168 results about "Path (graph theory)" patented technology

The invention relates to the technical field of intrusion detection, in particular to a network threat detection method and system, and the method comprises the following steps: building a threat path logic diagram through collecting field dependency items, action trigger timestamp items and action propagation hop count items of an attack behavior chain, and matching field dependency items among nodes based on a graph theory algorithm to obtain a threat path logic diagram; and detecting a mutual exclusion logic field combination, and generating a logic diagram structure with a connecting edge and a mutual exclusion mark. In the method, a threat path logic diagram is constructed by fusing field dependence, action timestamps and propagation hops, graph theory identification field mutual exclusion combination enhances cross-protocol attack chain analysis, and hidden Markov modeling state transition probability verifies time sequence continuity and path length. And performing dynamic time warping alignment on forward and reverse instruction sequences to extract semantic offset, overlapping rate and time sequence entropy, and performing non-linear score classification based on an isolated forest to detect an adversarial sample, topological structure analysis, time sequence verification, instruction alignment and non-linear classification to cooperatively identify a composite attack with field mutual exclusion and time sequence confusion.

The invention provides a method and a system for detecting and defending cross-domain threats of a power system. The method comprises the following steps: after carrying out anomaly identification on operation monitoring data of a physical domain node in a target power grid region to obtain an anomaly identification result and carrying out denial of service attack identification according to network flow data of an information domain node to obtain an attack identification result, carrying out abnormal event association analysis on the anomaly identification result and the attack identification result to obtain an attack cross-domain anomaly identification result; according to key nodes and key risk propagation paths in a cross-domain attack chain generated based on a graph theory algorithm, generating an attack tracing atlas, and according to vulnerability information of the key nodes in the atlas, obtaining a corresponding power system topological graph and a corresponding communication network topological graph; and iteratively generating an active defense rule based on a game theory algorithm and a reinforcement learning algorithm, and issuing the active defense rule to the node. According to the method, the cross-domain attack risk is accurately perceived in real time and adaptive security defense is executed through cross-domain abnormal event association analysis, so that the comprehensiveness and reliability of security protection of the power system are improved.

The invention discloses an unmanned aerial vehicle group cooperative inspection control method for power station inspection, and the method comprises the steps: determining an unmanned aerial vehicle group according to a power station inspection task; performing task allocation of the heterogeneous unmanned aerial vehicle cluster by using a multi-objective optimization algorithm; performing unmanned aerial vehicle path planning by adopting an improved dynamic multi-population particle swarm algorithm; based on a graph theory and master-slave control, unmanned aerial vehicle group attitude consistency control is realized; integrating a target detection technology based on deep learning, and constructing an inspection anomaly detection model; performing remote fault diagnosis analysis on the real-time inspection data through an inspection anomaly detection model to obtain an inspection anomaly result; optimizing the inspection anomaly detection model according to the target condition of the real-time inspection data; and dynamically controlling task allocation and path planning of the unmanned aerial vehicle group according to an abnormal inspection result. Through the scheme, potential problems can be found and processed in time, the intelligent control level of power station inspection is improved, and the efficiency and accuracy of unmanned aerial vehicle group cooperative inspection are improved.

The invention discloses a disaster emergency rescue command system and method, and relates to the technical field of rescue command systems. Comprising an information collection module which collects information, including disaster situations, personnel distribution and environmental conditions, of a disaster site through sensors and communication equipment; the collected information is input into the system, so that accurate disaster assessment can be conveniently obtained; the decision support module determines optimal allocation of rescue resources by using a linear programming model according to disaster assessment provided by the information collection module, and plans a rescue path by using a graph theory algorithm; and the command control module is used for converting the rescue decision of the decision support module into a specific rescue instruction. According to the system, the disaster assessment time can be shortened through real-time monitoring and rapid data processing, and the rescue decision-making speed is increased; optimal configuration of resources is realized through an algorithm, resource waste is avoided, and resource availability at a critical moment is ensured.

