Prediction method and device for non-abandoned item material suitable growth area and storage medium

Abstract

The invention discloses a prediction method and device for a non-abandoned item material suitable-for-growth area and a storage medium. Relates to the technical field of non-abandoned project protection, and mainly aims to improve the prediction accuracy of a non-abandoned project material suitable-for-life area so as to realize distribution prediction and targeted protection of non-abandoned projects. Comprising the following steps: in response to a suitable region prediction instruction of a non-perpetual item material, obtaining a manufacturing raw material of a material carrier required for forming a target non-perpetual item, and determining a candidate region image of a candidate suitable region corresponding to the manufacturing raw material, and environment information influencing the raw material in the candidate suitable region; based on the environment information, determining the suitable probability of the manufacturing raw material under each raster image in the candidate area image; and selecting a suitable grid image in each grid image based on the suitable probability, and determining at least one suitable area corresponding to the non-abandoned item material from the suitable grid image. The method is suitable for the scene of predicting the suitable growth area of the non-abandoned project material and protecting the non-abandoned project.

Description

Technical Field

[0001] The present invention relates to the technical field of intangible cultural heritage project protection, and in particular to a method, device and storage medium for predicting suitable growth areas of intangible cultural heritage project materials. Background Art

[0002] my country's representative intangible cultural heritage items (intangible cultural heritage items) are representatives of China's excellent traditional culture and the crystallization of the wisdom of human cultural diversity. Intangible cultural heritage is inseparable from the material materials related to it. Based on this, predicting the suitable areas for the protection of intangible cultural heritage items becomes particularly important.

[0003] Currently, the area where an intangible cultural heritage item is declared is usually used as the suitable habitat for its corresponding production materials. However, this method of determining suitable habitats only focuses on the intangible cultural heritage item as a whole, resulting in low accuracy in determining the suitable habitats for intangible cultural heritage material. Summary of the Invention

[0004] The present invention provides a method, device and storage medium for predicting the suitable growth area of ​​intangible cultural heritage project materials, which mainly aims to improve the prediction accuracy of the suitable growth area of ​​intangible cultural heritage project materials, realize the prediction of the potential distribution area of ​​intangible cultural heritage, and further promote the overall protection of intangible cultural heritage.

[0005] According to a first aspect of the present invention, a method for predicting suitable growth areas of intangible cultural heritage materials is provided, comprising:

[0006] In response to the suitable growth zone prediction instruction for the intangible cultural heritage project material, the raw materials for forming the material carrier required for the target intangible cultural heritage project are obtained, and candidate region images of candidate suitable growth zones corresponding to the raw materials are determined, as well as environmental information in the candidate suitable growth zones that affects the raw materials;

[0007] Based on the environmental information, determining the probability of the production raw material being suitable for each grid image in the candidate area image;

[0008] Based on the suitable growth probability, a suitable growth grid image is selected from each of the grid images, and at least one suitable growth area corresponding to the intangible cultural heritage item material is determined by each of the suitable growth grid images.

[0009] Optionally, the production raw material is at least one;

[0010] The method of selecting a suitable growth grid image from each of the grid images based on the suitable growth probability, and determining at least one suitable growth area corresponding to the intangible cultural heritage item material from each of the suitable growth grid images, comprises:

[0011] Taking any one of the raw materials as a target raw material, determining a suitable grid image having a suitable growth probability greater than a preset threshold in each grid image based on the suitable growth probability of the target raw material in each grid image in the candidate region image, performing spatial clustering on each of the suitable grid images, and determining at least one material suitable region for the target raw material according to the clustering result;

[0012] Based on the material suitable growth areas corresponding to each of the production raw materials, the overlapping material suitable growth areas corresponding to each of the production raw materials are determined, and the overlapping material suitable growth areas are determined as the suitable growth areas of the intangible cultural heritage project materials.

[0013] Optionally, determining the suitable growth area of ​​the overlapping materials as the suitable growth area of ​​the intangible cultural heritage project materials includes:

[0014] Obtaining a preset cross structuring element template and determining a corrosion binary image corresponding to the image of the suitable area of ​​the overlapping material, wherein the preset cross structuring element template is composed of a central pixel as an origin and one pixel extended in the horizontal direction and the vertical direction of the origin, and the pixel values ​​of the central pixel and the extended pixels are both set to 1;

[0015] Taking any pixel point in the eroded binary image as a pixel point to be eroded, and aligning the central element of the preset cross structure element template with the pixel point to be eroded;

[0016] Determine whether the pixel values ​​of the pixels in the eroded binary image covered by the positions with a value of 1 in the aligned preset cross structuring element template are all 1; if so, determine the pixel to be eroded as a first foreground image pixel; otherwise, determine the pixel to be eroded as a first background image pixel, and each first foreground image pixel and each first background image pixel constitute the overlapping material suitable area after the erosion process;

[0017] Any pixel point in the expanded binary image corresponding to the suitable area of ​​the overlapping material after the corrosion process is used as a pixel point to be expanded, and the central element of the preset cross structure element template is aligned with the pixel point to be expanded;

[0018] Determining whether there is at least one 1 in the pixel values ​​of the pixels in the dilated binary image covered by the position with a value of 1 in the aligned preset cross structuring element template; if so, determining the pixel to be dilated as a second foreground image pixel; otherwise, determining the pixel to be dilated as a second background image pixel, and each second foreground image pixel and each second background image pixel forming the overlapping material suitable area after dilation;

[0019] The suitable growth area of ​​the overlapping materials after the expansion treatment is determined as the suitable growth area of ​​the intangible cultural heritage project materials.

[0020] Optionally, determining the suitability probability of the production raw material in each grid image in the candidate area image based on the environmental information includes:

[0021] Determine the grid environment information f corresponding to each grid image z in the environment information i (z), and respectively determine each of the grid environment information f i (z) corresponding weight coefficient λ i ;

[0022] Based on each of the grid environment information f i (z) and its corresponding weight coefficient λ i , determine the appropriate generation probability p(z) corresponding to each of the grid images z, Wherein, n is the number of grid environment information, i is the identifier of each of the grid environment information, and a is a normalization constant.

[0023] Optionally, after determining at least one suitable area corresponding to the intangible cultural heritage item material from each of the suitable grid images, the method further comprises:

[0024] Acquire predicted environmental information of each of the suitable areas after a preset time, and determine the predicted suitable probability corresponding to each grid image in the suitable area image of each of the suitable areas based on the predicted environmental information;

[0025] Based on the predicted suitable growth probability, determining the predicted suitable growth area of ​​the intangible cultural heritage item material after the preset time in each suitable growth area;

[0026] Based on each of the suitable growth areas and its corresponding predicted suitable growth area, determining the extent of reduction in area of ​​each of the suitable growth areas after the preset time;

[0027] Based on the degree of reduction in the area of ​​the current suitable zone where the intangible cultural heritage project materials are located, determine whether it is necessary to recommend a suitable zone for the intangible cultural heritage project materials; if so, determine a recommended suitable zone in each of the suitable zones, and determine a recommended path from the current suitable zone to the recommended suitable zone for the intangible cultural heritage project materials; based on the recommended path, recommend the intangible cultural heritage project materials from the current suitable zone to the recommended suitable zone; otherwise, it is prohibited to recommend a suitable zone for the intangible cultural heritage project materials.

