46 results about "Integration algorithm" patented technology

The invention discloses a moon leap trajectory planning method, system and device and a medium. The method comprises the steps of obtaining target landing point data; based on the acquired data, establishing a moon surface leap device kinetic model by defining a specific coordinate system and a state variable; based on the kinetic model, discretizing the kinetic equation through a numerical integration algorithm, constructing and solving a leap trajectory convex optimization problem with optimal burnup, and obtaining an obstacle avoidance-free optimal trajectory; based on the obstacle avoidance-free optimal trajectory, performing obstacle avoidance iteration through an iteration obstacle increase strategy to obtain a static obstacle avoidance trajectory; and on the basis of the static obstacle avoidance trajectory, the flight trajectory is adjusted again by calculating the trajectory error band width and the maximum extension distance, and a dynamic safety enhanced trajectory is obtained. According to the method, safe, robust and efficient moon surface leap trajectory planning in a complex and uncertain environment is realized.

The invention discloses a three-dimensional design model conformity analysis method and system based on a large language model, and the method comprises the steps: obtaining the related data and design specification constraint conditions of a three-dimensional design model, and building a data interaction channel through a collaborative review platform; calling a semantic geometry collaborative verification algorithm to process the data and extracting feature parameters; generating a rule adaptation weight matrix through a space rule learning adaptation model; constructing a mapping relation between the feature vector and the design specification through a CAD point cloud feature coding mapping model; carrying out multi-dimensional conformity verification on the basis of the result; and outputting the comprehensive analysis data set. The system realizes deep cooperative processing of geometric and semantic data of a three-dimensional design model through multi-unit cooperative linkage and integration of an algorithm and a platform function, improves the accuracy of rule adaptation and feature mapping, comprehensively covers a conformity verification dimension, and meets a high-precision analysis requirement in a complex scene.

The invention provides a training method for aero-engine modeling driven by mechanism and data fusion, and relates to the technical field of aero-engine modeling simulation, and the method comprises the steps: decomposing a simulation model of an aero-engine into a plurality of assemblies containing to-be-identified unknown parameters, and employing an assembly integration algorithm to associate the plurality of assemblies, an end-to-end differentiable complete simulation model is formed; based on hierarchical division of the simulation model, performing parameter pre-estimation by adopting a top-down layer-by-layer progressive strategy to obtain an initial estimation value of the unknown parameter; the strategy comprises the following steps: firstly, estimating unknown parameters of components in a highest level according to actually measured output data, and generating a training target of a next lower level based on a calculation result of an estimated level so as to complete estimation of unknown parameters of the lower level in sequence; and performing gradient back propagation in the complete simulation model by taking the initial estimation value as a starting point to optimize and update unknown parameters.

The invention belongs to the field of aerospace electronic measurement, and provides an inductance type proximity sensor resolving method and system based on a time domain integration algorithm, and the method comprises the steps: applying a generated sine excitation voltage to a measurement loop; synchronously acquiring sine excitation voltage and response voltage of an inductive proximity sensor in a measurement loop; based on a time domain integration algorithm, respectively carrying out orthogonal integration on the sine excitation voltage and the response voltage, and calculating respective amplitudes and phases; according to the amplitude, the phase and the resistance value of the reference resistor, an inductance value and a parasitic resistance value of the inductive proximity sensor are calculated through a trigonometric function relationship; and establishing a piecewise linear fitting model through a least square method, and calibrating the inductance value to obtain a calibrated inductance value. The method has the advantages of high reliability, strong anti-noise capability, no need of complex electronic hardware, and reduction of the development cost at a lower development guarantee level.

The invention belongs to the technical field of machine learning, and particularly relates to an algorithm research based on GNN multi-mode lightweight and edge computing fusion integration, which comprises the following steps: step 1, acquiring sensor data from at least two different modes; and 2, constructing the multi-modal data into a uniform heterogeneous graph, wherein the data of different modals are expressed as nodes or edges of different types. According to the method, a unified heterogeneous graph is constructed, and data from different sources are mapped into different types of nodes or edges in the graph. Then, through a cross-modal attention mechanism, dynamically learning association strength and an interaction mode between different modal nodes, and realizing end-to-end multi-modal information deep fusion in a GNN message transmission process, thereby avoiding information loss caused by simple splicing or later fusion in a traditional method; the cross-modal attention mechanism can dynamically calculate and allocate importance weights of different modals according to specific input samples and contexts.

