48 results about "Topological sorting" patented technology

This invention discloses an online editing and parallel execution method and system for vehicle network test cases, relating to the field of vehicle network testing technology. It establishes an online editing environment via a web interface, enabling automatic generation of protocol code and providing testers with a convenient and efficient development experience. Regarding test case execution, it accurately analyzes the dependencies of test cases, uses a topology sorting algorithm to construct a reasonable execution plan, and adaptively switches between sequential and parallel execution modes. Combined with containerization isolation technology, it allocates an independent execution container for each test case, ensuring the isolation and stability of the testing environment. Simultaneously, it initializes a unified test execution context for each test case and establishes a communication connection with the vehicle network bus simulation engine through a standardized interface, achieving standardization and normalization of operations such as message sending and receiving, fault injection, and assertion verification. In variable management, it adopts a copy-on-write mechanism to achieve isolated sharing of project variables, avoiding data crosstalk.

This invention discloses an automatic business application construction method based on AI semantic analysis, belonging to the field of artificial intelligence semantic analysis and automatic software application generation technology. The method includes: acquiring user-input business requirement description text, performing word segmentation and stop word filtering to form a requirement word sequence; inputting the requirement word sequence into a pre-trained semantic encoding model to generate semantic feature vectors; extracting business intent tags, functional entity sets, and dependency triples; performing similarity matching between the business intent tags and functional entities and component semantic vectors in a component knowledge base to determine the main control component and functional components; constructing a functional component call relationship graph and generating a component topology structure according to topological sorting; and calling an application building engine to instantiate each component sequentially according to the component topology structure, outputting a business application package. This invention enables automatic mapping of business requirements to application structures, reduces manual configuration, and improves the intelligence and consistency of business application construction.

This invention relates to a multi-agent orchestration and execution method supporting complex cyclic graph structures, comprising: S1: receiving workflow configuration and constructing a directed graph data structure; S2: performing a depth-first search traversal on the directed graph data structure, detecting and outputting strongly connected components in the directed graph data structure; S3: abstracting strongly connected components containing multiple nodes into super nodes, and keeping single-node strongly connected components as ordinary nodes, thereby constructing a directed acyclic graph containing super nodes; S4: performing topological sorting on the directed acyclic graph to generate a hierarchical execution plan containing multiple execution layers; S5: scheduling execution items according to the hierarchical execution plan, and when an execution item is the super node, starting a loop executor for iterative execution. This method, by constructing a multi-layered technical system, integrates graph algorithm innovation, unified context management, abstraction layer design, metadata-driven techniques, etc., to achieve automated orchestration and execution of multi-agent workflows supporting cyclic graph structures.

The application provides a causal discovery method and device fusing field knowledge of a large language model and a flow model, and relates to the technical fields of artificial intelligence and data mining. The method comprises the following steps: acquiring observation data and variable semantic information of a system to be analyzed; determining a causal topological order between variables by using a large language model; constructing a mask affine autoregressive flow model based on the causal topological order, and training the model by using the observation data; calculating a Jacobian matrix of the flow model with respect to input data, constructing a statistic based on the Jacobian matrix, and performing hypothesis testing; pruning according to a test result to obtain a candidate causal graph; inputting the candidate causal graph into the large language model, and performing secondary verification and pruning on candidate connections by using the variable semantic information to obtain a final sparse causal graph. The application introduces prior knowledge by using semantic information of the large language model, and fits data by using a more flexible function form of the flow model, thereby significantly improving the accuracy and robustness of causal discovery.

The application discloses a kind of based on multi-focal sharpness analysis's stacked cell hierarchy determination method and system.Acquire Z-stack multi-focal image sequence and extract each focal plane cell contour;Based on centroid coordinates and area features, establish the profile correlation data table of the same cell in different focal planes;Ellipse fitting algorithm is used to complete the shape of the profile of the cell that is blocked;Based on complete geometry mask, screen potential stacked candidate cell pair and locate overlapping area profile;With gradient function as evaluation index, calculate the overlapping area profile sharpness of each cell under multiple focal planes, determine the best focus focal length and judge cell hierarchy relationship;Attribute graph is constructed and topological sorting is executed, and global stacked hierarchy sequence is output.The application establishes hierarchy reasoning rule with rigorous physical basis according to the physical law that upper cell best focus focal length is higher, is compatible with existing Z-stack imaging process, adapts to basic laboratory high-throughput analysis demand.

The application relates to an ordered, enhanced and cacheable symbol execution static analysis method and system, wherein a program function is calculated through graph structure topology sorting, and the dependence order of an inspector is checked; each inspection step is sequentially performed; the inspection information of each dependence step is cached and searched; the inspection information of a current inspector is calculated by combining the information of the inspected inspectors; and the inspection information of a current function is calculated by combining the information of the inspected functions. According to the dependence order, the application is realized in a combined mode as interdependent inspectors, the reuse rate of the inspectors is increased, and repeated development is reduced; the dependence order among functions can solve the analysis dependence problem of cross-function calling; meanwhile, the analyzed results are cached, the analysis efficiency is effectively improved, and incremental analysis and cross-binary library analysis can be realized on the basis.

