255 results about "Proportional Stratified Sampling" patented technology

The invention discloses an intelligent recommendation method for optimizing advertisement keyword combination through cross validation, and relates to the technical field of advertisement technology and search engine marketing, which comprises the following steps: constructing a heterogeneous data set through multi-modal data fusion, and layering according to data sparseness: training a Transform-XL time sequence model by adopting time cross validation of a dynamic K value in a high resource layer; a graph neural network association graph is introduced into a low resource layer, semantic expression of a long tail word is enhanced, a stratified sampling-transfer learning two-channel mechanism is designed, and the generalization ability is improved in combination with exposure frequency weighting and a parameter freezing strategy; developing a Bayesian fusion engine, and dynamically weighting a high / low resource layer prediction result by using an improved Materon kernel function Gaussian process; and generating a confidence interval based on neural quantile regression, and outputting an optimal keyword combination sequence under ROI-risk-diversity constraint in combination with multi-target Pareto optimization. According to the method, the cold start efficiency and the long-tail resource utilization rate are improved, and high-robustness decision support is provided for advertisement putting.

The invention provides an artificial intelligence auxiliary antenna design method based on a Gaussian regression process, and the method comprises the steps: employing a script interface to interact with a simulation platform, automatically completing the parameterized modeling process of an antenna model, and setting an excitation condition and a radiation boundary; a multi-dimensional space stratified sampling method is adopted to generate a uniformly distributed sample point set in the multi-dimensional parameter space, and electromagnetic simulation is carried out; preprocessing the data output by simulation to form a data structure suitable for machine learning model processing; integrating the trained MLNN model into a grey wolf optimization algorithm, and optimizing antenna design parameters; and performing electromagnetic simulation on the optimal parameter obtained by optimization, comparing a prediction result with actual simulation data, and verifying the performance of the optimization engine in the target frequency band. According to the method, the problems of insufficient sample generation efficiency, insufficient parameter sensitivity analysis, limited model generalization ability, low convergence speed of an optimization algorithm and the like in the prior art can be solved.

The invention relates to the field of water resource quality detection, in particular to a sampling device for water resource quality detection. The invention provides a water resource quality detection sampling device which comprises a sampling barrel, a barrel cover is arranged at an opening of the sampling barrel, clamping seats are symmetrically distributed on one side, close to the barrel cover, of the sampling barrel, clamping pins are arranged in the clamping seats, the barrel cover is locked through cooperation of the clamping pins and the clamping seats, and the sampling barrel is connected with the clamping seats. A plurality of sampling box bodies for containing water samples are vertically arranged in the sampling barrel, a water pump is arranged in the sampling barrel, and a water inlet pipe of the water pump extends to the outer side of the sampling barrel. The stratified sampling box body and the independent flow guide assembly are combined with the servo motor to drive the staggered box cover, so that accurate stratified collection of water samples at different depths is realized, and mixed pollution is avoided; a water flow switching assembly is additionally arranged, a pipeline is automatically flushed after sampling, a residual water sample is discharged into a liquid storage box, cross contamination is reduced, independence and representativeness of the water sample are guaranteed, and detection accuracy is improved.

The invention belongs to the technical field of geological exploration, particularly relates to a high-adaptability multi-type geological exploration sampling device and an accurate sampling method.The high-adaptability multi-type geological exploration sampling device and the accurate sampling method aim to solve the problems that a drill bit is stuck and stratified sampling is difficult, and the high-adaptability multi-type geological exploration sampling device comprises a base, a vertical plate, a lifting plate and a driving cylinder with the drill bit; a first annular groove is formed in the outer wall of the driving cylinder and matched with the first circular ring, downward-pressing drilling and upward-lifting resetting of the drill bit are achieved, a second annular groove is formed in the drill bit, and the flow direction of hydraulic oil is controlled through a second circular ring connected with a fixing rod; during lifting, hydraulic oil is injected into the second hydraulic channel, the trapezoidal collecting box extends out to scrape hole wall samples, the electromagnet and the iron block are matched to adjust the position of the second circular ring, the working states of the teeth and the collecting box are switched, drill bit jamming is reduced, hole wall sampling at any depth is supported, and exploration efficiency is improved.

