66results about How to "Realize scientific" patented technology

The thoracolumbar vertebra fixing brace comprises a front chest supporting structure, a back supporting structure, an inflation and deflation device and a control module, the front chest supporting structure and the back supporting structure are connected and define a thoracolumbar vertebra clamping area, a front chest air bag set is arranged on the inner side of the front chest supporting structure, and the front chest air bag set is provided with a front chest pressure detection device; a back air bag set is arranged on the inner side of the back supporting structure and provided with a back pressure detection device. The chest air bag set and the back air bag set are both connected with the inflation and deflation device, and the chest pressure detection device, the back pressure detection device and the inflation and deflation device are all connected with the control module. The front chest air bag set and the back air bag set adjust the pressure value through inflation and deflation actions, the expectation of the pressure value applied to the thoracolumbar vertebra of a patient by a doctor can be achieved, standardization and scientization of the wearing and fixing tightness degree of the thoracolumbar vertebra fixing brace are facilitated, and the comfort degree of the patient is improved.

The invention discloses a ship path planning method and system based on Beidou grid codes, and belongs to the technical field of path planning, and the method comprises the steps: obtaining planning data of a to-be-planned area of a ship, carrying out the priority level division of the ship, and combining a prior path, a priority level and a planning index, a grid chart based on Beidou grid codes is generated through a real environment Beidou grid code management module to perform global path planning, collision risk analysis is performed according to real-time sensing data of a navigation positioning system, an AIS, an electric gyrocompass, a log, waves and weather forecast, a path planning effect is evaluated according to task completion efficiency after planning, and the path planning efficiency is improved. According to the method, real-time sensing data such as port information, ship route information, route planning historical data and meteorological information of ships are analyzed and excavated, the route is recommended, the safety, economical efficiency and reliability of the route are improved, and the method is suitable for large-scale popularization and application. And the intelligent level and the operation efficiency of the ship are improved.

The invention discloses an intelligent agriculture platform construction method based on big data analysis and a visual model, and the method comprises the steps: arranging a sensor network, and monitoring the key environment parameters of a farmland in real time; using the unmanned aerial vehicle to shoot crop images; according to the shot crop image, identifying a part with pest and disease damage characteristics in the crop image; deducing the age of the crop leaf according to the shot crop image; a cloud platform is built, farmland related data is displayed in an integrated mode through the cloud platform, and decision suggestions are provided based on big data analysis according to all data input into the cloud platform. The system integrates multiple functions such as farmland data display, unmanned aerial vehicle fixed-point automatic cruise, disease and pest recognition and early warning, agricultural question and answer assistant and the like, and provides one-stop intelligent agricultural management service for farmers. The platform provides scientific guidance suggestions for agricultural production based on big data analysis, and assists in improving yield and quality.

The embodiment of the invention provides a children language behavior rehabilitation teaching system and computer equipment. The system is characterized in that a teacher end determines teaching courses in multiple fields according to a screening result to form an initial personalized rehabilitation teaching plan; the supervision terminal performs auditing and adjustment to form a final personalized rehabilitation teaching plan; the educational administration terminal forms course arrangement according to the final personalized rehabilitation teaching plan and the teaching resource condition; the teacher end allows the teacher to teach after determining that the teacher has prepared the teaching course; in the teaching process, the teaching content is displayed to the target child, and the teaching operation guidance content is displayed to any teacher; in the teaching process, the teacher end receives rehabilitation training process data in each teaching course, teaching summary reports of different time periods are formed, family generalization teaching content suitable for target children is determined, and the teaching summary reports and the family generalization teaching content are sent to the parent end; and the supervision end feeds back teaching suggestions to the teacher end in real time.

The invention provides a steel production scheduling method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining the production supply and marketing data, production technology data, rolling line production state parameters and billet stock parameters of a steel production process, building a production planning model, and carrying out the initial production plan scheduling solving according to the production planning model; obtaining an initial production scheduling plan, and solving the initial production scheduling plan based on a large-scale neighborhood search algorithm and a production planning model to obtain an optimal production scheduling plan; according to the method, the production planning model is constructed through the supply and marketing, the process, the rolling line production state and the billet stock, the initial production plan scheduling is performed, and the initial plan is iteratively optimized by means of the neighborhood search algorithm to obtain the optimal production scheduling plan, so that the problem of overall non-optimization caused by existing single-link optimization is solved, and the production efficiency is improved. The production flexibility and response speed of an enterprise under complex production process conditions and a dynamic market environment are improved, and global optimization of a production plan is realized.

