354 results about "Plankton" patented technology

The invention provides a small sample plankton image enhancement recognition method and a small sample plankton image model building method, and belongs to the technical field of underwater image enhancement. The method comprises the following steps: firstly, acquiring and sorting plankton microscopic image data, and constructing a normalized data set; secondly, designing a small sample plankton image enhancement recognition model based on a feature map reconstruction technology, performing feature extraction on the image by adopting a deep convolutional neural network, generating an intermediate layer feature map, and realizing category discrimination in combination with a feature map reconstruction mechanism; the model fuses multiple key designs oriented to cross-domain adaptation and structure perception, the distribution difference between different data domains is relieved, and the characterization capability of the model on the complex morphological structure of plankton is also remarkably improved; and finally, performing end-to-end training and optimization on the model under a meta-learning framework to obtain an optimal model. Experimental results show that the method shows excellent classification performance on a plurality of plankton data sets, and high-precision recognition can be achieved under the condition that the number of samples is limited.

The invention relates to the cross technical field of artificial intelligence and environment monitoring, and discloses an algal community structure change prediction algorithm and system based on multi-source data fusion, and the algorithm comprises the steps: obtaining water quality, weather and plankton multi-source time sequence data; performing time alignment and missing value interpolation; eliminating and screening key environment factors through recursive features; performing dynamic weighted fusion on the multi-modal features by using a space-time attention mechanism; inputting a three-layer stacked LSTM network to output future algae dominant species abundance prediction; and model parameters are corrected on line based on measured data. The system comprises a multi-source data acquisition module, a preprocessing module, a key factor extraction module, a space-time attention fusion module, a dynamic prediction module and an adaptive correction module. According to the method, the prediction accuracy and stability are remarkably improved, and algal bloom early warning and ecological regulation are effectively supported.

The invention discloses a marine plankton hyperspectral imaging detection system, relates to the technical field of spectrum detection, and is used for solving the problem of poor spectrum classification and recognition in a water body environment. According to the method, the hyperspectral image and the environmental disturbance parameters are synchronously acquired, and the disturbance mapping sequence is constructed, so that accurate alignment between the image and disturbance is realized. A disturbance contribution weight matrix is constructed based on a dominant wave band, pixel-level spectrum stripping is carried out, a plankton purification spectrum is extracted, the spectrum purity and the recognition accuracy are improved, and a spectrum abnormal drift region is precisely recognized in combination with derivative spectrum change and image texture features; a coupling relation between the drift region and background disturbance is further established, a dynamic interference factor map is generated, and identification model parameters are dynamically adjusted, so that the identification stability and classification accuracy of the system in a complex interference environment are improved, and the method is suitable for multi-scene marine ecological monitoring.

The invention relates to a marine ranching digital construction method and system based on artificial intelligence, and the method comprises the steps: monitoring plankton in a marine ranching in real time, obtaining a water body image through an image recognition technology, and building a dynamic database, so as to regularly store and update the related data of the plankton. Based on monitoring data, a water quality evaluation model is established, and the correlation among plankton species, density and water quality parameters is analyzed. Factors such as water flow velocity and flow direction are integrated, a flow change model is established, and the influence of water flow on plankton is judged. A primary culture optimization scheme is formulated by simulating the interaction between cultured organisms and planktons, and the culture trend is predicted in real time and the management strategy is adjusted by integrating the water quality evaluation and the output result of the flow change model. According to the scheme, the intelligent management level of the marine ranching is effectively improved, dynamic and scientific management of the culture environment is achieved, powerful support is provided for healthy growth of cultured organisms, and sustainable development of the marine ranching is promoted.