[0028] Optionally, determining a recommended path from the current suitable growth area to the recommended suitable growth area for the intangible cultural heritage item material includes:

[0029] Determining a plurality of candidate recommended paths from the current suitable habitat area to the recommended suitable habitat area, and determining, based on terrain data of an area in which each candidate recommended path is located, a terrain slope and a land use type, as well as a slope resistance corresponding to the terrain slope and a land resistance corresponding to the land use type for each candidate recommended path;

[0030] Determining a relative importance ratio of the terrain slope and the land use type to the recommended resistance, and constructing a judgment matrix of the terrain slope and the land use type to the recommended resistance based on the relative importance ratio, and determining resistance weight coefficients of the terrain slope and the land use type respectively based on the judgment matrix;

[0031] Based on the resistance weight coefficient, the slope resistance and the land resistance are weighted and summed to obtain a comprehensive recommendation coefficient corresponding to each candidate recommended path, and based on the comprehensive recommendation coefficient, the recommended path of the intangible cultural heritage project material is determined in each candidate recommended path.

[0032] Optionally, the step of obtaining raw materials for producing the material carrier required for forming the target intangible cultural heritage item includes:

[0033] Obtaining descriptive text information of the target intangible cultural heritage item, searching a preset corpus for supplementary corpus information whose similarity to the descriptive text information is greater than a preset similarity threshold, and inputting the descriptive text information and the supplementary corpus information into a large model with a sequence annotation header for carrier prediction, thereby obtaining a material carrier required to form the target intangible cultural heritage item;

[0034] Obtain material prediction prompt information, input the material prediction prompt information and the material carrier into a preset material prediction model for material prediction, and obtain the raw materials for making the material carrier, wherein the preset material prediction model is pre-constructed based on a sample material carrier data set with a production material label.

[0035] According to a second aspect of the present invention, there is provided a device for predicting suitable growth areas of intangible cultural heritage materials, comprising:

[0036] an acquisition unit, configured to, in response to a suitable growth zone prediction instruction for intangible cultural heritage project materials, acquire raw materials for forming a material carrier required for a target intangible cultural heritage project, and determine candidate region images of candidate suitable growth zones corresponding to the raw materials, as well as environmental information in the candidate suitable growth zones that affects the raw materials;

[0037] A first determining unit is configured to determine, based on the environmental information, a probability of suitability of the production raw material under each grid image in the candidate area image;

[0038] The second determining unit is used to select a suitable grid image in each of the grid images based on the suitable probability, and determine at least one suitable area corresponding to the intangible cultural heritage item material from each of the suitable grid images.

[0039] According to a third aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for predicting the suitable growth area of ​​the intangible cultural heritage project materials.

[0040] According to a fourth aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method for predicting suitable habitats for intangible cultural heritage materials when executing the program.

[0041] According to the present invention, a method, device, and storage medium for predicting the suitable growth zone for intangible cultural heritage project materials are provided. Compared to the current method of determining the region where the intangible cultural heritage project is inherited as the suitable growth zone for the corresponding production materials, the present invention determines the production materials of the target intangible cultural heritage project and selects candidate suitable growth zones. Then, based on the environmental information of the candidate suitable growth zones, the suitable growth probability of the production materials under each grid image in the candidate region image is determined. Based on the suitable growth probability, a suitable grid image is selected in each grid image, and at least one suitable growth zone corresponding to the intangible cultural heritage project material is determined from each suitable grid image. That is, the present invention automatically determines the suitable growth zone for intangible cultural heritage project materials by considering environmental information, which can improve the accuracy of determining the suitable growth zone for intangible cultural heritage project materials. The suitable growth zones can effectively reproduce the intangible cultural heritage project materials, thereby improving the effective protection of intangible cultural heritage projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0043] Figure 1 A flow chart of a method for predicting suitable growth areas of intangible cultural heritage materials provided by an embodiment of the present invention is shown;

[0044] Figure 2 A flow chart of another method for predicting suitable growth areas of intangible cultural heritage materials provided by an embodiment of the present invention is shown;

[0045] Figure 3 A schematic structural diagram of a device for predicting suitable growth areas of intangible cultural heritage materials provided by an embodiment of the present invention is shown;

[0046] Figure 4 A schematic structural diagram of another device for predicting suitable growth areas of intangible cultural heritage materials provided by an embodiment of the present invention is shown;

[0047] Figure 5 A schematic diagram of the physical structure of a computer device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0048] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0049] At present, the method of determining the area where the intangible cultural heritage project is declared as the suitable area for its corresponding production materials ignores the connection between the intangible cultural heritage itself and the environment, and only facilitates the administrative management of the intangible cultural heritage project, resulting in low accuracy in the determination of the suitable area for the intangible cultural heritage project materials. At the same time, if the existing area of ​​the intangible cultural heritage project materials shrinks, it will lead to the endangerment of the intangible cultural heritage project materials, which will in turn affect the protection of the intangible cultural heritage project.

[0050] In order to solve the above problems, the embodiment of the present invention provides a method for predicting the suitable growth area of ​​intangible cultural heritage materials, such as Figure 1 As shown, the method includes:

[0051] 101. In response to the suitable growth zone prediction instruction for the intangible cultural heritage project materials, the raw materials for forming the material carrier required for the target intangible cultural heritage project are obtained, and candidate area images of candidate suitable growth zones corresponding to the raw materials are determined, as well as environmental information in the candidate suitable growth zones that affects the raw materials.

[0052] The target intangible cultural heritage item can be any intangible cultural heritage item. For example, if the target intangible cultural heritage item is "Shalang", its corresponding material carriers are "Qiang flute" and "linen clothing", and the raw material required to make Qiang flute is "oil bamboo", and the raw material required to make linen clothing is "ramie". If the target intangible cultural heritage item is "Pingyao polished lacquerware", its corresponding material carrier is "natural lacquer", and the raw material required to make natural lacquer is "lacquer tree".

[0053] For the embodiment of the present invention, in order to predict the suitable zone of the materials of the target intangible cultural heritage project, it is first necessary to determine the raw materials required to form the target intangible cultural heritage project. Based on this, step 101 specifically includes: obtaining the descriptive text information of the target intangible cultural heritage project, searching for supplementary corpus information in a preset corpus whose similarity with the descriptive text information is greater than a preset similarity threshold, and inputting the descriptive text information and the supplementary corpus information into a large model with a sequence annotation header added to perform carrier prediction to obtain the material carrier required to form the target intangible cultural heritage project; obtaining material prediction prompt information, inputting the material prediction prompt information and the material carrier into a preset material prediction model to perform material prediction to obtain the raw materials for the production of the material carrier, wherein the preset material prediction model is pre-constructed based on a sample material carrier data set with production material labels.

[0054] Among them, the descriptive text information includes the name, introduction, inheritance area, skill description, species distribution data, etc. of the target intangible cultural heritage project; the preset corpus stores the descriptive corpus information of various intangible cultural heritage projects; the preset similarity threshold is set according to actual needs.