The hip joint brace comprises a waist supporting piece, a leg supporting piece, a connecting support, an inflation and deflation device and a control module, the waist supporting piece and the leg supporting piece are connected through the connecting support, a waist air bag is arranged on the side, facing the waist, of the waist supporting piece, and the waist air bag is provided with a waist pressure detection device in a matched mode; a leg air bag is arranged on the side, facing the leg, of the leg supporting piece, and the leg air bag is provided with a leg pressure detection device; the waist air bag and the leg air bags are both connected with the inflation and deflation device, and the waist pressure detection device, the leg pressure detection device and the inflation and deflation device are all connected with the control module. The pressure values of the waist air bag and the leg air bags are adjusted through inflation and deflation actions, the expectation of the pressure value applied to the hip joint position of a patient by a doctor can be achieved, standardization and scientization of the wearing and fixing tightness degree of the hip joint brace are facilitated, and the comfort degree of the patient is improved.

The invention provides a business workflow dynamic arrangement and optimization method based on a large model agent, and the method comprises the steps: (1) analyzing the features and operation logic of a multi-element business workflow, and defining a business workflow description language; and (2) decomposing a complex business process construction process, and providing a layered process modeling system to guide a large model agent to construct a workflow model. And (3) constructing a task execution queue based on the task dependency relationship, and dynamically executing and monitoring the workflow. And (4) according to the execution log of the business workflow, discovering the bottleneck, redundancy and abnormity of the workflow model by adopting a process mining algorithm, and proposing a process improvement and optimization strategy. And (5) constructing a collaboration framework of a plurality of large model agents, and realizing dynamic arrangement, monitoring and optimization of the business workflow. According to the method, the defects that the current business workflow construction depends on experience of designers, and effectiveness and function requirements are difficult to guarantee are overcome; the defect that the business workflow is difficult to adapt to dynamic demand changes is overcome.

The invention discloses an intelligent doctor seeing method, system and device for AI virtual person accompanying diagnosis and a medium. The method comprises the steps that an intelligent hospital guide demand instruction is received, a virtual consulting room is constructed, and an AI virtual person is generated; after it is judged that the user enters the virtual consulting room, user input information is obtained in real time; determining a user object type and a user hospital guide application scene according to the user input information; the abnormal emotion of the user is recognized, and a preset emotion pacifying strategy is matched, so that the AI virtual human interacts with the user according to the matched emotion pacifying strategy; according to the real-time interaction information of the user and the historical intelligent hospital guide information of the user, matching a preset deep learning model in combination with a hospital guide application scene of the user, and outputting AI virtual human interaction reaction information and a preliminary diagnosis result; and determining a registration department according to the preliminary diagnosis result, generating registration appointment recommendation and completing registration appointment. According to the invention, the user experience in the intelligent treatment process of AI virtual human accompanying diagnosis can be improved.

This invention provides a method and system for predicting vehicle speed in commercial vehicles using the E-Power architecture, relating to the field of commercial vehicle speed measurement technology. First, vehicle operating data is collected via hardwired and CAN bus lines. Second, the PCA method is used to extract features from the collected vehicle operating data, obtaining variables highly correlated with vehicle speed, which serve as input to the speed prediction model, improving computational efficiency. Finally, a speed prediction model is established based on a recursive fuzzy neural network and a multi-step prediction strategy, achieving accurate prediction of vehicle speed during operation and improving fuel economy and driving comfort.

The invention discloses a wrist joint brace which comprises an upper fixing plate, a lower fixing plate and a connecting piece, the connecting piece is used for connecting the upper fixing plate and the lower fixing plate, an annular cavity is formed between the upper fixing plate and the lower fixing plate, an annular air bag is arranged in the annular cavity and connected with an inflation and deflation device, and the inflation and deflation device is connected with a control module. A pressure detection device is arranged on the surface of the annular air bag and connected with the control module. According to the wrist joint brace, the pressure of the annular air bag on the wrist joint of the human body is monitored in real time through the pressure detection device, the fixing state of the wrist joint brace can be adjusted in time, the occurrence rate of complications / disability is effectively avoided, the operation, treatment and rehabilitation effects are guaranteed, and the pain of a patient is relieved; the value of pressure applied to the wrist joint position of the patient by a doctor is expected, standardization and scientization of the wearing and fixing tightness degree of the wrist joint brace are facilitated, and the comfort degree of the patient is improved.