The invention provides an intelligent actual measurement and quantity management method and system for a building. The method comprises the following steps: capturing environmental parameters, material circulation paths and spatial geometric information of key parts of a building in a construction process in real time to obtain a measurement data set; a distributed ledger technology is combined with a homomorphic encryption algorithm, a graph theory analysis technology is applied to evaluate a dependency relationship among operation points of a construction site, and a data log is generated; according to the data log, using an augmented reality technology to superpose a BIM model, introducing a support vector machine algorithm to carry out automatic classification and risk assessment processing on deviation data between measured data and preset standard data, and generating a rectification suggestion report; and a closed-loop quality management process is formed by continuously collecting rectification effect feedback. According to the technical scheme, high transparency and efficient quality control in the construction process are ensured.

The invention provides a fire-fighting escape guiding method based on a sensor, and the method comprises the steps: calculating a safe evacuation path and evacuation facilities through a graph theory algorithm according to a building structure model and the position information of escapers in combination with a fire spreading trend, a fire spreading speed and a fire spreading direction; according to the fire development situation and a preset trigger threshold value, the updating frequency of fire induction and evacuation alarms is dynamically adjusted, and it is ensured that real-time alarms transmitted to escapers have perspectiveness and accuracy; fire induction information and evacuation alarms are dynamically pushed to escapers at different positions through electronic display equipment or sound prompts, and evacuation paths and facilities which should not go to or be used at present are informed; according to the real-time position of the escaper and the fire development condition, the induction direction and the evacuation path are continuously optimized, and the accuracy and the real-time performance of user safety induction and evacuation alarm are ensured.

The invention relates to the technical field of computer networks, and discloses a method for locating reasons for network dial test quality index abnormity, which comprises the following steps of: multi-source data acquisition and network topology modeling: generating state information of network equipment and links by acquiring performance data of each equipment and flow data of the links in a network, and establishing a network topology model; establishing a network topological graph model; shortest path calculation and abnormal path identification based on the graph theory: calculating a shortest path from source equipment to target equipment by using a shortest path algorithm in the graph theory, and identifying abnormal links and equipment in the path; and load evaluation and bottleneck analysis based on an information theory. Through combination of multi-source data acquisition, graph theory optimization, information theory evaluation, game theory resource allocation, deep reinforcement learning and multi-target optimization, network paths and loads are dynamically adjusted, abnormal sources are accurately positioned, and network performance, stability and adaptive capacity are improved.

The invention discloses a graph theory-based industrial internet identification system full-process tracing method, which realizes full-process tracing in a supply chain by introducing identifier fields into metadata and constructing a directed graph structure. The identifier fields include fields with similar representations for representing associations of the product upstream and downstream of the supply chain. The system queries across enterprises through a graph traversal algorithm (such as depth-first search (DFS) or breadth-first search (BFS)), and tracks the full life cycle of a product. The method supports attribute pointing code management, is used for tracing multi-attribute information (such as allocation weight, time and the like) of a product, solves cross-enterprise and cross-system coding differences through an alias mechanism, and simplifies a tracing process. The method has a flexible traceability path setting capability, can monitor the product circulation process in real time, gives out an early warning when an abnormality is found, and improves the transparency and safety of a supply chain.

The invention relates to the technical field of artificial intelligence and educational informatization, and discloses a teaching application system optimization method based on local knowledge base and AI association, comprising the following steps: constructing a dynamic knowledge graph, the graph comprising a plurality of nodes, each node representing a subject knowledge point, each edge representing a derivation relationship between the nodes, a reasoning path between the subject knowledge points is optimized through a graph theory shortest path algorithm; a space-time attention mechanism is introduced, weighted fusion is carried out on multi-modal data according to learning states of students, and different modal data including weighted weights of texts, images and audios are adjusted. According to the technical scheme, graph theory reasoning is combined with dynamic knowledge graph construction, the technical effects of automatically optimizing a subject knowledge point derivation path and improving the knowledge retrieval efficiency are achieved, and the problems that the reasoning path between knowledge points is lengthy and the retrieval efficiency is low are solved.