The utility model relates to the technical field of ecological environment detection, in particular to an underwater plankton sampling device which comprises a main body, a sampling driving component is arranged in the main body, and a control collecting component is fixedly connected in the main body; according to the utility model, the sampling depth can be accurately controlled by utilizing the depth sensor, in order to meet different research requirements, the tube wheel is driven by the motor to wind the sinking tube, and the automatic control driving mechanism can quickly complete sampling and can drive the sampling barrel to move up and down in water to realize sampling at different depths, so that the sampling efficiency is improved. The microprocessor is used for controlling the operation of the depth control mechanism and the driving mechanism, automatic sampling is realized, the inner wall of the sampling barrel is smooth, attachment and damage of plankton in the sampling process are avoided, automatic sampling is realized through the control unit, the operation is simple, and the use is easy; the sample collection container can be used for storing sampled plankton samples, so that the samples are prevented from being polluted.

The invention relates to the technical field of biological outbreak prediction, in particular to a marine organism outbreak prediction method and system based on real-time monitoring, and the method comprises the following steps: based on a sea area microsensor array, collecting environment and plankton data, processing interference and noise, normalizing parameters, and combining ecological baseline adjustment; and analyzing the environment and biological response relationship between the nodes, identifying a key area and a change trend, and judging plankton extension characteristics. According to the method, synchronous linkage of environmental factors and plankton response is realized through a joint discrimination mechanism of real-time acquisition, multi-parameter dynamic normalization and fusion of spatial distribution and time sequence data, sea area key change signals are identified by depending on ecological baseline reference, abnormal response is automatically screened in a monitoring network, and an extension situation is tracked; the space-time evolution trend of a risk area is effectively reflected, rapid identification and prospective early warning of potential explosion phenomena are realized through whole-process dynamic evaluation, and a reliable data basis is provided for ecological intervention and scientific management.

The invention discloses a method for predicting abundance of plankton by using marine ecological observation data, which belongs to the technical field of marine organism prediction, and comprises the following steps: collecting multi-source marine environment data to obtain a data set; processing short-term correlation characteristics among variables from the data set to obtain an environmental factor interaction vector; processing the time dynamic change of the environmental factor interaction vector to obtain a plankton abundance change trend; enhancing the association strength of the environmental factor interaction vector and the plankton abundance change trend to obtain a weighted dynamic feature set; extracting subsets having influence on plankton abundance prediction from the weighted dynamic feature set to obtain a prediction feature group; and constructing a regression model according to the prediction feature group, and processing the newly obtained multi-source marine environment data by adopting the regression model to obtain a plankton abundance prediction value. The method for predicting the abundance of the plankton by using the marine ecological observation data solves the problems that the current prediction result is lagged or not accurate enough, and the timeliness and reliability of a decision are influenced.

The invention discloses a sepiella maindroni stepped wild domestication device which comprises a plurality of net cages arranged from inside to outside, each net cage is provided with a plurality of meshes, and the meshes in different net cages are gradually increased from inside to outside in a stepped manner; a plurality of suspension type fish reefs are arranged in the net cage, each suspension type fish reef comprises a plurality of single bodies horizontally installed on the floating rope, and each single body is a shell with a plurality of small holes formed in the shell wall. An area which is flat in terrain, relatively gentle in water flow, rich in plankton and about 10 m in water depth is selected near a sea area to be released as a domestication field, the device is put into the domestication field, and in-situ wild domestication is carried out on sepiella maindroni larvae; and the predation capability, the capability of avoiding enemies and the capability of coping with environmental stress after entering a natural sea area are improved, so that the enhancement and release effects are improved.

The invention discloses a plankton dynamic monitoring method and device based on deep learning and a medium, and the method comprises the steps: inputting a preprocessed image into a target detection model for detection, and the target detection model comprises the steps: carrying out the multi-level feature extraction of the preprocessed image through a backbone network, and obtaining a plurality of feature maps of different levels; respectively inputting the plurality of hierarchical feature maps into a feature enhancement unit to extract various types of semantic information, and performing path fusion and feature re-calibration on each layer of feature map to obtain enhanced different hierarchical feature maps; inputting the feature maps of different levels into a multi-scale fusion unit for spatial semantic alignment and cross-level feature fusion; inputting the fused feature map into a decoupling detection head for target classification and bounding box regression prediction; and the plankton is positioned based on a result output by the detection head to obtain the type of the plankton. According to the invention, the accuracy of category classification and positioning is improved based on the architecture of the target detection model.