The invention discloses a sheet metal processing intelligent control method and system based on multi-source data feedback, and relates to the technical field of industrial digital control, and the method comprises the steps: obtaining the data of a to-be-processed sheet metal part, and according to the data of the to-be-processed sheet metal part, based on the geometric characteristics and deviation sensitive characteristics of a sheet metal part processing path, calculating the processing path of the sheet metal part; differentiated machining areas are divided, and a partition machining map is generated. According to the method, differentiated classified management and control of the processing areas are realized through the partitioned processing map, a regional basis is provided for subsequent differentiated process parameter configuration, accurate distribution of acquired resources is realized through configuring data acquisition frequency and precision parameters based on the regional deviation sensitivity level, deviation causes are quantified through a data model, and the accuracy of the data model is improved. And the technological parameter adjustment amount is deduced in combination with the equipment constraint range and the parameter sensitivity, so that the scientificity and accuracy of parameter adjustment are realized, the problems of insufficient blindness and adaptability of traditional manual experience adjustment are solved, and the precision consistency of sheet metal processing is improved.

The application discloses a cabin reverberation parameter recommendation method and system based on a multi-dimensional objective evaluation model, which comprises sound field equalization and reverberation acoustic data acquisition; multi-dimensional objective feature extraction, fusion and dimension reduction; multi-dimensional objective evaluation model modeling; based on indoor acoustics, sound quality evaluation and Zwicker psychoacoustic model and Filter Mode, facing cabin audio application scenarios, including voice mode, concert hall / theater mode, pop / electronic music mode, respectively outputting corresponding RT, C80 parameter value range, and executing on a vehicle-mounted DSP to realize adaptive reverberation parameter configuration. The application constructs a quantifiable multi-dimensional evaluation objective model Model=f(RT, C80) with reverberation time RT and clarity C80 as input and with intelligibility STI, sound quality SQ and surround sense LEV as output, and recommends optimal reverberation parameter configuration for different audio scenes based on the model.

The invention discloses a gynecological tumor 3D printing implantation guide plate puncture path design method, and relates to the technical field of gynecological tumor radiotherapy. The method comprises the following steps of: A100, filling a vaginal cavity, and acquiring intracavity and pelvic cavity data through CT (Computed Tomography); a200, the position Ti of a puncture target spot is determined, and a virtual puncture model is constructed; a300, modifying the CT data based on the virtual puncture model to enable a puncture path in the puncture model to be different from surrounding tissues, and exporting the modified CT data; a400, a final guide plate model is constructed according to the corrected CT data, and an implantation guide plate is manufactured through 3D printing; the problem that the puncture path of the gynecological tumor implantation guide plate is difficult to design scientifically is solved.

The present invention discloses a systematic method for radon shielding construction of underground projects, including survey, diagnosis, test, construction, acceptance, and maintenance stages; through on-site survey and measurement of the internal dimensions of the underground project, the original radon exhalation rate, and the background radon concentration of the external environment; setting the target radon concentration of the underground project, estimating the target radon exhalation rate; calculating the radon shielding efficiency target value of the anti-radon layer, and determining the construction plan; carrying out experimental construction on the wall of a local area of ​​the underground project according to the construction plan; carrying out comprehensive construction according to the construction plan; conducting an overall verification of the radon shielding effect of the underground project, and if the overall verification is unqualified, it is necessary to conduct a local verification of the radon shielding effect of the underground project; formulating the engineering use instructions and maintenance plan. The embodiment of the present invention carries out full-process planning of the entire radon shielding project, and optimizes the construction plan through on-site survey and testing, thereby realizing the scientificity, systematicness, and effectiveness of radon shielding of underground projects.

The invention relates to the technical field of intelligent medical treatment, in particular to a hospital-oriented intelligent scoring performance assessment method, system and device and a medium, and the method comprises the steps: obtaining the performance data of a plurality of hospitals, and extracting a standardized performance indicator vector; unsupervised clustering analysis is carried out on the standardized performance indicator vectors, multiple performance levels are divided, and benchmark groups are determined based on the performance levels; on the basis of the performance data of the benchmark group, key performance indicators and critical threshold values thereof are identified, and score weights are deduced through reverse regression analysis; constructing a scoring formula based on the key performance indicators, the critical threshold values and the scoring weights; and based on the performance data, calculating the comprehensive performance score of each hospital by using a scoring formula. According to the method, objective and adaptive scoring based on data driving can be realized, and scientificity and efficiency of hospital performance assessment are remarkably improved.