This invention provides a method for determining the stacked cell hierarchy based on contour completion and gradient quantization. The method involves extracting the visible contour point set of each cell from a cell microscopic image; performing ellipse fitting on the visible contour point set of each cell to obtain the fitted ellipse parameters for each cell, including center coordinates, major axis length, minor axis length, and rotation angle; calculating a global gradient magnitude map on the cell microscopic image; filtering candidate cell pairs based on the fitted ellipse parameters, including overlapping cell pairs and adjacent cell pairs; for each cell pair in the candidate cell pairs, extracting the contour points of each cell within the overlapping region, obtaining the gradient values ​​corresponding to the contour points from the global gradient magnitude map, and calculating the average gradient value for each; determining the hierarchy relationship between the two cells by comparing the average gradient values; constructing an attribute graph using each cell as a node and the hierarchy relationship as an edge; performing topological sorting on the attribute graph; and outputting a global stacked hierarchy sequence.

This invention discloses a load-balanced automatic parallel modeling method, device, and storage medium. First, it analyzes the key factors affecting the execution performance of operators and models (operator in-degree, tensor shape, and tensor data type), and proposes a method for constructing a performance evaluation model based on operator characteristics to assess the computational, communication, and overall costs of operators, as well as the training performance costs of the model. Then, with the goal of load balancing across devices, a layer-by-layer partitioning method based on topological sorting is used to quickly divide the neural network model into multiple sub-models with balanced overall costs, achieving coarse-grained partitioning. Finally, based on the model's training performance evaluation model, and according to the communication characteristics between operators, a fine-grained model partitioning and scheduling method based on communication optimization is used to fine-grainedly adjust the coarse-grained sub-models, reducing the amount of cross-device communication tensor transmission to achieve optimal global model scheduling.

The application provides a multi-agent dynamic workflow arrangement method and system based on an MCP protocol, and relates to the technical field of multi-agent collaborative work. The method comprises the following steps: constructing a standardized agent description and configuring an MCP protocol adapter; generating a task demand text through planning an agent, matching an optimal agent by using a cosine similarity algorithm, and obtaining an initial workflow arrangement graph including a task execution node and a task dependency relationship in combination with a logic analysis technology and a topological sorting algorithm; screening historical related content corresponding to the task execution node based on a context propagation strategy, determining a context dependency result according to the task dependency relationship, and generating context inheritance information by summarizing; accessing the optimal agent by using the MCP protocol adapter, and performing a task execution operation according to the initial workflow arrangement graph in combination with the context inheritance information to generate a task execution result, so that multi-agent efficient collaboration can be realized, and arrangement flexibility and interactive stability can be improved.

The application belongs to the technical field of artificial intelligence and intelligent education, and discloses a knowledge graph joint decoding method and system based on coverage planning and backtracking navigation for education content generation, which is used for solving the problems of incomplete knowledge coverage and disorder of teaching preposition dependency in automatic generation of education content. The method contains three cooperative mechanisms: pre-decoding coverage planning, learning order constraint topological sorting based on an education knowledge graph to generate a teaching planning sequence and allocate a length budget; double-head joint decoding, maintaining a graph cursor, and outputting teaching text and navigation actions through the cooperation of a word prediction head and a navigation prediction head, and fusing graph embedding through a gating mechanism; preposition dependency backtracking, automatically inserting teaching review text and then restoring when a preposition knowledge reference intention is not covered, and simulating instant knowledge connection in teacher teaching. The knowledge coverage rate of the method is 98.3%, and the preposition dependency violation rate is less than 0.5%.

The application provides a multi-dimensional cognitive state vector simulation agent digital textbook dynamic adaptability evaluation method, and relates to the technical field of artificial intelligence assisted education. The method comprises the following steps: extracting teaching entities and semantic relationships between the entities in a source file of a digital textbook to be evaluated through a multi-modal analysis model, and constructing a knowledge graph; initializing multiple groups of virtual learning agents based on a pre-trained large language model, and configuring differentiated cognitive state vectors for each group of virtual learning agents; driving each group of virtual learning agents to traverse the teaching knowledge graph according to a topological sorting by using a knowledge boundary mask mechanism, obtaining understanding feedback of each node by each group of virtual learning agents, and generating confusion degrees and thought chains in the understanding feedback process; calculating a cognitive block index and an adaptability distribution curve of the source file of the digital textbook by using a weighted summation algorithm, and generating an evaluation report. The application simulates human cognitive processes by using a large language model agent, and evaluates the quality and adaptability of a digital textbook.