The invention discloses a splicing curved surface reinforcement method fusing a graph theory and UV parameterization. The splicing curved surface reinforcement method comprises the steps of creating a component BIM three-dimensional model, inputting reinforcement parameters, searching an arrangement path and generating reinforcing steel bars. In order to solve the technical problem of splicing curved surface reinforcement in the BIM three-dimensional design process of complex structure engineering, a graph theory is introduced to construct an edge and surface topological connected graph model, so that the problem of steel bar path planning in disordered splicing surfaces is effectively solved, and the construction efficiency is improved. The rapid routing of the steel bar arrangement path in the curved surface topology network and the rapid positioning of the steel bar arrangement path in a plurality of sampling points on the topology edge are realized. Meanwhile, by combining a UV bidirectional parameterization mapping mechanism, the problem of self-adaptive arrangement of the reinforcing steel bars in the three-dimensional curved surface is solved, so that efficient solving and accurate control of the reinforcing steel bars of the complex spliced curved surface are achieved, a traditional reinforcing steel bar mode dominated by manual experience is broken through, the automation degree and engineering reliability of the reinforcing steel bar design of the complex spliced curved surface are remarkably improved, and the construction cost is reduced. Good application prospects are realized.

The invention discloses a data communication method, system and device under a disaster condition, and belongs to the field of power systems, and the method comprises the steps: determining a graph structure model based on a current network topology structure and network topology change information under the disaster condition, carrying out the calculation through a graph theory algorithm, and determining a transmission node and a standby path; if the node connection is abnormal, performing multi-path planning calculation on the standby path to obtain a planning result; splitting the power grid information packet into a plurality of data packets, performing data transmission through a multi-path planning result, and monitoring a transmission progress and arrival confirmation information in real time; and if it is monitored that the transmission is overtime or lost, updating the planning result based on a preset path switching rule to obtain a target planning result, and performing rerouting processing on the remaining data packets according to the target planning result to realize data communication under the disaster condition. And efficient, reliable and stable operation of data communication of the power grid under disaster conditions can be realized.

The invention discloses a two-dimensional full-coverage path planning method for a mobile robot and related equipment, belongs to the technical field of robot full-coverage path planning, and aims to provide a two-dimensional full-coverage path planning method for a mobile robot in a complex two-dimensional environment model, such as a two-dimensional map with irregular obstacles and concave-convex polygonal obstacles. Firstly, a map can be effectively divided into a plurality of sub-regions through a Maklink line generated through a Maklink graph theory, the path searching problem can be simplified, the searching efficiency can be improved, then the sequence that a robot accesses the sub-regions is calculated, the optimal conversion path of the robot among the sub-regions is calculated, and finally, the Boutrophedon path is used for conducting traversal in the shape of a Chinese character'gong ', so that the path searching efficiency is improved. The method can ensure that the robot efficiently covers the whole sub-region, reduces the possibility of omission and repeated cleaning, moves among the sub-regions according to the optimal conversion path and access sequence, and helps to reduce repeated paths and invalid movement when the robot traverses the sub-regions.

The invention discloses a climate risk prevention and control method and device based on a graph theory and a knowledge graph. The method comprises the following steps: collecting climate data, traffic facility data and geographic topology data from multi-source heterogeneous data; constructing a knowledge graph by utilizing the entities extracted from the data and the relationship between the entities, representing knowledge by adopting triads in the knowledge graph, and updating by adopting a dynamic updating mechanism; a multi-temporal-spatial dynamic network is constructed based on a graph theory technology, a time dimension is introduced into the multi-temporal-spatial dynamic network, and a dynamic propagation process of climate risks is described by using a nonlinear dynamic model; describing a dynamic propagation process of climate risks in the multiple spatial-temporal dynamic networks by using a nonlinear dynamic model; by analyzing the multiple time-space dynamic networks, key nodes and risk propagation paths are identified and optimized. The technical problem that in the prior art, key risk nodes and propagation paths are difficult to accurately recognize, and consequently corresponding optimization strategies are lacked is solved.