The present invention relates to a lake plankton sample collection device in the technical field of lake plankton sample collection, comprising: a mounting bracket, a telescopic device arranged on the top of the mounting bracket, a receiving frame arranged at the output end of the telescopic device, and a bearing plate connected to the bottom of the receiving frame, wherein a bidirectional telescopic device is arranged in the bearing plate, and both output ends of the bidirectional telescopic device are connected to a connecting frame, and a collecting component for collecting plankton is connected to the bottom of the connecting frame. The present invention is provided with a collecting component, because the folding cylinder is in a folded state, when the collecting device enters the lake, the impact on the water surface is small during the process of its entry, and the water flow will not be caused to move significantly, and the two groups of mounting plates are close to each other, so that the mounting plates move laterally in the lake, so that the water flow can enter the folding cylinder laterally from the water inlet, so that the water flow and plankton at the water inlet are "sucked" into the folding cylinder, thereby improving the collection efficiency and collection quality.

The invention discloses an environment-friendly closed-loop ecological culture method for colored pearls, which belongs to the technical field of aquaculture and comprises the following steps: S1, selecting and culturing high-quality pearl mussels to form high-quality pearl mussels; s2, cooperatively culturing high-quality pearl mussels, fishes, algae and microbial communities; s3, according to the color requirement of the high-quality pearl mussels, algae, plankton, vegetable protein and a microorganism culture solution are used for preparing feed, the high-quality pearl mussels are fed, and the color and glossiness of pearls are regulated and controlled; s4, collecting breeding data in real time, and adjusting collaborative breeding parameters; according to the color requirement of high-quality pearl mussels, the feed is prepared from algae, plankton, vegetable protein and a microorganism culture solution, the high-quality pearl mussels are fed, nacre layer components secreted by pearl sacs in mussel bodies are affected through natural pigment components in the feed, and therefore the color and glossiness of pearls are regulated and controlled. The active regulation and control of the pearl color and glossiness can be realized.

The present application relates to the field of sewage purification, and discloses a household micro sewage treatment system and a sewage treatment method, which comprises the following steps: building a septic tank; preparing a household micro sewage treatment system, an aeration system and suspended filler for microbial attachment; pumping clarified liquid by a lifting pump, and the clarified liquid enters a contact oxidation zone, and microorganisms degrade COD and BOD in the clarified liquid; the clarified liquid at the contact oxidation zone flows into an electrocoagulation zone, and electrocatalytic flocculation is performed; then, pollutants and phosphorus in the clarified liquid are filtered by a filtering zone, and the clarified liquid forms purified water; the purified water is taken from a water outlet zone, and is used for crop irrigation; or, a landscape zone for breeding aquatic plants or plankton is arranged at the water outlet zone. In the present application, the contact oxidation zone, the electrocoagulation zone, the filtering zone and the water outlet zone are sequentially and continuously arranged from bottom to top, and the arrangement structure of the whole household micro sewage treatment system is compact, and it is more convenient to arrange the system in a separate house environment in rural areas.

The invention relates to the technical field of marine ecology, in particular to a plankton abnormal migration analysis method based on multi-sensing data fusion and diffusion modeling, which comprises the following steps: S1, arranging a micro sensing buoy array in a target sea area; s2, synchronously triggering the micro sensing buoy array to carry out data acquisition, and obtaining an original parameter set; s3, compensating and correcting the collected original parameter set; s4, spatial interpolation is carried out, and a plankton density distribution diagram is generated; s5, calculating the change rate of the density gradient of adjacent time slices, and outputting a dynamic diffusion rate field; and S6, when the rate value in the dynamic diffusion rate field exceeds a preset threshold value, marking the dynamic diffusion rate field as a biological abnormal migration area. According to the method, accurate identification of plankton spatial distribution and abnormal migration behaviors is realized in a mode of combining multi-source signal acquisition and dynamic diffusion analysis, and then the high-space coverage capability, the real-time multi-parameter fusion analysis capability and the dynamic migration identification capability are effectively achieved.