[0055] Specifically, in order to improve the prediction accuracy of the large model, it is first necessary to train and build a large model with a sequence annotation header. The specific construction method includes: obtaining an initial large model with a sequence annotation header, and obtaining a sample data set, wherein the sample data set contains descriptive text information of sample intangible cultural heritage items with carrier labels; using a random or predetermined strategy to divide the sample data set into training data and test data, and using the training data to train the initial large model. During the training process, the loss value, mAP and other indicators during the training process are monitored to evaluate the model performance, and the training parameters such as learning rate, optimizer, regularization, etc. are adjusted as needed to optimize the training effect. During the training process, the cross entropy loss function with category weights is used to add a sequence annotation header based on the initial large model as shown below:

[0056]

[0057] Among them, w c is the category weight, y i,c is the true label of the i-th token, p i,cis the predicted probability of the initial large model, N is the total number of tokens, and C is the total number of categories. Use an optimizer such as AdamW (Adaptive Moment Estimation WeightDecay, an optimization algorithm) to optimize the initial model parameters to minimize the loss function and train the initial large model to recognize carrier entities. The trained initial large model is then tested on the test data to evaluate its performance on unseen data. Calculate and record indicators such as mAP, precision, and recall on the test set. If the performance of the large model does not meet the requirements, return to the training stage for more iterations or adjustments. Until the model performance meets the requirements, a large model that meets the requirements is obtained.

[0058] Furthermore, the descriptive text information is cleaned and standardized, such as removing HTML tags and special symbols from the intangible cultural heritage description text; using regular expressions to extract key paragraphs (such as sentences containing "materials," "production," and "use"); and performing OCR text recognition and sentence segmentation on the descriptive text information. For example, if the target intangible cultural heritage item is "Sirloin," the data preparation and preprocessing of the descriptive text information of Sirloin can be performed according to the following procedures:

[0059]

[0060]

[0061] Based on the above preprocessing method, processed descriptive text information can be obtained. Furthermore, to improve the prediction accuracy of material carriers, the processed descriptive text information needs to be supplemented. To this end, the similarity between the descriptive text information and each corpus in the preset corpus can be calculated. Corpuses with similarities greater than a preset similarity threshold are then selected from the preset corpus as supplementary corpus. Ultimately, the supplementary corpus and the descriptive text information are input into a large model with a sequence annotation header to perform carrier prediction, thereby obtaining the material carrier required to form the target intangible cultural heritage item. Specifically, to utilize the latest information, improve carrier prediction accuracy, and enhance the interpretability and adaptability of the predicted carrier, the present invention adds a RAG (Retrieval Augmented Generation) module to the large model. This module uses information from private or proprietary data sources to assist in text generation, thereby overcoming the limitations of descriptive text information, helping to address the problem of hallucinations and improving timeliness. Text segmentation: Externally input files of different formats are converted into plain text and sentences are segmented by periods (".") and line breaks, making them more suitable for embedded search and adapting to the large model, thereby improving the accuracy of fragment recall. Text embedding: The text content is converted into a multidimensional vector (i.e., a digital language that can be outputted by artificial intelligence) through word embedding. The embodiment of the present invention can use the bge-large-en-v1.5 embedding model for text vectorization. Create an index: The original descriptive text information and the supplementary corpus information are stored in the form of information pairs to facilitate fast and frequent searches in the future. Data retrieval: Based on the descriptive text information, the most relevant supplementary corpus information is quickly retrieved and integrated into the prompt. Based on the descriptive text information, the descriptive text information is converted into a vector using the same encoding model as the index creation; the similarity between the vector and each corpus vector in the preset corpus is calculated, and the top K most relevant corpora are selected as the supplementary corpus information for the current descriptive text information based on the similarity level. By determining the supplementary corpus information of the descriptive text information, the embodiment of the present invention can improve the prediction accuracy and comprehensiveness of the material carrier corresponding to the target intangible cultural heritage item.

[0062] Furthermore, after predicting the material carriers required to form the target intangible cultural heritage item, it is necessary to predict the materials used to make the carriers. Specifically, a preset material prediction model can be used to predict the materials used to make the carriers. Prior to this, to improve the prediction accuracy of the preset material prediction model, the preset material prediction model must first be trained and constructed. Based on this, the method includes: obtaining a preset initial material prediction model and a sample dataset, wherein the sample dataset includes sample material carriers labeled with their raw materials; dividing the sample dataset into training data and test data using a random or predetermined strategy; training the preset initial material prediction model using the training data; monitoring metrics such as loss and mean average prediction accuracy (MAP) during training to evaluate model performance, and adjusting training parameters such as the learning rate, optimizer, and regularization as needed to optimize training results. The trained preset initial material prediction model is then tested using the test data to evaluate its performance on unseen data. Metrics such as mAP, precision, and recall on the test dataset are calculated and recorded. If the performance of the preset initial material prediction model does not meet requirements, the training phase can be returned to for further iterations or adjustments. Until the performance of the preset initial material prediction model meets the requirements, a preset material prediction model that meets the requirements is obtained.

[0063] Furthermore, the material prediction prompt information is determined, wherein the material prediction prompt information is determined according to the demand. For example, if the material carrier is "Qiang flute", the material prediction prompt information may be "the material must be natural raw materials, excluding synthetic materials", "give priority to relevant materials recorded in the input text", etc. The material prediction prompt information and the material carrier are input together into the constructed preset material prediction model to perform material prediction and obtain the raw materials for the material carrier. For example, if the material carrier is "Qiang flute", the prediction process of its corresponding production material is: given the material carrier: {Qiang flute}, its production material is inferred based on the following knowledge:

[0064] The material prediction prompt reads: Materials must be natural, excluding synthetic materials; prioritize materials relevant to the input text. Output format: Material name (type), such as: Oil bamboo (biological). Answer: Reference context: {context}#text block retrieved from the RAG knowledge base. Chain-of-Thought fine-tuning: facilitates explicit output of the reasoning process. Input: Carrier = Qiang flute. Output: Reasoning steps: The Qiang flute is a traditional musical instrument of the Qiang ethnic group. Literature records that its production materials must meet the following requirements: - Hollow bamboo tube for easy sound production → requires a specific bamboo species; - Resistant to dry climates, suitable for the western Sichuan plateau → excludes bamboo species from humid regions. The "Chinese Bamboo Catalogue" indicates that the oil bamboo (Fargesia angustissima) distributed in the Minjiang River basin meets these characteristics. Conclusion: Oil bamboo (biological). After predicting the raw materials, you can check whether the raw materials are recorded as distributed in the intangible cultural heritage area. You can also add a manual review interface to verify the accuracy of the predicted raw materials. Furthermore, the production raw materials can be checked to determine whether they are biological or non-biological materials based on the species distribution database and the mineral resource distribution database. The species distribution database records various biological materials and their corresponding distribution information, while the mineral resource distribution database records various non-biological materials and their corresponding distribution data.

[0065] Furthermore, after determining the raw materials corresponding to the target intangible cultural heritage project, candidate suitable growth areas are determined based on actual needs, wherein the candidate suitable growth areas can be any area. At the same time, based on the environmental information of the existing areas of the raw materials, the environmental information that affects the growth of the raw materials is determined. The environmental information can be the annual average temperature, the monthly average of the day and night temperature difference, isothermality, the standard deviation of temperature seasonality, the highest temperature in the warmest month, the lowest temperature in the coldest month, the annual average temperature variation range, the average temperature of the wettest quarter, the average temperature of the driest quarter, the average temperature of the warmest quarter, the average temperature of the coldest quarter, the average annual precipitation, the precipitation of the wettest month, the precipitation of the driest month, the coefficient of variation of precipitation, the precipitation of the wettest quarter, the precipitation of the driest quarter, the precipitation of the warmest quarter, the precipitation of the coldest quarter, altitude, soil type, soil pH, soil organic carbon content, average sunshine duration, etc.