The invention provides a UWB-NLOS identification and distance measurement correction method based on a DEA-PSO hybrid optimization Iight GBM algorithm, and the method comprises the following steps: 1, building multi-dimensional features after data stratified sampling, obtaining an HCNLOS data set through two times of label screening, and generating initial positioning; step 2, adopting a DEA-PSO hybrid optimization algorithm to realize LightGBM hyper-parameter automatic adjustment and optimization, and improving parameter adjustment efficiency through dynamic fitness evaluation and collaborative search; 3, constructing a classification model and a regression model in parallel; and 4, fusing the corrected NLOS data and the original LOS / HCNLOS data, and outputting a high-precision coordinate through a positioning algorithm, thereby effectively improving the positioning robustness in a complex environment.

The invention discloses a lake and reservoir inflow and outflow scheduling scheme optimization method and system based on a three-dimensional hydrodynamic force-water quality-water ecological model, and the method comprises the steps: firstly constructing a three-dimensional hydrodynamic force-water quality-water ecological model of a target lake and reservoir, setting a scheduling constraint, a scoring constraint, a scoring single item, and a comprehensive scoring weight by a decision maker, stratified sampling and one-dimensional uniform random sampling are carried out on each flow range of a water replenishing port, a flow outlet and a water suction pump station which can be regulated and controlled manually according to scheduling constraints set by a decision maker, and a plurality of inflow and outflow scheduling schemes are generated; and performing big data mining on the model calculation results of all the access flow scheduling schemes, performing comprehensive scoring according to the scoring single item and the comprehensive scoring weight, and selecting the access flow scheduling scheme with the highest comprehensive score as an optimal scheduling scheme for recommendation. The method has the advantages of high simulation precision, flexible decision support, multi-target comprehensive balance and the like, and a scientific and efficient technical solution can be provided for lake and reservoir inflow and outflow scheduling.

The invention belongs to the technical field of underground water sampling equipment, and discloses an efficient underground water stratified sampling device which comprises a frame, the frame is provided with an operation table and a lifting device, the lifting device is connected with a plurality of groups of sampling devices in the height direction, each sampling device comprises a sampling barrel, and a plurality of water inlets are formed in the sampling barrels in the circumferential direction; the sampling barrel is rotationally connected with a plurality of rotating plates in the circumferential direction, the rotating plates are in one-to-one correspondence with the water inlets, and the rotating plates are fixedly connected with telescopic push-pull rods; a driving assembly is arranged at the top of the sampling barrel, is rotationally connected with the free end of the push-pull rod and is used for driving the push-pull rod to rotate in the direction close to or away from the sampling barrel; one side, close to the outer side wall of the sampling barrel, of the rotating plate is connected with a sealing element; the operation table is provided with a controller used for controlling the driving assembly to work. The problems that an existing water taking device is prone to causing cross mixing of water bodies at different depths, the sampling efficiency is low, and a water inlet is prone to being blocked are solved.

The invention relates to the technical field of water quality detection, in particular to a high-precision water quality stratified sampling device which comprises a main body, a plurality of fixing plates are arranged at the top of the inner side of the main body, a plurality of mounting cabins and a control mechanism are uniformly arranged on the outer wall of the circumference of the main body, and the control mechanism is arranged between the fixing plates. The control mechanism comprises a fixing shell fixedly connected with the inner wall of the fixing plate, a speed reducer is arranged at the bottom of the fixing shell, a rope disc is rotationally connected into the fixing shell, the input end of the top end of the speed reducer is fixedly connected with the bottom of the rope disc, and the output end of the bottom of the speed reducer is fixedly connected with a butt joint rod and a sampling mechanism. High-precision stratified sampling is realized through close cooperation of the control mechanism and the sampling mechanism. The rope disc is driven by a water body to rotate and drives the butt joint rod through the speed reducer, the pressing face of the butt joint rod acts on the butt joint face of the check block, opening and closing of a water inlet of the water taking box are accurately controlled, and accurate sampling is conducted on different water layers according to needs.