The application discloses a kind of plankton detection method, system and electronic equipment, it is related to computer vision technical field.The present application can be based on the image data of different regions, different river reaches of the river to be detected by using river plankton detection model, accurately, quickly get the plankton detection result of each pixel.And, multiple domain self-adaptive feature extraction modules are arranged in the river plankton detection model of the application, the distinguishing ability of target and background difference in image data can be improved, multiple boundary alignment modules can enhance the target feature extraction capability, the accuracy of plankton detection can be significantly improved, and the economic and ecological cost of plankton management can be effectively reduced.

The utility model discloses a reservoir water quality plankton detection vertical rope, which comprises a detection sampling rope, a sampling base and a movable seat, the bottom end of the detection sampling rope is provided with a sampling barrel, the sampling barrel is sleeved with a lifting cover in a sliding manner, the outer walls of the two sides of the sampling barrel are both provided with sampling grooves, and the top of the lifting cover is integrally connected with a lifting block; a motor is fixedly arranged on the inner wall of the sampling barrel, and a lead screw is arranged on an output shaft of the motor. When the sampling rope is detected to be unwound and the gravity of the balancing weight is added, the sampling barrel can sink into the water of the reservoir, the motor drives the screw rod to rotate and the lifting block to be threaded, the lifting block can drive the lifting cover to ascend to expose the sampling groove, and the water of the reservoir can enter the sampling barrel to be sampled; by controlling the lifting cover, the sampling tank can be opened when the sampling barrel reaches the required depth in water, so that water at different depths in a reservoir can be sampled and detected.

The invention discloses a microbial fermentation chicken manure fish fertilizer for aquaculture and a preparation method of the microbial fermentation chicken manure fish fertilizer, and belongs to the technical field of agricultural waste resource utilization. The method comprises the following steps: firstly, flushing chicken manure of cage rearing chickens with a photosynthetic bacterium solution and screening out particles; then adding EM bacteria and lactic acid bacteria for composting fermentation; drying the fermentation product; and finally adding zeolite powder loaded with photosynthetic bacteria, mixing and modifying to obtain the final fish fertilizer. Through a unique process of combining multi-strain synergistic fermentation and zeolite powder modification, thorough harmlessness and recycling of the chicken manure are realized. The obtained fish fertilizer not only has comprehensive nutrition and lasting fertilizer efficiency, can effectively promote the growth of plankton in an aquaculture pond, but also has the functions of adsorbing and degrading ammonia nitrogen, hydrogen sulfide and other harmful substances in a water body, and has the remarkable advantages of improving water quality, reducing diseases and increasing the culture yield.

The invention provides an underwater plankton sampling method and device, and relates to the technical field of underwater biological sampling, and the technical scheme is characterized in that the method comprises the steps: obtaining the current position information of sampling equipment, the distance information of a next sampling point, and the current water environment parameters; controlling a plurality of adjustable nozzles on the surface of the sampling equipment to carry out washing operation, wherein filtered environmental water is used as a washing medium in the washing operation; according to the distance information, the movement speed of the sampling equipment and the current time, dynamically adjusting the intensity and mode of the scouring operation, so that the intensity of the scouring operation is gradually reduced along with approaching the next sampling point; the scouring effect is monitored in real time, and the scouring strength and mode are adaptively adjusted according to the monitoring result; and the flushing operation is stopped before the sampling equipment reaches the sampling point by a preset distance. The underwater plankton sampling method and device have the advantages that water disturbance is reduced, cross contamination of samples is prevented, and sampling precision and efficiency are improved.