[0066] 102. Based on the environmental information, determine the probability of the production raw materials being suitable for each grid image in the candidate area image.

[0067] The candidate region image corresponding to the candidate suitable area is determined, and the candidate region image is grid-divided according to actual needs to obtain each grid image in the candidate region image. For example, when performing grid division, the grid size (e.g., 100x100 pixels), starting coordinates (e.g., starting from the upper left corner of the image by default), and overlap ratio (e.g., 5% overlap to avoid edge effects) are first determined. Then, the candidate region image is grid-divided according to the grid size, starting coordinates, and overlap ratio to obtain each grid image.

[0068] In the embodiment of the present invention, after determining the environmental information that affects the production of raw materials in the candidate suitable growth area, it is necessary to determine the suitable growth probability of each grid image of the raw materials based on the environmental information. Based on this, step 102 specifically includes: determining the grid environmental information f corresponding to each grid image z in the environmental information. i (z), and respectively determine each of the grid environment information f i (z) corresponding weight coefficient λ i Based on each of the grid environment information f i (z) and its corresponding weight coefficient λ i , determine the appropriate generation probability p(z) corresponding to each of the raster images z, Wherein, n is the number of grid environment information, i is the identifier of each of the grid environment information, and a is a normalization constant.

[0069] Specifically, the grid environment information and its corresponding weight coefficient corresponding to each grid image are substituted into the above formula. This formula can be used to calculate the corresponding survival probability for each grid image, i.e., the probability of survival. By determining the environmental information that affects the production of raw materials and combining this environmental information to predict the survival probability, the embodiments of the present invention can avoid the waste of resources and time associated with analyzing environments that have no impact on the production of raw materials. Furthermore, by using environmental information to determine the suitable growth zone for the production of raw materials, the accuracy of the determination of the suitable growth zone for the production of raw materials can be improved.

[0070] 103. Based on the probability of suitability, a suitable grid image is selected from each grid image, and at least one suitable area corresponding to the intangible cultural heritage project material is determined by each suitable grid image.

[0071] Specifically, a target survival probability is determined in each raster image, where the survival probability is greater than a preset threshold. The raster image corresponding to the target survival probability is then determined as a survival raster image. Subsequently, at least one survival zone corresponding to the intangible cultural heritage project material is determined based on the survival raster image corresponding to each production raw material. Thus, by predicting the survival zone for each production raw material corresponding to the target intangible cultural heritage project, the embodiment of the present invention can ensure that the ultimately determined survival zone can meet the survival requirements of each production raw material. That is, in the process of predicting the survival zone of the intangible cultural heritage project material, the collaborative constraints of multiple materials are taken into account, thereby improving the prediction accuracy of the survival zone of the intangible cultural heritage project material.

[0072] According to a method for predicting suitable growth zones for intangible cultural heritage materials provided by the present invention, compared to the current method of determining the region where the intangible cultural heritage is inherited as the suitable growth zone for the corresponding production materials, the present invention determines the production materials of the target intangible cultural heritage project and selects candidate suitable growth zones. Then, based on the environmental information of the candidate suitable growth zones, the suitable growth probability of the production materials under each grid image in the candidate region image is determined. Based on the suitable growth probability, a suitable grid image is selected in each grid image, and at least one suitable growth zone corresponding to the intangible cultural heritage material is determined from each suitable grid image. That is, the present invention automatically determines the suitable growth zone for intangible cultural heritage materials by considering environmental information, which can improve the accuracy of determining the suitable growth zone for intangible cultural heritage materials. The suitable growth zones can effectively reproduce the intangible cultural heritage materials, thereby improving the effective protection of intangible cultural heritage.

[0073] Furthermore, in order to better illustrate the above process of classifying data, as a refinement and extension of the above embodiment, the embodiment of the present invention provides another method for predicting the suitable growth area of ​​intangible cultural heritage project materials, such as Figure 2 As shown, the method includes:

[0074] 201. In response to the suitable growth zone prediction instruction for the intangible cultural heritage project materials, obtain the raw materials for forming the material carrier required for the target intangible cultural heritage project, and determine the candidate area images of the candidate suitable growth zones corresponding to the raw materials, as well as the environmental information in the candidate suitable growth zones that affects the raw materials.

[0075] Specifically, environmental information that affects the survival of the production raw materials is analyzed by analyzing environmental information of the area where the production raw materials are currently located.

[0076] 202. Based on the environmental information, determine the appropriateness probability of the production raw material under each grid image in the candidate area image, wherein the production raw material is at least one type.

[0077] Specifically, the environmental information that affects the production of raw materials in the candidate suitable growth area includes the environmental information under each grid image. Based on the environmental information under each grid image, the suitable growth probability of the production raw materials under each grid highlight is determined. Different grid images correspond to different grid areas, thereby determining the suitable growth probability corresponding to each small grid area in the candidate suitable growth area.

[0078] 203. Take any one of each type of production raw materials as a target production raw material, determine a suitable raster image with a suitable probability greater than a preset threshold in each raster image based on the suitable probability of the target production raw material in each grid image in the candidate area image, perform spatial clustering on each suitable raster image, and determine at least one material suitable area for the target production raw material based on the clustering results.

[0079] The preset threshold is set according to actual needs. Specifically, the target intangible cultural heritage project will correspond to at least one production raw material. Taking a certain target production raw material as an example, in each raster image, a suitable raster image whose suitable probability of the target production raw material is greater than a preset threshold is determined. Then, the regional spatial characteristics of the raster area corresponding to each raster image are determined. The regional spatial characteristics include geometric characteristics and land use type. Regional characteristics such as geometric characteristics (including the center coordinates of the raster area, the area of ​​the area, the perimeter of the area, the distance to the adjacent raster area, etc.) and land use type such as residential, green space, commercial land, etc. Then, based on the above regional spatial characteristics, each suitable raster image is spatially divided into regions using a preset clustering method, such as K-means clustering. For example, the raster areas corresponding to the closest suitable raster images are divided into a group. At the same time, land use type can also be considered during the regional division. Finally, the raster areas with the closest distance and the same land use type are converted into a group. In this way, at least one material suitable area can be determined for the target production raw material in the candidate suitable area.

[0080] 204. Based on the material suitable growth areas corresponding to each production raw material, determine the overlapping material suitable growth areas corresponding to each production raw material, and determine the overlapping material suitable growth areas as the suitable growth areas of the intangible cultural heritage project materials.