The application provides an engineering maintenance management method, system, storage medium and program product, relates to the technical field of engineering maintenance management, and the method comprises the following steps: acquiring three-dimensional space coordinates and target fault type identifiers of a plurality of initial work order applications in a preset time window; aggregating the initial work order applications with a spatial distance less than a preset conflict threshold value into a target chain fault work order set, and determining a conflict space region according to the three-dimensional space coordinates of each initial work order application in the target chain fault work order set; mapping the target fault type identifiers to a preset facility physical topology graph to obtain target fault nodes, and generating a collaborative maintenance queue by topological sorting according to a directed edge connection relationship; and performing a work order issuing operation according to the collaborative maintenance queue and the conflict space region. The technical problem of low cross-departmental collaborative scheduling efficiency of engineering maintenance in the related art is solved, and the technical effect of improving the cross-departmental collaborative scheduling efficiency of engineering maintenance is achieved.

This invention relates to the field of intelligent manufacturing technology, and particularly to an IoT-based system for coding and integrating home furnishing products into an ERP system. The system uses a production sensing module to verify the historical convergence of equipment operating parameters via Mahalanobis distance to obtain equipment status confidence. A coding decision module generates a target coding strategy based on the fusion characteristics of production data and an environmental disturbance index compensation model, and then filters it using a strategy effectiveness prediction model. An edge verification module achieves dynamic error correction and dynamic reconstruction of error-correcting codes through bidirectional verification of code graph semantic integrity and a conflict resolution decision matrix. An ERP synchronization module achieves causal consistency updates of inventory status through topological sorting of the coded data causal graph and transaction compensation. A quality traceability module constructs a product traceability knowledge graph to achieve entity disambiguation and data lineage traceability. This invention solves the technical problems of data silos and broken traceability chains in production coding and ERP systems.

This invention discloses a multi-objective hierarchical intelligent optimization decision-making method for reservoir drought limit water levels, deployed in a reservoir scheduling automation system. The method includes the following logically strongly coupled and irreversibly sequential steps: constructing a multi-dimensional objective function topology network for drought limit water level scheduling; establishing multi-element marginal triggering rules for drought limit water level scheduling; creating a reservoir scheduling digital twin model considering the activation signals; pre-creating 19 non-redundant weight configuration vector sets in the system rule engine, generated by topological sorting of four types of objective nodes: benefit, risk, cost, and effectiveness; using the drought limit water level sequence of key nodes as decision variables; and implementing a two-level normalization compensation mechanism to eliminate dimensional differences for all non-dominated solution sets. This invention forms a logically strongly coupled six-step irreversible decision pipeline, achieving optimized allocation of computing resources and industrial-grade security against parameter tampering. It is applicable to intelligent drought limit water level scheduling for multi-objective reservoirs involved in flood control, water supply, ecology, power generation, and navigation.

This invention discloses a method for automatically generating reference schematics for electronic devices, an electronic device, and a storage medium. The method includes: extracting the set of actual chip models corresponding to the underlying physical point diagram of the electronic device; assigning uniformly standardized virtual standard reference designators to components in the chip model set based on a global standard mapping dictionary, and establishing a heterogeneous data mapping table; using the chip model set as the query key, initiating a batch search to a general circuit module library to retrieve matching general circuit data packages; dynamically replacing variable placeholders in the general circuit data packages with virtual standard reference designators based on the heterogeneous data mapping table; performing topological sorting on the replaced general circuit data packages according to classification weight values ​​using a topological sorting algorithm to generate a multi-page structured logic reference schematic set, and generating a dynamic directory with interactive jump anchors based on the multi-page structured logic reference schematic set. This method can solve the problem of low repair efficiency caused by the lack of original manufacturer circuit diagrams.

The application relates to the field of artificial intelligence and automatic planning, and in particular to a large-scale planning problem solving method based on general knowledge of a large language model, which comprises the following steps: parsing a PDDL domain file and an instance file to obtain an initial state, a target state and an action model; decomposing the target state into sub-targets in the form of directed binary tuples, constructing a directed acyclic dependency graph and topologically sorting to obtain an ordered sub-target sequence; recursively traversing the sequence to generate sub-problems and calling a planner to solve the sub-problems, and if the solving fails or times out, optimizing through two modes of the LLM; mode A selects actions from an executable action sequence to compress a search space, and mode B predicts an intermediate state to split an intermediate sub-problem; and finally, sequentially concatenating sub-plans to generate an overall plan; the application aims to solve the problems of large search overhead, difficulty in determining the order of sub-targets and unreliable LLM output of a traditional planning method.