The application discloses a kind of composite heavy metal pollution site three-dimensional identification and earthwork volume estimation method and system, and it is related to computer data processing technical field.Target site survey data is obtained and engineering voxel space resolution is set, and the chemical action parameter between heavy metals is extracted to construct composite spatial variation function.Three-dimensional distribution model is constructed using three-dimensional space interpolation, and preliminary pollution spatial grid set is extracted according to risk control threshold discretization.Boole logic operation is introduced to cross screen out single and composite heavy metal pollution area, and three-dimensional engineering boundary is obtained by boundary topology reconstruction with minimum mechanical construction envelope as constraint, and then the corresponding pollution total volume is estimated using spatial volume integration algorithm.The application can output three-dimensional boundary with engineering excavation continuity and realize accurate estimation of various pollution quantities.

The invention discloses an efficient simulation method for collision between long ellipsoid particles and a wall surface based on discrete elements, and belongs to the technical field of gas-solid two-phase flow numerical simulation. The method comprises the steps that a universal long ellipsoid particle-wall surface collision elastic force model is established, and the model represents a universal function relation between elastic force and particle geometry, material attributes and kinematics state parameters; based on the elastic force model and the momentum theorem, constructing a particle-wall surface collision dynamic model; based on the kinetic equation, a discrete time method and a numerical integration algorithm are adopted, and force, speed and energy parameters, changing along with time, of the long ellipsoid particles and the wall face in the whole collision period are solved. According to the method, the analytic model is embedded into a discrete element simulation framework to replace calculation-intensive finite element solution, so that second-level efficient solution is realized while the calculation precision is ensured, and the calculation efficiency is remarkably improved.

The invention discloses a space-time multi-parameter cooperative computing method and system based on a universe model, and relates to the technical field of universe and celestial body physics computing. According to the method, an integral kernel function is constructed based on an FLRW degree gauge of a standard universe model, redshift and universe densitology parameters input by a user are received, a Friedemann equation is calculated by using a Gauss-Kronrod adaptive numerical integration algorithm, basic quantities such as co-movement distance and time are solved, and the cosmic movement is realized. And deriving derivative parameters such as co-dynamic volume, angular diameter distance, luminosity distance, universe age, light running time and the like according to universe curvature types (flatness, opening and closing). The system comprises a parameter input module, a core integral calculation engine, a geometric model judgment module, a multi-type distance and derivative parameter calculation module and a result output module. According to the method, the problems of low calculation precision and poor model adaptability in the prior art are solved, a high-precision (error is less than or equal to 10 <-7 >) self-adaptive universe calculation solution with comprehensive parameter coverage is provided, and a powerful calculation tool is provided for universe research and astronomical observation data analysis.

The present application belongs to the field of lithium battery SOC calculation, and particularly relates to a lithium battery SOC estimation method based on high-precision ampere-hour integral algorithm. The method comprises establishing an ampere-hour integral mathematical model and solving, and performing Taylor expansion on the solution; the average slope is obtained by means of linear combination of three-point slope by investigating the slope of two points in the interval, so as to ensure that the precision of the third-order Taylor expansion formula and the equivalent formula is the same. When the algorithm is executed, the charge state and the capacity value are initialized first, then the sampling time is obtained according to the sampling frequency, and then the relevant parameters are calculated according to the current sampling value, and finally the current SOC is calculated according to the specific value and the three slopes and is iterated in a loop. This method can improve the ampere-hour integral precision, and weaken the cumulative error and SOC jump.

The invention provides a switched reluctance motor speed regulation system fault diagnosis method based on an adaptive sliding window integration algorithm, and relates to the technical field of motor speed regulation system fault diagnosis. The method comprises the following steps: firstly, collecting current of each phase under different working conditions to construct fault data, extracting features through normalization and harmonic analysis, obtaining fault features through feature selection, and training a plurality of integrated learning classifiers and neural network classifiers; collaborative decision making is sequentially carried out on data to be diagnosed in the graded sliding window, rapid and accurate online identification of single-tube short circuit and winding turn-to-turn short circuit faults is achieved, and the stability and reliability of a speed regulation system are improved.