[0081] For the embodiment of the present invention, according to the method of step 203, at least one material suitable growth zone corresponding to each production raw material can be determined, and then overlapping material suitable growth zones are determined in each material suitable growth zone corresponding to each production raw material. For example, if the material suitable growth zones corresponding to production raw material a are respectively regions A, B, C, and D, the material suitable growth zones corresponding to production raw material b are respectively regions E, B, F, and G, and the material suitable growth zones corresponding to production raw material c are respectively regions H, B, I, and G, it can be seen that region B is the overlapping material suitable growth zone corresponding to production raw material a, production raw material b, and production raw material c, and thus region B is ultimately determined as the suitable growth zone for the intangible cultural heritage project material. By comprehensively considering each production raw material corresponding to the target intangible cultural heritage project to determine the suitable growth zone for the intangible cultural heritage project material, the coordinated constraints of the target intangible cultural heritage project's reliance on multiple production raw materials are fully considered, thereby improving the accuracy and comprehensiveness of the determination of the suitable growth zones for the intangible cultural heritage project material, and ensuring that the determined suitable growth zones are suitable for the survival needs of each production raw material forming the target intangible cultural heritage project. In another embodiment of the present invention, the raw materials required to create the target intangible cultural heritage item may include both biological and non-biological materials. If non-biological materials are present, the mineral resource distribution database can be used to determine the suitable growth areas for the non-biological materials. Regions where both biological and non-biological materials are suitable for growth are then determined as suitable growth areas for the intangible cultural heritage item.

[0082] Furthermore, when determining the suitable growth area of ​​the intangible cultural heritage project material, in order to eliminate regional noise and fill holes, the suitable growth area of ​​the overlapping material can be preprocessed. Based on this, the method includes: obtaining a preset cross structure element template, and determining the eroded binary image corresponding to the image of the suitable growth area of ​​the overlapping material, wherein the preset cross structure element template is composed of a central pixel as the origin, and the origin is extended by one pixel in the horizontal direction and the vertical direction, and the pixel values ​​of the central pixel and the extended pixel are both set to 1; any pixel point in the eroded binary image is respectively used as a pixel point to be eroded, and the central element of the preset cross structure element template is aligned with the pixel point to be eroded; it is judged whether the pixel values ​​of the pixel points in the eroded binary image covered by the position with a value of 1 in the aligned preset cross structure element template are all 1. If so, the pixel point to be eroded is determined as the first foreground image pixel point, otherwise the pixel point to be eroded is determined as the first foreground image pixel point. The method comprises the following steps: determining a pixel point as a first background image pixel point, and forming the overlapping material suitable area after the corrosion treatment by each pixel point of the first foreground image and each pixel point of the first background image; taking any pixel point in the dilated binary image corresponding to the overlapping material suitable area after the corrosion treatment as a pixel point to be expanded, and aligning the central element of the preset cross structure element template with the pixel point to be expanded; judging whether there is at least one 1 in the pixel values ​​of the pixel points in the dilated binary image covered by the position with a value of 1 in the aligned preset cross structure element template; if so, determining the pixel point to be expanded as a second foreground image pixel point; otherwise, determining the pixel point to be expanded as a second background image pixel point; forming the overlapping material suitable area after the expansion treatment by each pixel point of the second foreground image and each pixel point of the second background image; and determining the overlapping material suitable area after the expansion treatment as the suitable area for the intangible cultural heritage project material.

[0083] The preset cross structure element template is as follows:

[0084]

[0085] Specifically, to determine the binary image corresponding to the image of the suitable growth area of ​​the overlapping material, a corner pixel in the binary image can be used as a starting pixel, and each pixel in the binary image can be aligned with the central element in the preset cross structure element template in turn. If the pixel values ​​in the binary image covered by the position with a value of 1 in the preset cross structure element template are also 1, the pixel points aligned with the central element will be retained as the foreground, otherwise they will be set as the background. In this way, each pixel in the binary image can be set as the foreground or background according to the above method. After each pixel is set, the suitable growth area of ​​the overlapping material after corrosion treatment can be obtained. Furthermore, after the overlapping material suitable area is corroded, a corner pixel in the binary image of the overlapping material suitable area after the corrosion process is used as the starting pixel, and each pixel in the binary image is aligned with the central element in the preset cross structure element template in turn. If there is at least one 1 in the pixel value of the binary image covered by the position with a value of 1 in the preset cross structure element template, the pixel aligned with the central element is retained as the foreground, otherwise it is set as the background. Thus, according to the above method, each pixel in the binary image can be set as the foreground or background. After each pixel is set, the overlapping material suitable area after the expansion process can be obtained. The embodiment of the present invention can eliminate small objects, smooth boundaries, and disconnect objects by corroding the overlapping material suitable area. The expansion process can fill holes, connect broken areas, and expand object boundaries, thereby obtaining a suitable area for intangible cultural heritage project materials that meets the needs.

[0086] Furthermore, after determining the suitable habitat of the intangible cultural heritage project materials under the current environmental information, in order to permanently protect the intangible cultural heritage project materials, it is also necessary to predict the predicted environmental suitable habitat after a preset time in the future for each suitable habitat under the current environmental information. Based on this, the method includes: obtaining the predicted environmental information of each suitable habitat after the preset time, and based on the predicted environmental information, respectively determining the predicted suitable habitat probability corresponding to each grid image in the suitable area image of each suitable habitat; based on the predicted suitable habitat probability, respectively determining the predicted suitable habitat of the intangible cultural heritage project materials after the preset time in each suitable habitat; based on the predicted suitable habitat probability, In each of the suitable growth areas and its corresponding predicted suitable growth areas, the extent of reduction in the area of ​​each suitable growth area after the preset time is determined; based on the extent of reduction in the area of ​​the current suitable growth area where the intangible cultural heritage project material is located, it is judged whether it is necessary to recommend a suitable growth area for the intangible cultural heritage project material; if so, a recommended suitable growth area is determined in each of the suitable growth areas, and a recommended path from the current suitable growth area to the recommended suitable growth area is determined for the intangible cultural heritage project material; based on the recommended path, the intangible cultural heritage project material is recommended from the current suitable growth area to the recommended suitable growth area; otherwise, it is prohibited to recommend a suitable growth area for the intangible cultural heritage project material.

[0087] Among them, the preset time is set according to actual needs. Specifically, a large model or any other arbitrary method can be used to determine the predicted environmental information of each suitable area corresponding to the intangible cultural heritage project material after the preset time (the predicted environmental information is the environmental information that affects the survival of the intangible cultural heritage project material, such as environmental temperature, humidity, temperature difference and other information). Taking any one of the suitable areas as an example, the suitable area is divided into grid areas, and based on the predicted environmental information of each grid area after the preset time, the predicted suitable probability of the grid image corresponding to each grid area is calculated in the manner described in step 102, and the target grid image with a predicted suitable probability greater than the preset threshold is determined in each grid image, and each target grid image is spatially clustered, and the predicted suitable area corresponding to the suitable area after the preset time is obtained according to the spatial clustering result. Thus, according to the above method, it can be calculated. Calculate the predicted suitable area corresponding to each suitable area, and based on the area of ​​the suitable area and its corresponding predicted suitable area, determine the degree of reduction in the area of ​​the suitable area after a preset time. If the degree of reduction in the area of ​​the suitable area where the target intangible cultural heritage project material is currently located is greater than a preset degree threshold (the preset degree threshold is set according to actual needs), it is necessary to determine the suitable area with the smallest area reduction among all the suitable areas as the recommended suitable area, and set a recommended path for the target intangible cultural heritage project material from the current suitable area to the recommended suitable area, so as to migrate the target intangible cultural heritage project material from the current suitable area to the recommended suitable area based on the recommended path. If the degree of reduction in the area of ​​the current suitable area is less than or equal to the preset degree threshold, it means that the current suitable area is suitable for the long-term stable growth of the intangible cultural heritage project material, and therefore it can be omitted. In an embodiment of the present invention, a specific method for setting a recommended path includes: determining multiple candidate recommended paths from the current suitable area to the recommended suitable area, and based on the terrain data of the area where each candidate recommended path is located, determining the terrain slope and land use type of each candidate recommended path, as well as the slope resistance corresponding to the terrain slope and the land resistance corresponding to the land use type; determining the relative importance ratio of the terrain slope and the land use type to the recommended resistance, and based on the relative importance ratio, constructing a judgment matrix of the terrain slope and the land use type to the recommended resistance, and based on the judgment matrix, determining the resistance weight coefficient of the terrain slope and the land use type; based on the resistance weight coefficient, performing weighted summation on the slope resistance and the land resistance to obtain a comprehensive recommendation coefficient corresponding to each candidate recommended path, and based on the comprehensive recommendation coefficient, determining the recommended path of the intangible cultural heritage project material in each candidate recommended path.