The invention discloses a three-network emergency resource optimization method and system fused with an unmanned aerial vehicle communication relay, and belongs to the technical field of power system planning and disaster defense, and the method comprises the steps: building a communication power supply coupling model based on an unmanned aerial vehicle relay drive, and obtaining a communication recovery basic framework; constructing an outer layer optimization model taking the pre-disaster multi-type emergency resource layout scheme as a decision variable; an improved bald eagle optimization algorithm is adopted, constraint conditions of a communication recovery basic framework are embedded, an outer layer optimization model is iteratively solved, and a pre-disaster resource deployment scheme which is most robust in all scenes is determined; constructing an inner-layer model by adopting mixed integer second-order cone programming, performing refined solution on post-disaster emergency response, and optimizing a pre-disaster resource deployment scheme; and constructing a double-layer robust optimization model to realize three-network emergency resource optimization. According to the method, the cooperative scheduling capability of multiple types of resources in pre-disaster, in-disaster and post-disaster stages can be improved, the guarantee capability of key loads is enhanced, and the method has global search capability and engineering adaptability.

The application discloses a kind of flight platform cluster's track planning method and device, the method includes: collection obtains task demand information set and flight platform cluster technical index information set;The task demand information set includes the execution position and demand information of each to be executed task;The demand information includes demand task type information and the demand value of all technical indexes;The flight platform cluster technical index information set includes the execution task type information, position information and technical index value set of each flight platform;The technical index value set includes several technical index values;The task demand information set and flight platform cluster technical index information set are preprocessed, and obtain preprocessed information set;The preprocessed information set is subjected to track planning processing, and obtains the track set of flight platform cluster.

The present application relates to the field of medical information technology, in particular to a medical consumable intelligent evaluation system fusing evidence-based medicine and personalized analysis. The system comprises a data fusion module, an evidence-based evidence management module, a personalized analysis module, a decision interaction module and a closed-loop feedback tracing module. The data fusion module integrates internal and external data of the hospital to generate a structured data set; the evidence-based evidence management module quantitatively grades the evidence and constructs a dynamic evidence database; the personalized analysis module combines patient characteristics and preferences, and outputs individualized multi-dimensional analysis results through a patient-surgery scene-consumable matching model; the decision interaction module generates structured options based on the analysis results, supports doctor-patient collaborative decision-making and records the process; the closed-loop feedback tracing module collects real-world feedback data for calibrating and iteratively optimizing the matching model. The present application realizes intelligent, reasonable and personalized evaluation of medical consumables, and improves the scientificity, interpretability and auditability of the evaluation.

The invention provides a steam generator heat transfer tube wear prediction and intelligent tube blocking method and system. The method comprises the steps that flow fields, vibration fields and wear databases of a heat transfer tube under different working conditions and positions are constructed through analogue simulation and real overhaul data of a nuclear power plant; constructing a training sample based on the constructed flow fields, vibration fields and wear databases of the heat transfer tube under different working conditions and positions; respectively training the flow field prediction model, the vibration field prediction model and the wear coefficient prediction model; during the unit overhaul period, operation data of a steam generator, position information of each heat transfer pipe and a supporting plate and corresponding abrasion data are obtained; respectively carrying out pretreatment; utilizing the trained flow field prediction model, vibration field prediction model and wear coefficient prediction model to predict the wear depth during the next overhaul; and judging whether the predicted wear depth during the next overhaul reaches or exceeds a set threshold value, and triggering and controlling the automatic pipe plugging operation when the wear depth reaches or exceeds the threshold value.

The invention discloses a power grid operation maintenance dispatching task management method, and belongs to the field of power grid operation maintenance, and the method comprises the steps: 1, obtaining dispatching demands, which comprise a normal dispatching demand and a temporary dispatching demand; normal dispatching demands and temporary dispatching demands are combined and managed in a unified manner to form a comprehensive dispatching demand pool; step 2, evaluating dispatching demand priorities, including evaluation dimension design and priority algorithm design; step 3, intelligently formulating dispatching tasks, including personnel allocation, historical data utilization and regional influence analysis; and step 4, recording the execution process of the dispatching task, including recording the execution process and intelligently scoring the task. According to the invention, each link of power grid operation maintenance dispatching task management is comprehensively improved, the timeliness and comprehensiveness of information acquisition are realized, and the efficiency and reliability of power grid operation maintenance are improved.