The embodiment of the invention discloses a stable adsorption configuration global search method based on similarity distribution and active learning. The method comprises the following steps: S1, constructing a knowledge-embedded high-throughput adsorption structure model; s2, constructing an adsorption structure small sample data set based on clustering stratified sampling; s3, in combination with the adsorption structure small sample data set and the Gaussian process regression model, establishing an adsorption energy prediction-oriented proxy model; and S4, training the proxy model, and searching a stable adsorption configuration. The embodiment of the invention discloses a stable adsorption configuration global search method based on similar distribution and active learning. By means of catalytic configuration high-throughput modeling containing knowledge embedding, small sample data set construction based on clustering stratified sampling, a small sample recommendation model based on Gaussian process regression and hybrid convergence criteria considering data distribution and agent model prediction, efficient searching of a stable adsorption configuration in a large structure space is achieved.

The invention discloses stratified sampling equipment for land engineering investigation and a sampling method of the stratified sampling equipment, and belongs to the technical field of land engineering investigation. The device comprises a fixing plate, the lower side of the fixing plate is rotationally connected with a threaded rod, the outer side of the threaded rod is in threaded connection with two threaded cylinders, the outer sides of the threaded cylinders are fixedly connected with mounting plates, a rotating cylinder is jointly rotationally connected between the two mounting plates, and a plurality of stop rods slidably penetrate through the interior of the rotating cylinder; the lower side of the fixing plate is fixedly connected with a motor, and the output end of the motor is fixedly connected with a rotating shaft. According to the invention, the whole device is firstly placed in an excavated sampling point, the cutting plate is opposite to a soil layer to be sampled, and then the motor is started, so that the sampling operation can be automatically carried out, the workload of workers is reduced, the operation is simple, and the working efficiency is relatively high.

The invention discloses an expert matching method based on structured data, and the method comprises the following steps: firstly, calculating the objective weight and subjective weight of each result index through information and a Delphi method based on the structured data in a database, and generating an expert comprehensive academic score; then, keyword information input by a front end is obtained, the matching degree of keywords and expert fields is calculated by adopting a word frequency-inverse document frequency algorithm, and experts are grouped according to the matching degree; and finally, according to the scale of the expert database and the number of persons to be extracted, adaptively selecting a random extraction or hierarchical distribution extraction mode to determine a target expert. According to the method, through a dynamic weight calculation model and an intelligent stratified sampling mechanism, the accuracy and flexibility of expert matching are realized, the score is continuously optimized in combination with the historical participation performance data of the experts, and the scientificity and practicability of expert extraction are improved.

The invention discloses a grain depot intelligent sampling quality inspection system and method, and relates to the technical field of intelligent grain depot detection, and the method comprises the steps: collecting environment data, three-dimensional point cloud data and surface acoustic wave group velocity data, and carrying out the inversion calculation through a Love wave equation, and obtaining a three-dimensional density distribution diagram; calculating the density gradient in the vertical direction according to the three-dimensional density distribution diagram to obtain a stratified sampling parameter table; according to the stratified sampling parameter table, stratified puncturing is conducted on the grain pile, actual sampling depth data are generated, and a three-way sample valve is used for conducting sample distribution detection on the actual sampling depth data. Through layered detection of the three-way sample valve and near-infrared X-ray combined analysis, accurate detection of moisture, protein and heavy metal content is realized, and a detection result is matched with a density distribution diagram through a constrained Kriging interpolation method to generate a quality safety index.

The invention belongs to the technical field of soil sampling, and particularly relates to a grain planting soil detecting and sampling device which comprises a base, a supporting column is fixedly arranged on one side of the base, a top plate is fixedly arranged on the supporting column, a driving mechanism and a stratified sampling mechanism are arranged on the top plate, and a soil sample storage mechanism is arranged on the base. The stratified sampling mechanism comprises a sampling drill rod assembly and a pressure difference sampling assembly, the pressure difference sampling assembly is installed on the top plate, and the sampling drill rod assembly is located below the top plate and connected with the pressure difference sampling assembly; by combining the pressure difference principle with the longitudinally-arranged temporary storage cavities, soil of different depths can be collected in a layered mode in one-time sampling operation, after the soil is collected, the soil of different depths is sprayed into the corresponding sample receiving plates to be stored according to the pressure difference principle again, sample mixing is effectively avoided, accurate layered sampling is achieved, and the sampling efficiency is improved. And the collected soil sample is kept in an original state.