[0088] The terrain data may be digital elevation model data; the land use types include industrial land, residential land, mountainous and hilly areas, coastal land, agricultural land, etc.; and the recommended resistance may be migration resistance.

[0089] Specifically, the terrain slope of each candidate recommended path is calculated using digital elevation model data, and the land use type is determined. The corresponding slope resistance is then determined based on the terrain slope, and the corresponding land resistance is determined based on the land use type. For example, the greater the slope, the greater the corresponding resistance, such as clay resistance being greater than sand resistance. The relative importance ratio of terrain slope and land use type to the recommended resistance is determined using multiple expert ratings or historical data (e.g., slope:land = 3:1). For example, 5-10 domain experts are organized to conduct independent ratings. Based on their experience, the experts determine the degree of influence of terrain slope and land use type on the recommended resistance. If the experts believe that the impact of terrain slope on resistance is significantly greater than that of land use type (scale 5), the ratio of land use type to terrain slope is 1 / 5. Based on the expert evaluation results, a judgment matrix is ​​then constructed. The judgment matrix is ​​shown below:

[0090]

[0091] Among them, a 12 is the relative importance ratio of terrain slope and land use type to the recommended resistance, a 21 =1 / a 12 . Further, the maximum eigenvalue of the judgment matrix and the eigenvector corresponding to the maximum eigenvalue are calculated, and the eigenvector is normalized to obtain a weight vector, that is, the resistance weight coefficient of the terrain slope and the land use type is obtained. Thereafter, the slope resistance and the land resistance are weighted and summed according to the resistance right coefficient to obtain the comprehensive recommendation coefficient corresponding to each candidate recommended path, and finally the path corresponding to the minimum comprehensive recommendation coefficient is selected as the recommended path. The embodiment of the present invention determines the recommended path by considering the path resistance, and can save the migration time and energy consumption of the intangible cultural heritage project materials by optimizing the path planning.

[0092] Furthermore, the production raw materials corresponding to different intangible cultural heritage projects may have overlapping suitable growth areas. It is necessary to set protection strategies for at least two intangible cultural heritage project materials with overlapping suitable growth areas to achieve balanced protection. Based on this, the method includes: based on the suitable growth areas of any two intangible cultural heritage project materials, determining the total number of pixels in the suitable growth areas and the number of overlapping pixels in the suitable growth areas corresponding to the suitable growth areas of the any two intangible cultural heritage project materials; determining the ratio of the number of overlapping pixels in the suitable growth areas to the total number of pixels in the suitable growth areas as the suitable growth area similarity between the any two intangible cultural heritage project materials, and generating protection strategy information for the any two intangible cultural heritage project materials based on the suitable growth area similarity.

[0093] Specifically, if the similarity between the two suitable zones exceeds a preset threshold (the preset threshold is set based on actual needs), the intangible cultural heritage materials of any two intangible cultural heritage items will be balanced and protected in the overlapping suitable zone. Otherwise, the intangible cultural heritage materials of any two intangible cultural heritage items will be protected in the overlapping suitable zone. This can achieve balanced protection for different intangible cultural heritage items and help build a sustainable intangible cultural heritage protection system.

[0094] According to another method for predicting suitable growth zones for intangible cultural heritage materials provided by the present invention, compared to the current method of determining the region where the intangible cultural heritage is inherited as the suitable growth zone for the corresponding production materials, the present invention determines the production materials of the target intangible cultural heritage project and selects candidate suitable growth zones. Then, based on the environmental information of the candidate suitable growth zones, the suitable growth probability of the production materials under each grid image in the candidate region image is determined. Based on the suitable growth probability, a suitable grid image is selected in each grid image, and at least one suitable growth zone corresponding to the intangible cultural heritage material is determined from each suitable grid image. That is, the present invention automatically determines the suitable growth zone of intangible cultural heritage materials by considering environmental information, which can improve the accuracy of determining the suitable growth zone of intangible cultural heritage materials. The suitable growth zones can achieve the effective reproduction of intangible cultural heritage materials, thereby improving the effective protection of intangible cultural heritage.

[0095] Further, as Figure 1 The specific implementation of the present invention provides a prediction device for the suitable growth area of ​​intangible cultural heritage project materials, such as Figure 3 As shown, the device includes: an acquisition unit 31, a first determination unit 32, and a second determination unit 33.

[0096] The acquisition unit 31 can be used to respond to the suitable growth zone prediction instruction of the intangible cultural heritage project material, obtain the raw materials for the material carrier required to form the target intangible cultural heritage project, and determine the candidate area image of the candidate suitable growth zone corresponding to the raw materials, as well as the environmental information that affects the raw materials under the candidate suitable growth zone.

[0097] The first determining unit 32 may be configured to determine, based on the environmental information, the applicability probability of the production raw material in each grid image in the candidate region image.

[0098] The second determination unit 33 can be used to select a suitable grid image in each of the grid images based on the suitable probability, and determine at least one suitable area corresponding to the intangible cultural heritage item material from each of the suitable grid images.

[0099] In a specific application scenario, the raw material is at least one; in order to determine at least one suitable area corresponding to the intangible cultural heritage project material, such as Figure 4 As shown, the second determination unit 33 includes a clustering module 331 and a determination module 332 .

[0100] The clustering module 331 can be used to take any one of the production raw materials as a target production raw material, determine a suitable grid image with a suitable probability greater than a preset threshold in each grid image based on the suitability probability of the target production raw material in each grid image in the candidate area image, and perform spatial clustering on each of the suitable grid images. According to the clustering results, determine at least one material suitable area for the target production raw material.

[0101] The determination module 332 can be used to determine the overlapping material suitable growth areas corresponding to each of the production raw materials based on the material suitable growth areas corresponding to each of the production raw materials, and determine the overlapping material suitable growth areas as the suitable growth areas of the intangible cultural heritage project materials.