The invention relates to the technical field of seawall ecological transformation, and discloses a slope type seawall inner slope ecological transformation method which comprises the following steps: selecting a seawall section suitable for ecological transformation according to three first-level indexes, namely a seawall shoreline foundation, hydrology and water quality conditions and surrounding environment conditions; constructing a pool in the selected seawall section according to the terrain; constructing a pool base; and constructing a plant community in the water pool according to the life type, the phenological period and the salt tolerance of the plant. According to the method, a proper transformation section can be selected in combination with various environmental factors of a transformation area, then a corresponding water pool is constructed in combination with the landform, then a proper ecological material is selected to construct a substrate, and different plant communities are constructed in the water pool according to the characteristics of different plants. A natural-imitated seawall ecological space is built, the flood prevention and tide blocking functions of the seawall are guaranteed, the hygrophytes, aquatic plant communities and planktons can be utilized, an inhabiting and foraging environment is built for aquatic animals and hydrophilic birds, and the ecological service function of the seawall is improved.

The invention belongs to the technical field of black and odorous water treatment, and particularly relates to a method for repairing and treating rural black and odorous water. According to the invention, aquatic plants, aquatic animals and microbial communities are configured in the system, and hydrodynamic optimization is combined, so that an underwater forest ecological system with self-maintenance capability is constructed, biological self-purification of the black and odorous water body and long-acting stability of the ecological system are realized, and the system is suitable for black and odorous water body treatment of rural rivers and ponds. The ecological balance of a water body is maintained through closed-loop feedback of excessive plankton, enhancement of fish ingestion, promotion of plant growth by excrement and absorption of excessive nutritive salt, meanwhile, oxygen is supplied through photosynthesis of submerged plants, and zero external energy consumption is achieved by combining stepped oxygen transfer without external aeration. In addition, the raw material of the carrier is derived from agricultural wastes, so that the treatment cost is reduced, and the recycling of rural solid wastes can be effectively promoted.

The invention discloses a lake and bay habitat maintenance method based on hierarchical calculation, and relates to the technical field of water ecological environment protection and ecological restoration, the effective water body volume of a lake is accurately calculated by combining terrain scanning with a partition weighted correction formula, and the volume estimation deviation of a traditional method is avoided; on the basis, the existing biomass of the plankton is subjected to layered correction, and the estimation precision of the primary productivity of the lake is improved, so that a scientific basis is provided for the proliferation capacity of filter-feeding fishes. Through water level and water quality dynamic correction and in combination with submerged vegetation population structure regulation and control, vegetation degradation caused by excessive ingestion of fishes can be effectively avoided. Further introducing batch stocking of the snails and the shellfish, constructing a closed-loop mechanism of snail ingestion-plankton reproduction-shellfish filter feeding-fish utilization-vegetation restoration, finally forming a fish, shellfish, snails and grass synergistic ecological balance system, and realizing long-term stable maintenance of the lake and bay habitat.

The invention discloses a plankton image enhancement method based on a deep learning model, which belongs to the technical field of image enhancement, is used for plankton image enhancement, and comprises the steps of inputting a plankton image into a local feature extraction module, obtaining a plankton local feature map, and adjusting parameters of a global feature extraction module. Inputting the plankton image into a global feature extraction module to obtain a plankton global feature map, carrying out feature fusion on the plankton local feature map and the plankton global feature map to obtain a locally enhanced plankton image and a globally enhanced plankton image, and inputting the locally enhanced plankton image and the globally enhanced plankton image into a classifier, and obtaining a plankton image enhancement result. According to the method, the key local features of the plankton are obtained, the local features and the global features of the plankton are extracted, the enhanced plankton image is obtained, and the image enhancement accuracy of the plankton is improved through the image.