The utility model relates to the field of sewage sampling, and discloses a sewage detection stratified sampling device, which comprises three sampling buckets, a support column and a sliding rod, the sampling buckets are internally provided with mounting cavities, the middle part of the support column is provided with a sliding chute, and the sliding rod slides in the sliding chute. The lower ends of the supporting columns penetrate through the sampling barrel and extend out of the sampling barrel, a plurality of sliding cavities are formed in the two sides, close to the sampling barrel, of the middle of the outer wall of a supporting column rod body, and connecting rods are fixedly connected to the two sides, close to the sampling barrel, of the middle of the outer wall of a sliding rod body. According to the stratified sampling device, when the stratified sampling device is used for sampling sewage, the stratified sampling device is in threaded connection with the filter screen on the outer wall of the threaded pipe, water plants, floating objects or other garbage in a sampling water area can be effectively prevented from blocking the water taking hole, the sampling process is ensured to be smoothly carried out, and in addition, the threaded connection mode is convenient to mount and dismount and simple and convenient to operate. And when the filter screen needs to be replaced or equipment needs to be maintained, a worker can quickly finish operation, so that the maintenance cost is reduced.

The invention provides a complex industrial contract information extraction method and system based on a large language model, and the method comprises the steps: S1, carrying out the clustering analysis of different obtained industrial contract texts, and determining a cluster where each contract text is located; s2, stratified sampling is carried out on each cluster, and representative samples are obtained; s3, carrying out key content extraction meeting a preset requirement on the representative sample corresponding to each cluster; obtaining a corresponding structured text based on the extracted key content meeting the preset requirement; s4, labeling the structured text to obtain labeled data; step S5, acquiring annotation data of all clusters to generate an annotation data set, and performing fine tuning on the large language model by using the annotation data set to obtain a fine-tuned large language model; and S6, deploying the fine-tuned large language model into a production environment, and extracting key information, meeting a preset requirement, of the unlabeled contract text.

The invention discloses a protein mutation stability change prediction method based on an integrated convolutional neural network model and regression hierarchical training, and belongs to the technical field of protein stability change prediction. Firstly, a training set and a test set are constructed, and four data sets are collected and arranged. The method comprises the following four steps: 1, performing enhancement processing on data based on antisymmetry, and balancing and training stable and unstable abrupt sample data in a set; 2, extracting protein characteristics; 3, training the model by adopting a regression stratified sampling strategy; and 4, constructing an integrated model based on a plurality of CNN sub-models for predicting the stability change of the protein mutation. Spatial neighbor evolution information is introduced for the first time; a regression stratified sampling strategy is proposed for the first time and is successfully applied to the training process of the model, so that the prediction capability of the model for the extreme delta delta G is effectively improved; the trained CNN sub-models are combined, information of all samples in a training set is fully utilized, and the generalization ability of the model is enhanced.

The invention provides a geological stratified sampling device for geological exploration, and belongs to the technical field of exploration sampling, the geological stratified sampling device comprises a cart, a hole is formed in the cart, lifting assemblies are fixedly connected to the two sides of the hole, a power assembly is arranged between the lifting assemblies, the power assembly is in transmission connection with a sampling mechanism, and the sampling mechanism comprises a plurality of sampling barrels. The sampling barrels are detachably connected, a plurality of sampling holes are formed in the sampling barrels, blocking assemblies are arranged above the sampling holes 4, and sampling parts are arranged in the sampling holes and used for collecting soil. The cart is moved to the position where sampling is needed, the lifting assembly drives the power assembly to ascend and descend, the power assembly can drive the sampling mechanism to conduct sampling, the number of the sampling barrels can be selected according to needs, and meanwhile the sampling barrels entering soil can conduct stratified sampling through the sampling part in the sampling hole. The device is convenient to disassemble and carry, the number of the sampling barrels can be selected according to the sampling depth, and the using effect of the device is improved.