The application provides a photovoltaic array fault diagnosis method based on a composite model soft voting integration, and comprises the following steps: acquiring a plurality of P-V curve data of a photovoltaic array in normal operation and when a fault occurs; preprocessing the plurality of P-V curve data, formulating a fault type label and dividing processing, obtaining a training data set and a test data set; constructing a plurality of composite sub-models, integrating the composite sub-models based on a soft voting integration algorithm, determining each hyperparameter of an integrated diagnosis model based on a global optimization algorithm, and completing the construction of the integrated diagnosis model; inputting the training data set into the integrated diagnosis model for training to obtain a trained integrated diagnosis model; inputting the test data set into the trained integrated diagnosis model to test and evaluate the performance thereof; and diagnosing the photovoltaic array through the integrated diagnosis model to determine the fault type of the photovoltaic array.

The invention relates to a multi-agent collaborative decision-making method and device, and belongs to the technical field of multi-agent collaborative decision-making. The method comprises the following steps: each agent performs joint perception and feature coding on acquired multi-modal input data through a data perceptron; fusing and updating the current multi-modal representation vector and the historical representation set by using a data updater and adopting a time sequence increment consistent integration algorithm; the fused codes are compressed through a data transmitter and sent to an adjacent agent; each agent receives coding information from an adjacent agent through a data receiver, and the coding information is aligned and fused with a fusion code of the agent; and the data updater adopts a multi-level weighted feature pyramid algorithm to update the fusion representation, and new historical representation data is generated to support the next round of collaborative decision. According to the multi-agent collaborative decision-making method, the reliability and robustness of multi-agent collaborative decision-making are improved through the four core components including the data sensor, the data updater, the data transmitter and the data receiver.

The application discloses a three-dimensional code integrated query method for a compatible database and an operating system thereof, and the three-dimensional code integrated query method is characterized in that: by adopting the theory of three-dimensional code positioning, endless massive ordered and disordered information is stored and positioned in a three-dimensional mode and is quickly queried; the principle is that letters and numbers are the basis for processing all information by a computer, for example, Chinese character input is implemented by using numbers or letters as codes to effectively process information, and a permanent corresponding relationship between letter combinations and numbers is established; the application relates to the technical field of data processing. The three-dimensional code integrated query method for the compatible database and the operating system thereof can realize unified integration of data in a plurality of sub-databases through a three-dimensional code integration algorithm in a parent database, and can form a precise unique three-dimensional code for positioning storage, so that the purpose of quickly and accurately obtaining required data information in the database is achieved.

The present application relates to the technical field of data processing, and more particularly to a novel arbitrary polygonal element calculation method for structural simulation analysis, comprising obtaining a geometric model and extracting node coordinate data, calculating polygonal element center point and edge midpoint coordinates to form an extended coordinate data set, generating quadrilateral sub-element topology through geometric connection operation, establishing strain displacement relationship and fusing equivalent strain matrix data through constraint equation calculation, adopting single point integration algorithm and hourglass control algorithm for numerical integration and stability correction, outputting stiffness matrix data controlled by hourglass, integrating into a finite element solving system for numerical solving, and calculating stress and strain distribution based on node displacement data. The present application overcomes the low efficiency and poor accuracy problem caused by the dependence of the prior art on sub-element decomposition, and improves calculation stability and engineering applicability.

The invention discloses an energy storage equipment operation state monitoring method based on artificial intelligence, and belongs to the technical field of energy storage equipment monitoring. According to the method, multi-dimensional data are collected through sensors of an equipment layer, an environment layer and a power grid layer, a 1: 1 three-dimensional digital twin with an equivalent circuit, an electrochemical model and a thermal model coupled is constructed, digital twin parameters are optimized through DDPG reinforcement learning, a state prediction model is trained through a Transform-ConvLSTM hybrid network, and fault diagnosis and multi-level early warning are achieved in combination with a knowledge graph. The method supports incremental learning, can dynamically adapt to equipment aging and environment change, and guarantees the full-life-cycle monitoring precision through a Fisher information matrix and an elastic weight integration algorithm. Compared with the prior art, the method solves the problems of insufficient multi-dimensional data fusion, weak dynamic modeling capability and the like, realizes operation state monitoring and fault early warning of the energy storage equipment, and improves the operation safety and operation and maintenance efficiency of the equipment.

The present application relates to the technical field of data prediction, in particular to a swelling soil swelling evaluation model construction method and system, comprising the following steps: collecting wetting and drying cycle data to construct closed state evolution coordinate sequence, using trapezoidal numerical integration algorithm to calculate single cycle hysteresis energy dissipation density, calculating structure damage increment to update structure integrity coefficient, constructing suction stress contribution factor and correcting real-time matrix suction, superimposing to obtain equivalent effective stress, using Lagrange interpolation combined with pore ratio relationship table to calculate pore ratio change and volume expansion rate. In the present application, the structure damage and integrity degradation are quantified by calculating the hysteresis energy dissipation value, the stress state is corrected by constructing the suction stress contribution factor, and the pore ratio change is deduced, thereby establishing a mechanical property prediction system based on energy dissipation and structure evolution, overcoming the limitations of static physical index evaluation, and significantly improving the prediction accuracy and applicability of swelling soil volume deformation.