The invention relates to the field of ecological environment monitoring production, in particular to an efficient separation type ecological planktonic animal and plant collecting net which comprises a frame, the middle of the frame is provided with a first-layer net used for intercepting large sundries, and the top of the first-layer net is provided with a lifting hook. The bottom second-layer net is used for intercepting phytoplankton, the third-layer net located on the same axis with the inner side of the second-layer net is used for intercepting zooplankton, rotating force is generated through the propellers under the action of water flow, and the auger push plate is made to be of a conical structure and rotate on the inner side face of the third-layer net. One end of the corrugated plate on the outer side inclines along the inner side face of the third layer of net, plankton can be pushed to move in a dispersed mode to avoid local accumulation and blockage during rotation, the plankton can be accurately intercepted by means of component force, and the wave trough positions of the three corrugated plates are not located on the same horizontal plane to generate a staggered stirring effect, so that filtering is more comprehensive and uniform.

The invention discloses a total factor monitoring method for a marine ranch, and belongs to the technical field of ocean engineering and information. The method comprises the following steps: collecting water quality parameters and biological population data in real time; the planktons and pollutants are identified through spectral analysis and chemical sensing, and environmental elements are classified; a sonar and an electronic tag are combined to track a fish trajectory, and dynamic monitoring data are obtained; predicting a red tide probability based on machine learning and outputting risk early warning; continuously updating the model to form multi-element integrated monitoring data; and finally, sorting the key indexes to generate marine ranch key element monitoring framework data. According to the invention, the real-time monitoring capability of the marine ranching environment and the biological state is obviously improved, the ecological risks such as red tide are reduced, and the sustainable development of the marine ranching is ensured.

The invention discloses a protective area biodiversity monitoring and sampling device which comprises a support, a rotating roller rotatably inserted in the support and a plurality of supporting rods fixed to the end of the rotating roller and circumferentially distributed at equal intervals, sampling shells are arranged at the other ends of the supporting rods, and isolation hoods are fixedly connected to the inner walls of the sampling shells; an isolation cover is arranged in the sampling shell, a sampling cavity is formed between the isolation cover and the sampling shell, an elastic assembly is arranged in the isolation cover, two sealing rods are arranged on the elastic assembly, and two through holes which are symmetrically distributed are formed in the surface of the sampling shell. According to the invention, when the sampling shell is driven to enter a water body, the end part of the sealing rod is separated from the interior of the through hole due to water pressure, and the water body containing plankton enters the sampling chamber; when the sampling shell rotates to a position separated from the water body, the sealing rod is reset to seal the through hole; when the sampling shell rotates to a drainage station, namely, the first butt-joint assembly and the second butt-joint assembly are communicated, the water is guided into the liquid drainage pipe at the moment, and the purpose of drainage is achieved.

The invention discloses a portable floating algae collection device, and belongs to the technical field of plankton collection, the collection device comprises an unmanned ship, a transversely arranged collection net below the unmanned ship, an open collection port at the front end of the collection net, the rear end of the collection net is collected and connected with a valve, the outer side of the front end of the collection net is connected with an outer sleeve member, and the outer sleeve member is connected with the unmanned ship. The outer sleeve part is connected with the unmanned ship, an overflowing gap is formed between the inner wall of the outer sleeve part and the periphery of the collecting net, the two ends of the overflowing gap are communicated with the outside, a rotating part is arranged in the overflowing gap and comprises a rotating ring, the rotating ring is rotationally connected with the inner side of the outer sleeve part, blades are arranged on the rotating ring in a surrounding mode, the blades have bending degrees, and the tail ends of the blades can make contact with the periphery of the collecting net. A clamping ring for limiting the position of the rotating ring is arranged on the inner wall of the outer sleeve piece. The attitude of the collection net can be stabilized, and the collection stability and the collection efficiency are improved.