The invention relates to the technical field of sampling devices, and provides a bottom mud stratified sampling device and method.The device comprises a barrel, the cross section of the barrel is rectangular, the bottom of the barrel is provided with an opening, the inner wall of the bottom of the barrel is provided with a pair of opening sealing pieces capable of being opened and closed, and the end of the barrel extends to form a tool bit; wherein the tool bit comprises a movable blade and a fixed blade which are overlapped, the movable blade and the fixed blade are both in a sawtooth shape, and the movable blade can rub the fixed blade in a reciprocating mode to conduct cutting; an opening is formed in the bottom of the sampling box, the sampling box is detachably embedded in the cylinder body, a plurality of insertion seams used for insertion of the separation blades are formed in the side wall of the sampling box, and at least one detachable side plate is arranged between every two adjacent insertion seams; and the moving rod is connected to the top of the barrel and used for moving the barrel. The tool bit can cut various fibrous attachments covering the upper layer of bottom mud. The bottom mud can be layered by inserting the separation blade into the insertion seam of the sampling box, and the bottom mud which is kept in the original state can be respectively taken out by opening the side plate, so that the accuracy is improved.

The invention discloses a water quality stratified sampling and sample preparation device, and relates to the technical field of water quality sampling, the water quality stratified sampling and sample preparation device comprises a connecting rod and a sampling tank, the sampling tank is arranged below the connecting rod, the sampling tank performs sampling operation through a sampling mechanism, and the water quality stratified sampling and sample preparation device further comprises a connecting mechanism and a discharging mechanism. By arranging the sampling mechanism, during sampling, a plurality of sampling tanks are sequentially mounted below a connecting rod, the sampling tanks are put into water, after the sampling tanks move to a proper depth, a motor runs to drive a movable plate to move upwards, and external water enters the sampling tanks through sampling ports to be collected; the movable plate moves to the top end of the inner wall of the sampling tank, at the moment, the first rotating plate moves to shield the sampling opening, water at different depths can be synchronously sampled at the same time, sampling operation can be carried out by changing different numbers of sampling tanks according to different sampling depths, and therefore stratified sampling analysis can be carried out on the water area.

This invention provides an in-situ stratified rapid sampling device and method for river and lake sediment pollution, relating to the field of river and lake sediment pollution monitoring technology. The device includes: a main control system, a main sampling system, a mounting frame, a depth sounding module, a working vessel hull, and a crane. The depth sounding module is installed below the stern of the working vessel hull. The main control system and the crane are both mounted on the working vessel hull. The main sampling system is connected to the crane and fixed within the mounting frame. The depth sounding module is used to detect and determine water depth and the thickness of floating mud, flowing mud, and silt. The main control system is used to control the sampling process of the main sampling system and to read the water depth, sediment thickness, and determine whether the main sampling system has completely inserted into the sediment in real time. The main sampling system is used to insert into the sediment to perform stratified sampling of the sediment pore solution. This invention solves the problems of low sampling rate, inability to perform stratified sampling, deviation between stratified sediment samples and actual conditions, low efficiency, and large errors in detection results in existing technologies.

The invention relates to the technical field of biological sampling netting gears. A stratified sampling net comprises a trawl net frame and a netting assembly, the netting assembly comprises sub-netting bodies which are sequentially arranged from top to bottom, and the lower line of the upper sub-netting body in every two adjacent sub-netting bodies is fixedly connected with the upper line of the upper sub-netting body; the trawl frame comprises a main body frame, the main body frame comprises lateral slide rails, the lateral slide rails comprise a front side slide rail and a rear side slide rail which are arranged front and back, and the rear side slide rail is longitudinally and slidably connected with the sub-netting side ropes; the netting opening and closing control mechanism comprises a sliding transverse rod, an elastic telescopic assembly and an unlocking and releasing assembly, wherein the sliding transverse rod is longitudinally connected with the front side sliding rail in a sliding manner; the upper line of the uppermost sub-netting is connected with a sliding cross rod; the lower line of the sub-netting located at the lowermost part is connected with the other sliding cross rod; and the joints of the upper lines and the lower lines of the adjacent sub-nettings are connected with the same sliding cross rod. According to the invention, the requirement of stratified sampling is met.