The invention discloses a multi-stage separation process simulation efficient DLPT general solving method and system and application, and relates to the technical field of chemical process simulation, and the method comprises the steps: obtaining the initial condition of a multi-stage separation differential algebraic model; determining simplified physical property model parameters according to the initial conditions; performing iterative solution on the differential algebraic equation set based on the simplified physical property model parameters and an integral algorithm; and outputting a final calculation result. The efficient DLPT general solving method and system for simulating the multi-stage separation process and the application have the advantages that the PT algorithm is low in initial value requirement and wide in convergence domain, the inner-layer strategy and the outer-layer strategy are introduced, a simplified physical property model is used in the inner-layer integration process, calculation time consumption is greatly shortened, the inherent speed bottleneck problem of the PT algorithm is solved, and the calculation efficiency is improved. And the balance between convergence robustness and calculation efficiency is realized.

The invention discloses an artificial intelligence behavior optimization system based on collaborative evaluation and comprehensive decision, and belongs to the technical field of artificial intelligence safety. Comprising an input interface module, an intelligent response generation unit, a safety compliance evaluation unit, a decision fusion center and a result optimization controller. The input interface module is used for receiving instruction data input by a user; and the intelligent response generation unit is connected with the input interface module and is used for generating a plurality of candidate responses based on a pre-trained generative artificial intelligence model and calculating an efficiency index for each candidate response. Through a unique co-processing architecture, security assessment is deeply fused into a decision generation link, risk is avoided from the source, computing resource waste and delay caused by serial filtering are eliminated, the index integration algorithm unifies efficiency and security targets on the system level, and the security assessment is more efficient and more reliable. And guiding the system to find an optimal solution within the security boundary.

The invention discloses a cross-regional tie line power fluctuation suppression method based on deep learning, and belongs to the field of deep learning. The method comprises the following steps: designing a tie line power fluctuation suppression controller: driving new energy to quickly adjust power, and dynamically suppressing tie line power fluctuation; calculation of active power modulation quantity distribution: constructing a voting-based decision-making mechanism, and reasonably distributing control measures of the new energy station; the gain value of the total modulation amount is calculated, specifically, the gain value is calculated by using the boosting regression integration algorithm with the minimum active modulation amount as the target. According to the method, the boosting algorithm and the voting mechanism are applied to tie line power control for the first time, compared with a traditional control method, the method has the advantages of being high in response speed, high in control precision and excellent in economical efficiency, and cascading failures caused by the fact that power transmission in the transient process exceeds the static stability limit after a tie line fault occurs are avoided; and the method has important significance for ensuring safe and stable operation of a large-scale interconnection system.

This invention discloses a dynamic simulation method, system, computer, and storage medium for a space thin-film antenna system based on the absolute nodal coordinate method. The space thin-film antenna is simplified into a rigid-flexible coupled multibody system composed of a flexible support frame, a tensioned cable net, and a thin-film reflector. Nonlinear cable elements are introduced between the frame and the thin film as connections. The flexible frame and the non-bending stiffness thin film are divided into elements based on the absolute nodal coordinate method. According to the theory of continuum mechanics and the principle of virtual work, a dynamic model of the flexible frame-cable net-thin film coupled multibody system under pretension is established. A form-finding strategy for gentle slope loading is proposed. The generalized -α implicit time integration algorithm is used to solve the dynamic equations of this system, obtaining curves showing the displacement and vibration attenuation of the space thin-film antenna under impact disturbance as a function of time. This invention provides a new dynamic modeling model for large-scale space thin-film antenna systems and offers researchers in this field more comprehensive data and image data.

