural cultural heritage.

The utility model relates to the technical field of heat radiators, and aims to provide a phase change heat radiator and inversion equipment with the phase change heat radiator. The internal circulation resistance of the phase change radiator is small, and the radiating efficiency is high. The phase change radiator comprises a substrate and a plurality of radiating fins, the substrate is provided with a first cavity, and a phase change medium is arranged in the first cavity; the cooling fins are connected with the base plate through arc-shaped connecting parts at one ends and provided with second cavities, and the second cavities communicate with the first cavities. The phase-change radiator solves the problem that the internal structure of the phase-change radiator in the prior art has large circulation resistance to media, so that the radiating efficiency is low.

The invention belongs to the technical field of organoid culture, and particularly relates to a passage method of a human induced pluripotent stem cell-derived small intestine organoid and application of the passage method. According to the passage method disclosed by the invention, after matrigel is mildly removed by a dissociation reagent, long-range stable passage of the small intestine organoid can be maintained by a method for slightly breaking the small intestine organoid through a suction head, and the structure and cell type diversity of the small intestine organoid can be maintained. Meanwhile, enteroviruses are infected into the small intestine organoid obtained by adopting the passage method, and the enteroviruses can be effectively copied in the small intestine organoid and infect one or more cells including intestinal epithelial cells, proliferative cells, panning cells and intestinal endocrine cells; therefore, the method can be used for related research of enterovirus infection and host interaction.