The invention relates to the technical field of water quality sampling, and particularly discloses layered water quality sampling and classified storage equipment which comprises a sampling tank, the sampling tank comprises an upper shell and a lower shell, a self-locking telescopic rod is mounted at the top of the upper shell, a control switch is arranged at the tail end of the self-locking telescopic rod, an opening and closing assembly is arranged on the upper shell, and a water inlet is formed in the lower shell; a sampling assembly and a driving assembly are arranged on the inner side of the lower shell; the depth of the sampling tank in a water body is accurately adjusted through the self-locking telescopic rod, and meanwhile, ordered and accurate layered sampling of water samples of different water layers is realized by combining the linkage design of the driving assembly, the opening and closing assembly and the sampling assembly; compared with traditional sampling equipment, the sampling equipment has the advantages that the problem of disordered water sample collection is avoided, and a plurality of water layer samples can be obtained through sequential alternation of the multiple sampling barrels without adjusting the position of the equipment for multiple times, so that the sampling efficiency is greatly improved, and the collected water samples can truly reflect the water quality condition of each water layer.

The invention provides a method for analyzing and predicting the water stability of an asphalt mixture, which comprises the following steps of: acquiring multi-dimensional service environment, material composition and standard water stability test data, and carrying out standardization and stratified sampling division on the multi-dimensional service environment, the material composition and the standard water stability test data; a context sensing multi-layer perceptron network supporting feature parameter sharing and gradient accumulation is constructed, and the importance weight of each dimension of features under different data distributions is automatically evaluated and normalized. An attention mechanism and a graph convolutional network are introduced, association between features is quantified, and a key high-order interaction relationship is deduced; by means of K-fold cross validation and meta-learning optimization, the generalization ability of the model for new distribution data is improved, prediction accuracy and feature interpretation are improved, and intelligent analysis and proportion design of the water stability of the asphalt mixture are promoted.

The invention relates to an eDNA method for identifying bumblebee honeycombs in permafrost regions of Qinghai-Tibet Plateau. The eDNA method comprises the following steps: S1, positioning observation sample belts and arranging sampling points on the basis of multi-source data in combination with a Bayesian hierarchical model; s2, performing deep freezing and complete excavation on matrixes around and inside all the sampling points; s3, stratified sampling and anti-degradation treatment are carried out, and a spatial attribute database is established; s4, extracting and purifying eDNA (enhanced deoxyribonucleic acid); s5, determining a nest host based on PCR amplification, high-throughput sequencing and sequence comparative analysis; and S6, constructing a Bayesian hierarchical model in combination with biological information, and judging honeycomb characteristics. The method is simple, rapid and low in cost, not only is suitable for Qinghai-Tibet Plateau permafrost regions, has the core advantages of non-destructiveness and high sensitivity, but also is also suitable for underground insect nest identification research in other environment sensitive regions or regions difficult to physically explore in principle, and has wide application prospects. The method is especially suitable for monitoring rare, secret or difficult-to-approach organisms.

The invention provides a sediment stratified sampling device and a control method. The sediment stratified sampling device comprises a shell, a motor, a drill bit and a sample sampling pipe, the motor is arranged on the shell, and an output shaft of the motor penetrates out of the shell in the axial direction of the shell and is connected with the drill bit. The sample sampling tube at least comprises a first sampling tube and a second sampling tube, the first sampling tube and the second sampling tube extend out of the shell for sampling or retract into the shell after sampling is completed, and the end parts of the first sampling tube and the second sampling tube are respectively provided with a first sealing structure; and second sealing structures are arranged on the inner walls of the first sampling tube and the second sampling tube. The self-adaptive adjustment of the rotating speed of the motor and the double sealing of the sampling pipe generate a synergistic effect, so that the sampling efficiency is improved, the sampling quality is ensured, and the self-adaptive adjustment of the rotating speed of the motor can automatically adjust the sampling intensity and the sampling rate according to the difference of sediments.

The utility model discloses a stratified sampling device for geological survey, which relates to the technical field of geological survey and comprises a frame body, a through groove is arranged on the frame body, universal wheels are mounted on the bottom surface of the frame body, a ground-pricking rod is in threaded connection with the inside of the frame body, the bottom end of the ground-pricking rod is pricked into the ground, and a knob is fixedly connected with the top end of the ground-pricking rod. A driving assembly is arranged on the frame body, a sampling assembly is arranged on the driving assembly, the sampling assembly comprises a sampling barrel, the top end of the sampling barrel is sleeved with a barrel cover, and a group of second soil inlet grooves which are arranged at equal intervals are formed in the sampling barrel. By arranging the sampling assembly, when multi-layer sampling needs to be carried out on soil, the multi-layer sampling of the soil can be realized only by driving the sampling barrel to extend into the soil once, so that the sampling efficiency of the soil can be effectively improved, and by arranging the driving assembly, when the soil is sampled, the sampling assembly can be automatically driven to rotate to move towards the ground, so that the sampling efficiency is improved. And universal wheels are arranged, so that the device can be conveniently moved.