[0102] In a specific application scenario, in order to determine that the suitable growth area of ​​overlapping materials is the suitable growth area of ​​intangible cultural heritage project materials, the determination module 332 can be specifically used to obtain a preset cross structure element template and determine the eroded binary image corresponding to the image of the suitable growth area of ​​overlapping materials, wherein the preset cross structure element template is composed of a central pixel as the origin, and the origin is extended by one pixel in the horizontal direction and the vertical direction respectively, and the pixel values ​​of the central pixel and the extended pixel are both set to 1; any pixel point in the eroded binary image is respectively used as a pixel point to be eroded, and the central element of the preset cross structure element template is aligned with the pixel point to be eroded; it is determined whether the pixel values ​​of the pixel points in the eroded binary image covered by the position with a value of 1 in the preset cross structure element template after alignment are all 1, and if so, the pixel point to be eroded is determined as the first foreground image pixel point, otherwise the pixel point to be eroded is determined as the first Background image pixel points, each of the first foreground image pixel points and each of the first background image pixel points constitute the overlapping material suitable area after corrosion processing; any pixel point in the expanded binary image corresponding to the overlapping material suitable area after corrosion processing is respectively used as a pixel point to be expanded, and the central element of the preset cross structure element template is aligned with the pixel point to be expanded; it is judged whether there is at least one 1 in the pixel values ​​of the pixel points in the expanded binary image covered by the position with a value of 1 in the aligned preset cross structure element template, and if so, the pixel point to be expanded is determined as a second foreground image pixel point, otherwise, the pixel point to be expanded is determined as a second background image pixel point, and each of the second foreground image pixel points and each of the second background image pixel points constitute the overlapping material suitable area after expansion processing; the overlapping material suitable area after expansion processing is determined as the suitable area of ​​intangible cultural heritage project materials.

[0103] In a specific application scenario, in order to determine the probability of occurrence of each raster image, the first determining unit 32 may be used to determine the raster environment information f corresponding to each raster image z in the environment information. i (z), and respectively determine each of the grid environment information f i (z) corresponding weight coefficient λ i Based on each of the grid environment information f i (z) and its corresponding weight coefficient λ i , determine the appropriate generation probability p(z) corresponding to each of the grid images z, Wherein, n is the number of grid environment information, i is the identifier of each of the grid environment information, and a is a normalization constant.

[0104] In a specific application scenario, in order to recommend a suitable area, the device further includes: a recommendation unit 34.

[0105] The recommendation unit 34 can be used to obtain the predicted environmental information of each suitable area after a preset time, and based on the predicted environmental information, determine the predicted suitability probability corresponding to each grid image in the suitable area image of each suitable area; based on the predicted suitability probability, determine the predicted suitable area of ​​the intangible cultural heritage project material after the preset time in each suitable area; based on each suitable area and its corresponding predicted suitable area, determine the degree of reduction in the area of ​​each suitable area after the preset time; based on the degree of reduction in the area of ​​the current suitable area where the intangible cultural heritage project material is located, judge whether it is necessary to recommend a suitable area for the intangible cultural heritage project material; if so, determine a recommended suitable area in each suitable area, and determine a recommended path from the current suitable area to the recommended suitable area for the intangible cultural heritage project material; based on the recommended path, recommend the intangible cultural heritage project material from the current suitable area to the recommended suitable area; otherwise, prohibit the recommendation of a suitable area for the intangible cultural heritage project material.

[0106] In a specific application scenario, in order to determine the recommended path from the current suitable area to the recommended suitable area, the recommendation unit 34 can be specifically used to determine multiple candidate recommended paths from the current suitable area to the recommended suitable area, and based on the terrain data of the area where each candidate recommended path is located, determine the terrain slope and land use type of each candidate recommended path, as well as the slope resistance corresponding to the terrain slope and the land resistance corresponding to the land use type; determine the relative importance ratio of the terrain slope and the land use type to the recommended resistance, and based on the relative importance ratio, construct a judgment matrix of the terrain slope and the land use type to the recommended resistance, and based on the judgment matrix, determine the resistance weight coefficient of the terrain slope and the land use type respectively; based on the resistance weight coefficient, perform weighted summation on the slope resistance and the land resistance to obtain the comprehensive recommendation coefficient corresponding to each candidate recommended path, and based on the comprehensive recommendation coefficient, determine the recommended path of the intangible cultural heritage project material in each candidate recommended path.

[0107] In a specific application scenario, in order to obtain the raw materials for the material carrier required to form the target intangible cultural heritage project, the acquisition unit 31 includes a carrier prediction module 311 and a material prediction module 312.

[0108] The carrier prediction module 311 can be used to obtain the descriptive text information of the target intangible cultural heritage item, search for supplementary corpus information whose similarity with the descriptive text information is greater than a preset similarity threshold in a preset corpus, and input the descriptive text information and the supplementary corpus information into a large model with a sequence annotation header added to perform carrier prediction, so as to obtain the material carrier required to form the target intangible cultural heritage item.

[0109] The material prediction module 312 can be used to obtain material prediction prompt information, input the material prediction prompt information and the material carrier into a preset material prediction model to perform material prediction, and obtain the raw materials for making the material carrier, wherein the preset material prediction model is pre-constructed based on a sample material carrier data set with a production material label.

[0110] It should be noted that for other corresponding descriptions of the functional modules involved in the prediction device for the suitable growth area of ​​intangible cultural heritage materials provided in the embodiment of the present invention, please refer to Figure 1 The corresponding description of the method shown will not be repeated here.

[0111] Based on the above Figure 1The method shown, accordingly, an embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the following steps are implemented: in response to the suitable growth area prediction instruction of the intangible cultural heritage project material, the production raw materials of the material carrier required to form the target intangible cultural heritage project are obtained, and the candidate area image of the candidate suitable growth area corresponding to the production raw materials, as well as the environmental information under the candidate suitable growth area that affects the production raw materials; based on the environmental information, the suitable growth probability of the production raw materials under each grid image in the candidate area image is determined; based on the suitable growth probability, a suitable growth grid image is selected in each of the grid images, and at least one suitable growth area corresponding to the intangible cultural heritage project material is determined by each of the suitable growth grid images.

[0112] Based on the above Figure 1 The method shown and Figure 3 The embodiment of the device shown in the figure, the embodiment of the present invention also provides a physical structure diagram of a computer device, such as Figure 5 As shown, the computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor, wherein the memory 42 and the processor 41 are both arranged on a bus 43. When the processor 41 executes the program, the following steps are implemented: in response to a suitable zone prediction instruction for intangible cultural heritage project materials, raw materials for forming the material carrier required for the target intangible cultural heritage project are obtained, and candidate area images of candidate suitable zones corresponding to the raw materials are determined, as well as environmental information affecting the raw materials under the candidate suitable zones; based on the environmental information, the suitable probability of the raw materials under each grid image in the candidate area images is determined; based on the suitable probability, a suitable grid image is selected in each grid image, and at least one suitable zone corresponding to the intangible cultural heritage project material is determined by each suitable grid image.

[0113] The technical solution of the present invention determines the raw materials for the target intangible cultural heritage item and selects candidate suitable growth areas. Based on the environmental information of the candidate suitable growth areas, the method then determines the probability of the raw materials being suitable for each grid image in the candidate region image. Based on the suitable growth probabilities, a suitable grid image is selected within each grid image, and at least one suitable growth area corresponding to the intangible cultural heritage item material is determined from each suitable grid image. Specifically, the present invention automatically determines the suitable growth areas for intangible cultural heritage item materials by considering environmental information, thereby improving the accuracy of determining the suitable growth areas for intangible cultural heritage item materials. The suitable growth areas enable the effective reproduction of intangible cultural heritage item materials, thereby enhancing the effective protection of intangible cultural heritage items.