The invention provides a park integrated energy system low-carbon scheduling method combining demand response and carbon emission flow, and belongs to the technical field of energy system low-carbon scheduling. Establishing a directed weighted carbon flow network model based on a graph theory, tracking a carbon emission transmission path by adopting a maximum flow minimum cut theorem and a proportional allocation principle, constructing a space-time coupled dynamic carbon flow state space model, and performing state estimation by adopting a Kalman filtering algorithm; the carbon emission responsibilities are distributed based on a Shapley value method, a stepped carbon transaction cost function is established, an optimal scheduling strategy is solved through a double-layer iterative optimization framework, and the technical problem that the carbon emission responsibilities are difficult to distribute reasonably due to the fact that a park integrated energy system cannot accurately track a carbon emission transmission path when electric heat gas multi-energy flow coupling is considered is solved.

The invention discloses a house quality problem detection method and system based on graph theory correlation analysis, and the method and system have the advantages that a correlation graph model is established, a correlation graph between factors is provided by integrating construction process, material and maintenance data and dynamically recognizing high-risk nodes, the recognition of potential risks is improved, and the detection efficiency is improved. The node weight and the edge association strength can be adjusted in real time, and the quality can be effectively supervised; a multi-stage evolutionary game model is constructed, analysis is carried out in the early stage, the middle stage and the later stage of construction in combination with an association graph model, and a more accurate risk assessment model is formed; a sub-shortest path algorithm is introduced, a quality problem extension path is accurately predicted, a potential problem source can be quickly positioned, and the early warning efficiency is improved; historical data and game results are utilized to form a quality risk assessment model, high-risk nodes are deeply analyzed, potential quality problem extension trends are identified, prevention measures are taken in advance, later rework cost is reduced, and delivery safety and reliability are improved.

The invention discloses a power system optimization method based on topology compression, and the method comprises the following steps: 1) constructing a power system topological graph: abstracting a power system into a weighted graph, representing power equipment by nodes, representing power transmission paths by edges, distributing electrical attributes and weights for the nodes and the edges, and providing a basis for subsequent topology compression and optimization; 2) analysis and implementation of topological compression: identifying redundant nodes and edges through cut point and bridge edge algorithms in a graph theory, and simplifying a topological structure by merging or removing redundant parts; 3) power flow analysis and optimal scheduling: performing power flow analysis on the compressed topological structure, and realizing power scheduling and load distribution by using an optimization algorithm to improve the operation efficiency of the system; and 4) dynamic adjustment and fault recovery: updating a topological structure and node attributes based on real-time data, and quickly responding to load fluctuation and equipment faults of the power system through an optimization algorithm. The method has the beneficial effects that the calculation complexity can be remarkably reduced, and the optimization effect and the scheduling efficiency are improved.

The invention provides a structural engineering bearing capacity field detection method, and belongs to the technical field of structural engineering detection.The structural engineering bearing capacity field detection method comprises the steps that a multi-axial acceleration sensor and a strain gauge array are installed on the surface of a to-be-detected structural member, and an intelligent loading device is adopted to apply incremental loads; a mobile data acquisition terminal is utilized to acquire vibration response data and strain response data in real time, modal parameters are extracted based on a frequency domain analysis method to establish a load-modal parameter relation curve, the bearing capacity of a component is analyzed and calculated, a graph theory shortest path algorithm is adopted to optimize load transmission path analysis, and the load transmission path analysis is optimized. The bearing performance of the component is accurately evaluated through the structural response prediction model based on the Transform architecture, the technical integration of multi-dimensional detection data fusion, intelligent loading control, quantitative bearing capacity evaluation and accurate performance prediction is realized, and the technical problem of insufficient detection precision of the bearing capacity of the structural component is solved.