The invention discloses an automatic water body stratified sampling device and method, and relates to the technical field of water body sampling, the automatic water body stratified sampling device comprises a plurality of sampling boxes, the sampling boxes are fixedly connected through connecting assemblies, partition plates are fixedly arranged in the sampling boxes, and sliding check blocks are arranged at the positions, corresponding to water inlet holes, of the inner sides of the sampling boxes in a matched mode; a water inlet channel is formed in the sliding check block, a water inlet pipe is arranged at the position, corresponding to one end of the water inlet channel, of the bottom end of the sliding check block in a communicating mode, a connecting pipe is fixedly arranged on the sampling box, and a sampling mechanism for conveniently driving the sliding check block to move is arranged in the connecting pipe. A plurality of limiting sliding rods are arranged at the bottom end of the sampling box, so that a plurality of sampling boxes are fixedly connected conveniently, and a sliding stop block moves in the length direction of a guide sliding groove under the action of a sliding plate, a push rod, a second rack, a gear and a first rack, so that water body sampling is automatically completed.

The invention discloses a time sequence coal reservoir permeability prediction method based on improved deep learning, and belongs to the technical field of coal bed gas exploration and development and deep learning. According to the method, standardized preprocessing is performed on logging data, a time sequence sample is constructed by using a sliding window, stratified sampling is introduced to optimize K-fold cross validation, and an AdamW optimizer is adopted to train a double-layer LSTM network, so that the problems of low precision and poor generalization ability of a traditional prediction method are effectively solved. Experimental results show that the method can accurately capture the time sequence characteristics of the logging data, data balance is ensured through stratified sampling, overfitting is inhibited in combination with weight attenuation, and the prediction result has high stability and reliability.

The invention relates to the technical field of deep learning, in particular to an intelligent prospecting model construction method based on a knowledge graph and data deep learning, which comprises the following steps: collecting multi-source geological data to perform time decomposition and spatial stratified sampling to extract features, calculating an attachment weight through semantic coding to construct a geological knowledge structure, and constructing a geological prospecting model; the method comprises the steps of extracting spatial-temporal features in a convolution mode, combining with semantic deviation degree weighted fusion to generate a hierarchical feature coupling result, carrying out aggregation analysis on spatial-temporal correlation to extract consistent components, judging a metallogenic response relation through conditional probability reasoning, fitting a model, calculating deviation, adjusting weights, analyzing semantic consistency, and carrying out classification and aggregation to generate an intelligent prospecting optimization result. The feature precision is improved through time decomposition and spatial stratified sampling of multi-source geological data, data association is enhanced through semantic coding, time-space consistency is enhanced through convolution extraction and semantic fusion, multi-scale features are balanced through hierarchical coupling, the ore-forming relation judgment accuracy is improved through probabilistic reasoning, and the result precision and stability are remarkably improved.

The utility model relates to the technical field of sampling devices, and discloses a soil moisture stratified sampling device, which comprises a sampling rod, the drill bit is fixedly connected to the bottom of the sampling rod; the operation assembly is fixedly connected inside and outside the sampling rod. According to the soil moisture stratified sampling device, a fixed rod, a balance plate, a long rod, a sampling rod and a drill bit are driven by a control handle to rotate and drill into soil for sampling, the soil slides into a plurality of soil storage cavities through a sampling opening and a sample inlet, and a clamping block clamping column pull ring is connected through a sealing cover, so that the sampling barrel is prevented from rotating to influence sampling; a control rod slides in a guide groove to drive a fan-shaped block and a sealing plate to perform position adjustment and control sealing and opening of a sampling opening, so that stratified sampling at different depths of soil is facilitated, and meanwhile, a movable block drives a positioning ring to perform height adjustment through a connecting rod, so that the control rod can be fixed; the elasticity of the spring is utilized to prevent positioning from sliding freely to break away from the control rod.