The invention discloses an electric power inspection work order trend prediction method and system based on a large language model. The method comprises the following steps: collecting text data of an electric power inspection work order and time sequence data of work orders with similar problems, and carrying out data preprocessing; extracting multi-dimensional time sequence features from the time sequence data; semantic features of the text data are extracted; carrying out feature alignment and fusion on the time sequence features and the semantic features by adopting a self-adaptive gating fusion mechanism; after time sequence decomposition and semantic binding are carried out, multi-resolution time imaging and seasonal component and trend component decoupling are carried out; and carrying out multi-scale and multi-resolution mixing on the seasonal image and the trend image to obtain a final feature of each scale, and predicting a work order quantity variation trend of the same kind of problems by adopting an attention-based dynamic integration algorithm. According to the invention, accurate prediction of the work order change trend of similar problems can be realized.

The invention provides a high-precision dynamic simulation method and system suitable for a special vehicle in a complex environment, and the method comprises the steps: constructing a multi-body system dynamic model which comprises a cabin body, a suspension, a tire and ground coupling relation, and describing the pose and motion state of each part through an absolute node coordinate method; establishing a three-dimensional complex terrain model containing an E-level random pavement, a convex obstacle and a side-tipping ramp, and taking the three-dimensional complex terrain model as external excitation input; the three-dimensional complex terrain model is coupled with the multi-body system dynamics model, a tire-ground nonlinear contact system is constructed, and tire-ground interaction force is calculated in real time; constructing a discrete solver of a vehicle system dynamics equation set based on a pungent integral algorithm, and realizing time integration and evolution of a system state through numerical iteration; and outputting dynamic response parameters of the vehicle in a complex environment, including acceleration, speed and displacement of a cabin mass center, suspension contact force and tire impact load, for cabin structure strength analysis and comfort evaluation.

The invention discloses a resolving method and system for flight path simulation of a solar unmanned aerial vehicle, and belongs to the technical field of flight mechanics simulation. The method comprises the following steps: firstly, deducing a three-degree-of-freedom mass point motion equation, and constructing a core calculation equation which only takes a flight speed as an independent variable; then, solving the equation by applying a Newton iteration method to obtain numerical solutions of the flight speed and the trajectory angle; and finally, in combination with a kinematics equation, continuously solving at different flight heights, and simulating a complete flight trajectory. The method can effectively replace traditional trajectory integration algorithms such as a fourth-order Runge-Kutta integration method, and is suitable for full-stage trajectory calculation of climbing, level flight, gliding and the like of the solar unmanned aerial vehicle. According to the method, an iteration initial value does not need to be set, the calculation process is stable and efficient, the deterministic convergence characteristic is achieved, and the method can be widely applied to flight path simulation and performance analysis of various fixed-wing aircrafts with electric propellers as power.

The application provides a bearing capacity prediction model construction method of a flexible photovoltaic support composite cable-stayed foundation, and belongs to the technical field of photovoltaic support detection. The application establishes a soil fractional order viscoelastic plasticity constitutive database, and obtains equivalent macroscopic constitutive parameters by using a multi-scale homogenization algorithm of a variational asymptotic method. In combination with a symplectic geometry structure-preserving dynamics integration algorithm, the coupling relationship between cable force and displacement is iteratively calculated, multi-working-condition bearing capacity simulation calculation is performed to obtain foundation settlement, cable force distribution and soil plastic zone range. Pretreated simulation data is input into a fractional order memory enhancement model to perform bearing capacity prediction. Iterative optimization is performed according to the deviation rate of the limit bearing capacity prediction value and the design bearing capacity, so that the technical problem of insufficient accuracy of the bearing capacity prediction of the flexible photovoltaic support composite cable-stayed foundation under the coupling action of soil long-term creep and cable force is solved.

The invention provides a multi-flexible-body coupling dynamics modeling method and device for a rotary non-inertial system gear system, and the method comprises the steps: dividing the gear system into a shaft system substructure and a box body substructure, and respectively building the kinematic equations of the shaft system substructure and the box body substructure; a generalized coordinate kinetic equation of the box body is obtained, the generalized coordinate kinetic equation comprises fixed-axis rotation coordinates and flexible node coordinates, and the non-inertial system effect of random body rotation is included; a shaft system generalized coordinate kinetic equation is obtained, discretization is carried out, and a composite motion effect is included; performing order reduction on the box body and the shaft system through a state space fixed interface modal synthesis method, retaining interface nodes and mapping internal nodes to a low-order modal space; bearing coupling is achieved through multi-point constraint, and shafting bearing force is equivalently distributed to flexible joints of a box body; establishing a gear meshing coupling model, and loading a gear backlash, a meshing error and time variable stiffness; and all subsystem equations are coupled to form an integral reduced-order model, and a dimension-increasing fine integration algorithm is adopted for solving. The invention provides an efficient and accurate tool for the design of a gear transmission system.