The invention provides a multi-AGV conflict solving scheduling method based on a graph theory, and the method comprises the steps: planning a planning path from a starting point to a terminal point for each AGV, and issuing an actual path to the AGV for execution; defining a conflict detection range in a planned path for each AGV, calculating a conflict relationship between each AGV and other AGVs in the range, and updating a graph structure representing the conflict relationship between the AGVs according to the conflict relationship; identifying whether a cyclic conflict which cannot be solved by simply adjusting a sequence or a path exists in the conflict graph, and designing and issuing a specific unlocking path or a conflict solving strategy according to the detected deadlock; and according to the conflict resolution strategy, the planned path of the related AGV is adjusted in real time, and the adjusted path is used as an issuing path to be sent to the AGV for execution so as to deal with dynamically occurring conflicts. The method is used for solving conflicts and deadlocks in the multi-AGV scheduling process, and deadlocks are prevented from being formed in advance under the condition that information is sufficient.

The invention provides a method for constructing an arch-shaped large-span shell steel roof, and belongs to the technical field of arch-shaped large-span shell steel roof construction. A temporary supporting system is built, and distributed optical fiber sensors are arranged to monitor the lifting process of a main arch; a cable force distribution scheme of a cable supporting system is calculated by adopting a double-layer game optimization model to realize cooperative control of stress uniformity and form precision, tensioning force is applied by using an intelligent tensioning system in stages, and a crane moving path is planned in combination with a path optimization algorithm based on a graph theory to realize graded unloading of a temporary supporting system. The technical problem that it is difficult to achieve structural stress uniform distribution and form accurate control of an arched large-span shell steel roof at the same time in the tensioning process of a cable supporting system is solved.

The invention discloses a carbon dioxide seepage dominant channel judgment and permeation enhancement effect evaluation method and system, and the method comprises the following steps: obtaining three-dimensional image data through the three-dimensional CT scanning of a rock sample before and after a CO2 mineralization storage experiment reaction, extracting a crack network as a topological structure center line skeleton, calculating the topological indexes of a network structure, and calculating the permeability enhancement effect of the network structure; a fracture network topological structure model constructed based on a graph theory is coupled with a discrete fracture network model for CO2 flow simulation, an equivalent permeability tensor is obtained, an improved Dijkstra shortest path algorithm is adopted, spatial distribution of CO2 seepage dominant channels is obtained, dominant channel characteristics before and after transformation are compared with the equivalent permeability tensor, the seepage enhancement effect is quantitatively evaluated, and the CO2 seepage enhancement effect is obtained. And changing injection conditions to perform multi-group simulation under different working conditions, calculating the seepage enhancement effect and the mineralization reaction rate under different injection conditions, establishing a quantitative evaluation model of the mineralization sealing permeation enhancement effect, and realizing sealing effect prediction and seepage enhancement effect evaluation.

The invention discloses a method for exploring a heterogeneous catalytic reaction network based on a deep potential energy surface model, and the method comprises the steps: carrying out the accurate prediction of the free energy change of all possible element reactions on a catalyst through the combination of transfer learning and a density functional theory, and constructing a reaction network diagram based on a graph theory method; an improved Dijkstra method is used for searching a reaction network diagram to determine a reaction mechanism, and the selectivity of the catalyst is explored based on a Markov chain method. According to the technical scheme provided by the invention, when the CO2 reduction reaction mechanism on the monatomic alloy is explored, the prediction error MAE of the electron energy of each intermediate is only 0.16 eV, the calculated amount is reduced by 90%, the dominant path of the CO2 reduction reaction is visually displayed, and a new normal form is provided for complex mechanism exploration and catalyst screening.

The invention relates to the field of concrete 3D printing, and discloses a path optimization method for concrete 3D printing, which comprises the following steps: firstly, slicing a three-dimensional model of a to-be-printed concrete member, converting the sliced model into a geometric model, and initializing position information of geometric points in the geometric model; according to a graph theory principle, dividing the geometric model into a plurality of areas which can be printed at one time; the method comprises the following steps: constructing slices of a printing model into geometric figures which can be identified by a computer, extracting and numbering vertexes of the geometric figures, respectively recording coordinates of the vertexes, setting an adjacent matrix to describe a connection condition between the vertexes, then storing the vertexes into a partition matrix according to a rule, the partitions can be traversed at a time; finding out a shortest printing path in the plurality of divided areas by using an ant colony algorithm; and the printing platform is controlled to move according to the planned optimal printing path.