The invention discloses an endangered plant phoebe hainanensis identification and systematic monitoring method based on multi-source data fusion, and belongs to the technical field of endangered plant protection. According to the method, a potential distribution area is delineated through a species distribution model, individual accurate identification and filing are achieved through a multi-branch feature fusion model, multi-scale growth and microenvironment data are collected through Internet of Things nodes, and finally a'discovery-identification-monitoring-protection 'whole-process closed loop is formed through a unified data management platform. According to the method, phenological feature extraction, transfer learning modeling, man-machine collaborative verification and low-power-consumption Internet of Things monitoring technologies are adopted, and the problems that a traditional method is low in efficiency, insufficient in recognition precision and fragmented in monitoring are solved. According to the method, efficient discovery, accurate identification and long-term dynamic monitoring of the wild population of the phoebe hainanensis are achieved, scientific support is provided for protection decision making, and the method is convenient to operate and high in practicability and has protection value and application prospects.

The invention provides a government affair cloud service evaluation prediction method and system based on combination of improved TOPSIS and GRNN, and relates to the technical field of cloud service evaluation prediction. The method comprises the steps of collecting and preprocessing evaluation index data corresponding to government affair cloud services; calculating the weights of the preprocessed evaluation indexes by adopting an entropy weight method to obtain the weights of the evaluation indexes; according to the weight of each evaluation index, performing preliminary sorting on each evaluation index based on an improved TOPSIS method to obtain a preliminary evaluation result; according to each evaluation index corresponding to each government affair cloud service and the preliminary evaluation result thereof, training a prediction model constructed based on the GRNN; and inputting new evaluation index data of the government affair cloud service into the trained prediction model, and predicting to obtain an evaluation result of the government affair cloud service. According to the method, the accuracy and objectivity of government affair cloud service evaluation results are improved, and the calculation efficiency and real-time performance of the system are remarkably improved.

The invention provides a method for processing a bus driving plan after entering and exiting a parking lot at the same side. The method comprises the following steps: acquiring an original bus driving plan; the peak class with the odd number of shifts and the off-peak class with the odd number of shifts in any one of the morning peak segment and the evening peak segment are screened as adjustment classes; obtaining alternative departure time of feasible insertion shifts of the adjustment class; an integer programming model is established in an original public transport vehicle driving plan, an adjustment strategy of a class is adjusted, alternative departure time of a feasible insertion class of the class is adjusted as a decision variable of the integer programming model, and the integer programming model is solved by an adjustment target under a constraint condition to obtain a value of the decision variable; and adjusting the original bus driving plan according to the value of the decision variable to obtain a bus driving plan meeting the same-side entry and exit demand, and adjusting on the basis of the original bus driving plan to obtain a bus driving plan meeting the same-side entry and exit demand.

The invention discloses a water conservancy project construction archive management integrated system based on big data analysis, relates to the field of water conservancy projects, solves the problem of poor updating effect of water conservancy project construction archives, and comprises a water level monitoring module which is used for obtaining and analyzing natural water level deviation corresponding to each water level time detection point to obtain a regional water level change coefficient, the flow velocity monitoring module is used for acquiring and analyzing the water body flow velocity deviation corresponding to each flow velocity time monitoring point to obtain a regional flow velocity change coefficient, and the sediment monitoring module is used for acquiring and analyzing the sediment concentration deviation corresponding to each sediment time monitoring point to obtain a regional sediment change coefficient; and the archive management module is used for carrying out updating management on the water conservancy project construction archive corresponding to the target water conservancy project by analyzing the regional sediment change coefficient, the regional flow velocity change coefficient and the regional water level change coefficient. The water conservancy project construction archive management scientificity can be improved.

The invention discloses a short link generation method, a server, a storage medium and a program product, and relates to the technical field of internet information, and the method comprises the steps: obtaining user information, current time and an original webpage address; inputting the original webpage address into a preset hash function to obtain a hash value of a first length; generating a pseudo-random number according to the user information and the current time; inputting the pseudo-random number into a preset index calculation formula to obtain an effective index; on the basis of the effective index, selecting a continuous character with a second length from the hash value as a hash short code; performing security review on the Hash short code to ensure that the Hash short code does not have preset sensitive vocabularies, preset easily-confused characters and / or preset known vulnerabilities; and if the result of the security review is safe, encoding the Hash short code according to a preset link generation parameter to obtain a final short link. By implementing the method, the security of short link generation can be improved.