This invention discloses a method for calculating the dynamic hydraulic replacement cycle of a reservoir based on an inverse integral algorithm. The method includes: responding to a hydraulic replacement cycle calculation request, determining a second time interval matching a first time interval; obtaining the daily average inflow of the target reservoir within the second time interval, forming a daily average inflow time series; forming a daily average reservoir capacity time series based on the daily average inlet water level of the target reservoir within the first time interval, and the relationship curve data between the measured inlet water level and reservoir capacity; and using the daily average inflow time series and the daily average reservoir capacity time series, searching for preceding related days corresponding to each day within the first time interval using an inverse integral algorithm, and generating the daily hydraulic replacement cycle of the target reservoir within the first time interval. This invention enables the accurate construction of the dynamic water replacement process under unsteady runoff conditions, improving the accuracy and robustness of hydraulic condition assessment methods.

The invention discloses a fluid-structure interaction dynamics simulation analysis method of a nuclear reactor control rod drive line under a multi-point excitation load. The method comprises the following steps: firstly, obtaining a fluid resistance rule in a control rod falling process in advance through fluid simulation and fitting a quantitative relation; secondly, simulating incomplete elastic collision and friction between the control rod and the guide structure by adopting a contact model based on a lubrication theory; and finally, on the basis of commercial finite element software, in each step of transient dynamic analysis, calculating and applying corresponding fluid force according to the real-time motion state of the control rod to realize fluid-structure interaction simulation, and supporting an explicit time integration algorithm and an implicit time integration algorithm. According to the method, the rod dropping process can be completely and accurately simulated, the simulation process is standardized, the use complexity is reduced, and an efficient and reliable virtual experiment means is provided for safety design and performance optimization of the control rod drive wire.

The invention provides a document content analysis and identification method and device, electronic equipment and a storage medium, and relates to the technical field of document processing. According to the method, a to-be-analyzed document is input into a preset detection model comprising a controllable receiving module, a preset integration algorithm and a global-to-local design structure, and content features corresponding to at least one page in the to-be-analyzed document are obtained according to the controllable receiving module; according to the content features and a preset integration algorithm, obtaining corresponding integration features; according to the method and the device, the to-be-analyzed document is obtained, the integrated features are input into a global-to-local design structure, a detection positioning mode for obtaining the document content in the to-be-analyzed document is obtained, and finally the document content in the to-be-analyzed document is identified and obtained based on the detection positioning mode, so that the structural integrity of PDF document analysis and identification is optimized, and the PDF document analysis and identification accuracy is improved.

The invention relates to the technical field of data prediction, in particular to an expansive soil expansibility evaluation model construction method and system.The expansive soil expansibility evaluation model construction method comprises the following steps that moisture absorption and dehumidification cycle data are collected to construct a closed state evolution coordinate sequence, and the single-cycle hysteresis energy dissipation density is calculated through a trapezoidal numerical integration algorithm; and calculating a structural damage increment and updating a structural integrity coefficient, constructing a suction stress contribution factor and correcting real-time matric suction, performing superposition to obtain equivalent effective stress, and calculating a void ratio variation and a volume expansion rate by utilizing Lagrange interpolation and combining a void ratio relation table. According to the method, structural damage and integrity decline are quantified by calculating a hysteresis energy dissipation value, a suction stress contribution factor is constructed to correct a stress state, void ratio change is deduced, a mechanical property prediction system based on energy dissipation and structural evolution is established, and the limitation of static physical index evaluation is overcome; and the volume deformation prediction accuracy and applicability of the expansive soil are remarkably improved.

The invention discloses a robot path planning method based on a fuzzy reasoning spiking neural P system, and aims to solve the technical problem that an existing heuristic path planning algorithm is easy to fall into a local optimal solution. According to the method, nodes and path proposition neurons are introduced into a traditional fuzzy reasoning spiking neural P system, a search tree is correspondingly established by utilizing the plasticity of a spiking neural P system structure, so that a feasible path formed by a node set is obtained, and fuzzy information of a local solution is obtained based on regular neurons with a membership function; and fuzzy information of a global solution is obtained through normalization processing, so that the system is prevented from falling into a local optimal solution. Besides, a node integration algorithm based on three rule neurons of length, smoothness and safety can effectively reduce the dimensionality of an inference matrix and accelerate the convergence speed; and through a path repairing algorithm, the problem of sudden path conditions caused by dynamic obstacles is solved.