The invention provides a power distribution network fault self-healing control method based on artificial intelligence, and relates to the field of power system intelligent control, in particular to a power distribution network fault self-healing technology, which comprises the steps of acquiring real-time operation state data of a power distribution network, extracting features to establish a fault prediction rule base, monitoring faults in real time and determining positions, and constructing a topological structure based on a graph theory algorithm. And calculating the load transfer capacity of the selectable reconstruction path, solving the multi-objective optimization function by adopting an improved particle swarm algorithm to obtain an optimal reconstruction scheme, generating a control instruction sequence to isolate a fault area, and recovering power supply of a non-fault area. The intelligent level of power distribution network fault processing is improved, the fault recovery time is shortened, and the power supply reliability is improved.

The invention relates to the technical field of hydrology and water resource science, in particular to a rapid extraction method and device for a longest convergence path of a small watershed. Through a unified interface, the generation of intermediate data is remarkably reduced, so that the operation complexity is greatly reduced when a user executes a complex hydrological analysis task, and the possibility of data management errors and misoperation is reduced. And through the integrated processing flow, the operation steps required by the user are simplified. Flow direction analysis, flow calculation, river network extraction and longest confluence path search are integrated in continuous steps, frequent tool switching is not needed, and convenience of user operation is remarkably improved. According to the method, a data processing algorithm is optimized, particularly, a depth-first search (DFS) algorithm is adopted in the aspect of searching the longest runoff path, and the processing speed is increased by organically combining a graph theory algorithm with a GIS technology.

The invention relates to the technical field of electronic design automation, and discloses a standard cell layout legalization method and system based on a graph theory constraint graph, and the method comprises the steps: building a bidirectional directed constraint graph based on an existing layout and a design rule, and building a directed edge between adjacent graph edges according to the design rule; traversing the constraint graph, detecting whether a directed edge which does not meet a constraint condition exists, and if so, identifying the directed edge as a constraint violation edge; for two end points of each constraint violation edge, searching a key path based on a depth-first search algorithm, and determining a maximum movable distance in combination with a greedy strategy; moving the endpoint to a legal position according to the critical path and the maximum movable distance, and updating the position of a related node in the constraint graph; and mapping the position changes of the nodes in the constraint graph back to the corresponding graph edges in the layout, and outputting the legalized layout, so that efficient and automatic repair of design rule violation is realized through the method, and the layout compliance rate and the area optimization effect are remarkably improved.

The invention discloses a milling path planning method and system for stress gradient steepest descent, and the method comprises the steps: carrying out the discretization of a residual stress field based on a lightweight bearing member, and mapping the discretized residual stress field to a milling model, so as to form a high-dimensional matrix; calculating a gradient vector and stress streamline distribution of the residual stress field, and according to the gradient vector and the stress streamline distribution, based on a minimum potential energy principle and a stress steepest descent strategy, performing milling path planning degradation to obtain an optimized baseline; and according to the high-dimensional matrix and the optimized baseline, milling path planning is converted into graph complete traversal with the graph theory as guidance, a steepest descent scheme of strain energy and rigidity is optimized, and an optimal milling path scheme is obtained. The method serves for precision machine manufacturing process design, and the problems of array geometric feature milling path planning and machining deformation control of current lightweight force bearing components are solved; and the method is particularly suitable for light-weight bearing components with array geometric characteristics and high dimensional precision.