The invention discloses marine disaster early warning plankton density monitoring equipment, and belongs to the technical field of plankton density detection, the marine disaster early warning plankton density monitoring equipment comprises an anchoring ladder column and a plurality of positioning suspension seats, the top end of the anchoring ladder column is connected with a top sealing seat through a lifting umbrella column, and the top sealing seat is connected with the positioning suspension seats through a plurality of umbrella support assemblies. Through the arrangement of the reciprocating assembly and the opening and closing assembly, the imaging plankton recorder can be driven to reciprocate up and down by utilizing the cooperation of an impact spinning roller and a two-way threaded column and utilizing tidal power, layered monitoring at different depths is realized, and the motion of a reciprocating sleeve frame triggers magnetic repulsive force and controls opening and closing of a sealing arc plate; shallow-layer and deep-layer water samples are collected at the same time in the initial stage, meanwhile, the rotary taking assembly and the anchoring protruding block are arranged, the sediment sampling barrel can fall down to enable the impeller piece to drive the auger blade to rotate, the notch sleeve is opened in combination with the bottoming inertia of the anchoring protruding block and the ejection of the blasting diaphragm, and undisturbed sampling of bottom-layer planktons and sediments is achieved.

The invention belongs to the technical field of image processing, and discloses an underwater dredging robot terrain recognition method and system, and the method comprises the steps: obtaining an illumination attenuation coefficient through the shooting depth and plankton information, accurately correcting the influence of illumination on an image, and carrying out the brightness adjustment of the image based on the illumination attenuation coefficient, so as to enable the terrain features to be more prominent. Utilizing Laplace decomposition to obtain a multi-layer topographic image, and realizing multi-scale analysis; the accuracy of terrain analysis is improved by screening an edge texture region; the defogging weight is determined in combination with the illumination attenuation coefficient, and the dark channel prior is adopted for defogging recovery, so that the defogging effect is effectively removed, and the image visibility is improved. And reconstructing and synthesizing a complete image through an inverse Laplacian pyramid to obtain an underwater topographic image of which the quality is comprehensively improved, and further obtaining underwater topographic information. The method not only improves the image quality, but also achieves the precise analysis and recognition of the underwater topography, and provides powerful technical support for the research of the underwater topography.

The invention relates to an unmanned ship multi-water-layer plankton monitoring system and a monitoring method, which solve the defects of high cost, deep draft, large volume and poor automation degree of an artificial ship, expand the multi-water-layer monitoring capability of the unmanned ship, improve the working efficiency and reduce the cost. According to the technical scheme, a monitoring catenary is arranged on a stern frame of an unmanned ship body, mounting bases are arranged on the monitoring catenary at equal intervals, and each mounting base comprises an optical imager and a temperature-salinity-depth measuring instrument which are used for obtaining water quality parameters. The activity state of plankton such as acete chinensis is recorded in an image and video mode, the environmental information is collected through the temperature-salinity-depth measuring instrument, water quality samples do not need to be collected and reserved, and the monitoring process is effectively simplified.

The invention discloses a water ecological health assessment method based on sensitive species and community stability. The method comprises the following steps: step 1, identifying key species and sensitive species; 2, quantifying ecological system stability indexes, and calculating stability attributes based on plankton community composition time and functional time sequence data; step 3, constructing a multi-dimensional evaluation index system; step 4, data standardization processing: carrying out data cleaning, standardization and dimension reduction processing on the multi-dimensional evaluation indexes; 5, determining an index weight based on an entropy weight method; step 6, calculating an ecological health quality index; and step 7, ecological system health state evaluation: according to the ecological health quality index value, evaluating the ecological system health state and carrying out grading so as to provide a basis for management decision making. According to the method, the nutrition cascade effect and the species interaction can be captured; ecological system degradation can be early warned, and the accuracy of ecological health assessment and the pertinence of environment management are improved.

The invention relates to an N-BEATSx plankton prediction method fusing a semantic model. The method comprises the following steps: acquiring an observation data set in a current environment; performing multi-scale interpolation processing on the observation data set according to interpolation strategies corresponding to different interval durations to obtain a target observation data set comprising target multi-source environment data and target plankton data; and in the improved N-BEATSx network fused with the semantic model, performing cross attention operation and residual operation on the target multi-source environment data and the target plankton data to obtain a prediction result based on the plankton variation in the current environment. By adopting the method, semantic fusion and dynamic prediction of the environmental data and the biological data can be realized.