[0114] Obviously, those skilled in the art will appreciate that the various modules or steps of the present invention described above can be implemented using a general-purpose computing device, centralized on a single computing device, or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. In some cases, the steps shown or described can be performed in a different order than that shown, or can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0115] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for predicting the suitable growth area of ​​intangible cultural heritage materials, characterized in that: include: In response to the suitable growth zone prediction instruction for the intangible cultural heritage project material, the raw materials for forming the material carrier required for the target intangible cultural heritage project are obtained, and candidate region images of candidate suitable growth zones corresponding to the raw materials are determined, as well as environmental information in the candidate suitable growth zones that affects the raw materials; Based on the environmental information, determining the probability of the production raw material being suitable for each grid image in the candidate area image; Based on the suitable growth probability, a suitable growth grid image is selected from each of the grid images, and at least one suitable growth area corresponding to the intangible cultural heritage item material is determined by each of the suitable growth grid images.

2. The method according to claim 1, characterized in that The production raw material is at least one; The method of selecting a suitable growth grid image from each of the grid images based on the suitable growth probability, and determining at least one suitable growth area corresponding to the intangible cultural heritage item material from each of the suitable growth grid images, comprises: Taking any one of the raw materials as a target raw material, determining a suitable grid image having a suitable growth probability greater than a preset threshold in each grid image based on the suitable growth probability of the target raw material in each grid image in the candidate region image, performing spatial clustering on each of the suitable grid images, and determining at least one material suitable region for the target raw material according to the clustering result; Based on the material suitable growth areas corresponding to each of the production raw materials, the overlapping material suitable growth areas corresponding to each of the production raw materials are determined, and the overlapping material suitable growth areas are determined as the suitable growth areas of the intangible cultural heritage project materials.

3. The method according to claim 2, characterized in that The suitable growth areas of the overlapping materials are determined as the suitable growth areas of the intangible cultural heritage project materials, including: Obtaining a preset cross structuring element template and determining a corrosion binary image corresponding to the image of the suitable area of ​​the overlapping material, wherein the preset cross structuring element template is composed of a central pixel as an origin and one pixel extended in the horizontal direction and the vertical direction of the origin, and the pixel values ​​of the central pixel and the extended pixels are both set to 1; Taking any pixel point in the eroded binary image as a pixel point to be eroded, and aligning the central element of the preset cross structure element template with the pixel point to be eroded; Determine whether the pixel values ​​of the pixels in the eroded binary image covered by the positions with a value of 1 in the aligned preset cross structuring element template are all 1; if so, determine the pixel to be eroded as a first foreground image pixel; otherwise, determine the pixel to be eroded as a first background image pixel, and each first foreground image pixel and each first background image pixel constitute the overlapping material suitable area after the erosion process; Any pixel point in the expanded binary image corresponding to the suitable area of ​​the overlapping material after the corrosion process is used as a pixel point to be expanded, and the central element of the preset cross structure element template is aligned with the pixel point to be expanded; Determining whether there is at least one 1 in the pixel values ​​of the pixels in the dilated binary image covered by the position with a value of 1 in the aligned preset cross structuring element template; if so, determining the pixel to be dilated as a second foreground image pixel; otherwise, determining the pixel to be dilated as a second background image pixel, and each second foreground image pixel and each second background image pixel forming the overlapping material suitable area after dilation; The suitable growth area of ​​the overlapping materials after the expansion treatment is determined as the suitable growth area of ​​the intangible cultural heritage project materials.

4. The method according to claim 1, wherein The determining, based on the environmental information, the probability of the production raw material being suitable for each grid image in the candidate area image includes: Determine the grid environment information f corresponding to each grid image z in the environment information i (z), and respectively determine each of the grid environment information f i (z) corresponding weight coefficient λ i ; Based on each of the grid environment information f i (z) and its corresponding weight coefficient λ i , determine the appropriate generation probability p(z) corresponding to each of the grid images z, Wherein, n is the number of grid environment information, i is the identifier of each of the grid environment information, and a is a normalization constant.

5. The method according to claim 1, wherein After determining at least one suitable area corresponding to the intangible cultural heritage item material from each of the suitable grid images, the method further includes: Acquire predicted environmental information of each of the suitable areas after a preset time, and determine the predicted suitable probability corresponding to each grid image in the suitable area image of each of the suitable areas based on the predicted environmental information; Based on the predicted suitable growth probability, determining the predicted suitable growth area of ​​the intangible cultural heritage item material after the preset time in each suitable growth area; Based on each of the suitable growth areas and its corresponding predicted suitable growth area, determining the extent of reduction in area of ​​each of the suitable growth areas after the preset time; Based on the degree of reduction in the area of ​​the current suitable zone where the intangible cultural heritage project materials are located, determine whether it is necessary to recommend a suitable zone for the intangible cultural heritage project materials; if so, determine a recommended suitable zone in each of the suitable zones, and determine a recommended path from the current suitable zone to the recommended suitable zone for the intangible cultural heritage project materials; based on the recommended path, recommend the intangible cultural heritage project materials from the current suitable zone to the recommended suitable zone; otherwise, it is prohibited to recommend a suitable zone for the intangible cultural heritage project materials.

6. The method according to claim 5, characterized in that Determining a recommended path from the current suitable growth area to the recommended suitable growth area for the intangible cultural heritage item material includes: Determining a plurality of candidate recommended paths from the current suitable habitat area to the recommended suitable habitat area, and determining, based on terrain data of an area in which each candidate recommended path is located, a terrain slope and a land use type, as well as a slope resistance corresponding to the terrain slope and a land resistance corresponding to the land use type for each candidate recommended path; Determining a relative importance ratio of the terrain slope and the land use type to the recommended resistance, and constructing a judgment matrix of the terrain slope and the land use type to the recommended resistance based on the relative importance ratio, and determining resistance weight coefficients of the terrain slope and the land use type respectively based on the judgment matrix; Based on the resistance weight coefficient, the slope resistance and the land resistance are weighted and summed to obtain a comprehensive recommendation coefficient corresponding to each candidate recommended path, and based on the comprehensive recommendation coefficient, the recommended path of the intangible cultural heritage project material is determined in each candidate recommended path.

7. The method according to claim 1, characterized in that The process of obtaining the raw materials for producing the material carrier required for forming the target intangible cultural heritage item includes: Obtaining descriptive text information of the target intangible cultural heritage item, searching a preset corpus for supplementary corpus information whose similarity to the descriptive text information is greater than a preset similarity threshold, and inputting the descriptive text information and the supplementary corpus information into a large model with a sequence annotation header for carrier prediction, thereby obtaining a material carrier required to form the target intangible cultural heritage item; Obtain material prediction prompt information, input the material prediction prompt information and the material carrier into a preset material prediction model for material prediction, and obtain the raw materials for making the material carrier, wherein the preset material prediction model is pre-constructed based on a sample material carrier data set with a production material label.

8. A device for predicting the suitable growth area of ​​intangible cultural heritage materials, characterized by: include: an acquisition unit, configured to, in response to a suitable growth zone prediction instruction for intangible cultural heritage project materials, acquire raw materials for forming a material carrier required for a target intangible cultural heritage project, and determine candidate region images of candidate suitable growth zones corresponding to the raw materials, as well as environmental information in the candidate suitable growth zones that affects the raw materials; A first determining unit is configured to determine, based on the environmental information, a probability of suitability of the production raw material under each grid image in the candidate area image; The second determining unit is used to select a suitable grid image in each of the grid images based on the suitable probability, and determine at least one suitable area corresponding to the intangible cultural heritage item material from each of the suitable grid images.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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