The invention relates to the technical field of rail transit, in particular to an urban rail transit passenger flow guidance method and safety management system based on a graph theory, and the method comprises the steps: building a network topological graph based on a spatial topological relation in a rail transit station, and obtaining a passenger flow guidance result through a monitoring video image of each road section in the rail transit station in real time; obtaining the passenger flow volume of each road section at different moments; calculating a passage selectable value, a passage state value, a passage efficiency value and an induction weight of each road section at the current moment; and a weighted network topological graph at the current moment is obtained, a dynamic path planning algorithm is combined, an optimal induction path is obtained, and passengers in the rail transit station are induced to reasonably select a passing path. The optimal induction path is updated in real time, accurate planning of the induction path is improved, dense distribution of passengers in the station is avoided, potential safety hazards are effectively prevented and relieved, and the passing safety of the passengers is improved.

The invention relates to a burn treatment path planning technology, and discloses a burn treatment optimal massage path planning method based on a graph theory and an SAC algorithm. The system comprises a data acquisition and initialization module, a path modeling module, a reinforcement learning module, an optimization and generation module and a closed-loop management module. The data acquisition and initialization module is used for generating accurate point cloud data through a binocular camera in combination with an IMU (Inertial Measurement Unit), and calculating burn average degree and uniformity to provide a basis for subsequent processing; the path modeling module adopts a graph theory method to model a burn area into nodes and edges, and multi-objective optimization is carried out by integrating treatment efficiency and patient comfort; the reinforcement learning module designs a state space, an action space and a reward function based on an SAC algorithm, and realizes optimization of a path and a strength strategy; the optimization and generation module generates a final treatment path through initial exploration and local optimization, and introduces an adaptive force adjustment function to prevent secondary injury; the closed-loop management module supports off-line learning and real-time feedback, and ensures high efficiency and individuation of a therapeutic scheme through dynamic parameter adjustment and report generation. According to the method, the accuracy and efficiency of burn treatment are effectively improved, and the method has wide clinical application potential.

The invention discloses a biomass pyrolytic reaction network prediction method based on a graph theory and quantum chemistry, which comprises the following steps: analyzing the molecular structure of a biomass initial reactant, abstracting the molecular structure into a directed graph molecular model, marking a potential conversion path after molecular mechanics optimization, generating a unique identifier by using an atom numbering rule and a Hash algorithm, and predicting the biomass pyrolytic reaction network. Functional groups are extracted and packaged into sub-graph modules, chemical bond parameters are obtained in combination with quantum chemistry calculation and are converted into fracture probabilities, basic reaction building blocks are predefined to traverse and mark breakable bonds, fragments are recombined and then de-weighted through Hash, and then reaction activation energy weights are given to side chemical bond fracture reactions; an energy optimal path is screened by means of a priority queue search algorithm, accurate analysis of a chemical bond fracture path and intermediate product conversion in the biomass pyrolysis reaction network is finally achieved, reaction path and product distribution are efficiently predicted, and the calculation efficiency and precision of a complex system are balanced.

The invention discloses an efficient routing algorithm for offshore buoy networking. The problem that existing offshore buoy networking information transmission is poor in real-time performance and stability is mainly solved. According to the scheme, the method comprises the following steps: inputting the position of an offshore buoy network, constructing a communication link connectivity model, and abstracting a network link topology by means of a graph theory representation mode; comprehensively considering network efficiencies such as time delay, packet loss rate and network load balancing, and determining link cost between two buoy nodes; aiming at the defect that the ant colony algorithm is easy to fall into local optimum, two-point improvement is carried out on the basic ant colony algorithm. The method comprises the following steps: firstly, during construction of initial pheromones, in a first iteration process of an algorithm, 20% of ants in a population are selected, a path with the minimum cost is selected based on a neighbor algorithm, and the remaining ants adopt random selection paths, so that the convergence of the algorithm is improved, and meanwhile, the diversity of the population is ensured; and a second point, aiming at the problem that a large number of ants are easy to walk to a repeated path when the ant colony is converged to the local optimum in the later stage of iteration, adding repeated check operation in an algorithm updating process. According to the specific operation, when 20% of ants select repeated paths, the ants of the repeated paths select new paths in a random mode, the path search space is expanded, and the algorithm performance is improved. According to the method, the efficient route of buoy networking communication can be dynamically planned, and the real-time performance and the stability of the network are met.