9 results about "Geographic distribution" patented technology

A method for estimating glacial meltwater runoff is disclosed, comprising the following steps: S1, obtaining glacier geographical distribution information and calculating driving data; S2, simulating glacier ablation; S3, calculating glacial meltwater runoff. A relatively accurate glacial meltwater runoff estimation model is established, solving the problem of significant uncertainty in existing meltwater runoff estimation methods, and is able to simulate the changing characteristics of each glacier.

The application discloses a bird chirp sound recognition method based on a combination of voiceprints and spatial distribution, and belongs to the technical field of intelligent sound classification and recognition. In view of the problems of ignoring geographical distribution prior knowledge and sample imbalance in the prior art, the application firstly constructs a voiceprint recognition model: a training data set is constructed by audio preprocessing, logarithmic mel spectrum and dynamic difference feature extraction, a model is trained based on DenseNet-121 by adopting a two-stage training strategy, and recognition confidence of each species is obtained; meanwhile, a spatial distribution model is constructed: based on public observation data, an average observer ability index is used to correct an original encounter rate, and spatial distribution probability of the species in a specific city is obtained; finally, a Sigmoid function is used to perform nonlinear fusion on the two, a joint recognition probability is calculated, and a classification result is output. The application introduces ecological spatial constraints into the recognition decision, effectively reduces false positive misjudgment, improves rare species monitoring capability, and makes the recognition result have ecological interpretability.

The present invention relates to "A process for the production of whitefish from Pátzcuaro (Chirostoma estor) and balanced diets for its growth and fattening." These diets have specific characteristics for this species, with a content of easily digestible protein ingredients that efficiently contribute to larval survival and the size and weight of the juveniles fed in aquaculture farms with the appropriate diet for each stage. These diets can enter the national and international markets due to their unique characteristics and the results obtained with stomachless fish. Additionally, these feeds can be used for the production of species at a lower level of the food chain, which do not require the use of fishmeal and fish oil, making the aquaculture of these species a more sustainable activity.These diets are the first developed specifically for the successful growth and fattening of the species C. estor, "Pátzcuaro whitefish", having the potential to impact its conservation and marketing in the region of geographic distribution.

The application discloses a mountain and hilly biomass collection, storage and transportation collaborative scheduling method and system based on multi-agent game, relates to the technical field of wisdom agriculture and supply chain collaboration, and aims to solve the problems of unbalanced benefit distribution, ignored terrain constraints and rigid collaborative mechanism in the prior art. The application first acquires static attribute data, dynamic operation data of the collection and storage nodes, and geographical distribution and resource quantity of all resource points of the biomass to be collected and transported; determines the dispersion degree of the geographical distribution of all resource points, the balance degree of the resource quantity, and the difference degree of the appeals of the benefit related parties; takes the dispersion degree, the balance degree, the static attribute data of each collection and storage node and the difference degree of the appeals as judgment indexes, determines the collaborative mode of the benefit related parties according to a preset judgment mechanism, executes collaborative planning, and completes dynamic planning of the collection path and the corresponding resources; and finally realizes dynamic allocation of resources.

The present application relates to the technical field of data engineering, and particularly relates to a method and device for customized construction of a sample library of map patches, equipment and a storage medium, the present application first analyzes user demand, matches the semantic category corresponding to the demand with an authoritative geographical classification system, and screens a standard geographical category in combination with a geographical distribution knowledge base; then calculates the distribution density and area proportion of vector plot data in a target region on the standard category, evaluates a sampling priority, and finally extracts and combines sample units from remote sensing images and vector data according to the evaluation result to form a sample library of map patches. The present application ensures that the semantic category of the sample is clear and consistent with the actual regional geography through semantic analysis and geographical knowledge verification, and improves the accuracy and practicality of the sample. The priority is evaluated based on the spatial distribution characteristics and hierarchical sampling is implemented, so that the sample collection is concentrated in the key area with rich information, and the method realizes the automated construction of a high-quality sample library from user demand.

This invention discloses an intelligent self-rescue system for marine jellyfish stings, relating to the field of first aid technology for biological injuries. This invention establishes a basic concept popular science system by integrating information on the species, habits, geographical distribution, and hazards of marine organisms to prevent marine organism injuries. It also integrates the clinical manifestations and treatment plans for injuries caused by venomous marine organisms, establishing a training system for treatment skills to aid in the preliminary identification of injury types and improve treatment skills. Furthermore, it integrates relevant data to compile a first aid guidebook and presents relevant medicines and equipment in a modular format for on-site emergency treatment. This effectively addresses the shortcomings and deficiencies in current marine organism injury treatment. Based on the epidemiological characteristics and treatment consensus of marine jellyfish stings, it improves the awareness, treatment skills, and on-site emergency treatment efficiency of potentially high-risk groups and medical personnel regarding marine jellyfish stings, reducing the risk of aggravated injury and mortality from jellyfish stings.

The application discloses a basin and peripheral region digital modeling method and system based on big data analysis, relates to the technical field of digital modeling, and comprises the following steps: connecting a GIS system to acquire geographical distribution information of a target basin region; building a digital space, performing grid division on the digital space, and determining a digital grid; collecting detection data of each exploration zone in the target basin region, respectively performing data interpretation and preprocessing, and determining geological feature information; based on the digital grid, combining the geological feature information, performing three-dimensional modeling on each digital grid in parallel, and respectively determining a grid model; splicing the grid models, determining a digital basin peripheral model, performing macro-quantization, and generating a macro-digital basin peripheral model. The application solves the technical problem of low modeling and model construction efficiency of the existing technology in the joint modeling of a basin and a peripheral orogenic belt, and achieves the technical effect of improving the efficiency and accuracy of exploration and analysis of a basin and a peripheral region.

The application discloses a kind of based on GIS and MaxEnt prediction plant disease and insect pest suitable area method, comprising the following steps: S1: the natural geographical distribution point data of the target disease and insect pest is obtained;S2: the environmental climate dataset under current and future climate conditions is obtained;S3: the biological climate variable screened in environmental climate dataset is obtained;S4: the main biological climate variable that influences the target disease and insect pest distribution is calculated and analyzed using MaxEnt model;S5: using ArcGIS software obtains the suitable area prediction graph of the target disease and insect pest under current and future climate scenarios;The beneficial effects of the application are to provide a kind of comprehensive prediction method combining modern GIS technology and advanced MaxEnt model;Second, it can better understand and predict the distribution change of disease and insect pest under different climate scenarios;Three is, the application of the application helps to improve agricultural production efficiency, reduce the loss caused by disease and insect pest.

The application discloses a kind of injection well mouth injection pressure monitoring evaluation methods, comprising: based on target and adjacent injection well multipoint pressure real-time acquisition, utilize geographic distribution label to realize cross well pressure data coupling, after data missing correction, multistage noise reduction and normalization, extract pressure fluctuation characteristics, and input self-evolution multi-label clustering model automatically induces dominant pressure mode, generates benchmark template that is dynamically updated with working condition;Through real-time pressure trend and benchmark template distribution label comparison, determine pressure fluctuation consistency and implement collaborative anomaly tracing analysis for significant deviation, identify abnormal cause type in combination with historical drift and noise characteristics, automatically optimize detection threshold, generate machine-readable anomaly tracing report and assist operation and maintenance decision;Online sample continuous learning mechanism guarantees the adaptability and diagnostic accuracy of model under different working conditions, the application improves the intelligentization, robustness and abnormal response efficiency of injection well area pressure monitoring.