The invention discloses a goaf ecological restoration method and device, and the method comprises the steps: collecting various ecological data of a goaf, and calculating an ecological health index of the goaf according to the ecological data; according to the ecological data and the ecological health index, utilizing an ecological restoration model based on machine learning to output an ecological restoration strategy of the goaf; collecting various ecological data after the goaf is restored by using the ecological restoration strategy to calculate an ecological health index after the goaf is restored, and judging whether the ecological health index exceeds a preset threshold value or not; and if the calculated ecological health index does not exceed the preset threshold value, returning to execute the step of outputting the ecological restoration strategy of the goaf by using the ecological restoration model based on machine learning according to the ecological data and the ecological health index until the calculated ecological health index exceeds the preset threshold value. By means of the goaf ecological restoration method and system, scientization and precision of goaf ecological restoration can be achieved through ecological data collection and analysis of the system.

The application provides a kind of city granularity-based vehicle transfer path calculation method, system and terminal machine, belongs to the field of vehicle path planning, constructs adjacent city data network;Vehicle path data network is constructed;According to the input condition, the shortest path between nodes is calculated using Dijkstra algorithm, and the strategy of greedy algorithm is adopted, the adjacent nodes of the vertex closest to the starting point and not visited are traversed each time, until the end point is expanded, to obtain the hottest route between any two nodes or multiple nodes.The method is based on the actual vehicle operating conditions, from the perspective of city transfer, analyzes the transfer trend and heat between cities, and provides an effective method for finding popular routes, with strong practical value.

The present invention discloses a method and system for constructing a lifting path planning model, and relates to the technical field of lifting path planning. The method comprises: collecting historical cargo loading and unloading task data and historical status information of obstacles; wherein the historical cargo loading and unloading task data includes the starting point data and the landing point data of the cargo; obtaining the first operation data of the first crane on four degrees of freedom during the execution of the historical cargo loading and unloading task; wherein the four degrees of freedom include lifting, amplitude change, rotation and telescopic; obtaining the second operation data of the second crane on four degrees of freedom during the execution of the historical cargo loading and unloading task; constructing a lifting path planning model according to the starting point data, the landing point data, the first operation data and the second operation data; the lifting path planning model is constructed based on a deep reinforcement learning network. The present application realizes the accuracy of cargo loading path planning.

The application discloses a spoken language evaluation system and method based on multiple dimensions, and relates to the technical field of data processing.The system comprises the following steps: obtaining audio text, a phoneme list and a phoneme time boundary list corresponding to speech data according to a pre-trained text phoneme recognition model; calculating a fluency score according to the phoneme list and the phoneme time boundary list; obtaining a semantic score of the audio text through a pre-trained semantic model; obtaining a syntax score of the audio text through a pre-trained syntax model; matching the audio text and an answer text according to a text matching method based on an edit distance to obtain a text matching score; obtaining a pronunciation score of the audio data finally through phoneme confidence of the phoneme list; dynamically adjusting the weight of each dimension score according to the length of the audio text, and calculating a final spoken language evaluation score; and the application comprehensively evaluates the spoken language ability through multi-dimensional evaluation and dynamic weight adjustment according to the scene, and realizes the comprehensiveness, fairness, accuracy and high efficiency of the spoken language evaluation.

An implementation method of intelligent agricultural planting decision support based on big data analysis, including: equipping with diversified sensor equipment and remote sensing technology, monitoring various indicators of farmland environment, integrating external relevant information; using the entropy-based weighted principal component analysis (PCA) method to clean data, and introducing the construction of spatiotemporal sequence features under the geographic space coordinate system; applying statistical big data analysis technology to construct an environment-crop response model and resource demand prediction model based on big data analysis; using the particle swarm optimization algorithm (PSO) based on adaptive learning weights and multimodal search to perform global optimization search and formulate planting decision strategies. The implementation method of intelligent agricultural planting decision support based on big data analysis realizes the intelligence of the entire process from data collection, processing, analysis to decision generation, and provides scientific, accurate, and real-time planting decision support for agricultural producers, with significant application value and broad market prospects.