The application relates to the technical field of software development, in particular to a development man-hour estimation method and system based on a function dependency graph. The method comprises the following steps: constructing a requirement function dependency graph, wherein a node represents a function module, a directed edge represents a dependency relationship between the function modules, and each directed edge carries a dependency coefficient; in response to a received change application of a development project, determining a node set of a direct change node corresponding to a function module that has changed; performing influence propagation traversal based on topological sorting on the requirement function dependency graph, automatically inferring all indirectly affected nodes according to the dependency coefficient, and combining the directly changed node set and the indirectly affected nodes to form an affected node set; and calculating the differential man-hour of each node in the affected node set. The development man-hour estimation method based on the function dependency graph can automatically, comprehensively and objectively estimate the man-hour in the development process.

The application relates to the field of data processing and communication technology, and discloses a standardized implementation method of a dynamic automatic translation device, which comprises the following steps: constructing and analyzing a standard configuration model, generating an attribute dependency matrix, performing loop detection and topological sorting, generating a linear ordered execution sequence, presetting a class code skeleton and a runtime context, extracting a logic code set according to the sequence, applying a code synthesis equation to generate a composite logic source code, calling an instant compiler and an isolated class loader to convert the source code into a dynamic translation instance and perform atomic reference replacement, and feeding device original data into the instance to make the device original data flow in a logical path in a one-way manner in the runtime context to complete translation. Through the conversion of the interpretive execution into the compiled sequential execution, the application eliminates runtime dependency lookup, cooperates with the isolated loading and atomic replacement mechanism, realizes the independent running and smooth hot updating of the device logic, and improves the efficiency and stability of the heterogeneous protocol adaptation.

The application provides a Web application system storage and calculation integration adaptation optimization method and device. The method comprises the following steps: determining a code module to be optimized in a Web application system, performing corresponding rewriting and compiling operations on the code module, obtaining WebAssembly bytecode corresponding to the code module, encapsulating the WebAssembly bytecode into a WebAssembly module, and then integrating the WebAssembly module into the Web application system; performing calculation adaptation optimization on the integrated Web application system based on a synchronous and asynchronous code decoupling mechanism and a virtual instruction set architecture of a corresponding WebAssembly virtual machine; and performing memory adaptation optimization on the integrated Web application system by using an in-place memory filling allocation mechanism based on topological sorting, so as to obtain an adapted and optimized Web application system. The method provided by the application can effectively improve the storage and calculation adaptation optimization effect of an application system, thereby improving the storage and calculation capabilities of the Web application system and the performance of Web services.

The application relates to the technical field of standardization management, in particular to a scientific research achievement standard draft intelligent compiling method and system based on big data; the method comprises the following steps: transforming scientific research achievements into a computable technical structure expression model by constructing a multi-dimensional semantic hierarchical and causal relationship model, and establishing a standardization adaptation index; identifying standard blank units and calculating an innovation contribution index by isomorphic mapping of the achievement structure and a current standard vector space, so that automatic positioning and priority sorting of blank clauses are realized; constructing a clause skeleton by using topological sorting and conflict detection, and generating a standard draft in combination with a structured semantic template; constructing a multi-agent collaborative verification mechanism, converting expert feedback into structured data, and realizing dynamic optimization of clauses through credibility weighting and influence tensor; establishing an implementation monitoring and life cycle management system, and performing difference analysis and adaptive iteration; the application realizes intelligent compiling and continuous optimization of a standard draft from scientific research achievements.

The application discloses a kind of reservoir acidification simulation methods for oil reservoir scale, it is related to oil and gas field development technical field.The acid rock reaction flow system of reservoir is decoupled into three-dimensional matrix continuous domain and one-dimensional discrete wormhole topology net, constructs pressure and flow coupling equation, acid liquid transport and reaction equation and geometric shape evolution equation to carry out reservoir acidification simulation, the pressure field of three-dimensional matrix continuous domain and one-dimensional discrete wormhole topology net is fully implicit simultaneous solution, obtains the fluid pressure distribution in reservoir, determines the volume flow and flow direction in one-dimensional discrete wormhole topology net, constructs directed acyclic graph, executes topological sorting and generates downstream calculation sequence calculation to obtain the acid liquid concentration field in one-dimensional discrete wormhole topology net, in combination with geometric shape evolution equation, the geometric parameter of one-dimensional discrete wormhole topology net is updated explicitly, generates new tip node and new wormhole pipe section using geometric topology update, until tip node breaks through production boundary, obtain the simulation result of reservoir acidification.

The invention discloses an operation and maintenance analysis scheduling method based on an analysis unit dependency relationship and a medium. Receiving a current to-be-executed analysis task in real time, and analyzing the current to-be-executed analysis task to obtain a target observable object and a target analysis request; matching with an analysis unit matching library according to the target observable object and the target analysis request to obtain a target analysis unit set; analyzing and processing the target analysis unit set through an analysis unit dependency analysis method to generate a target dependency analysis graph; and performing topological sorting on the target dependency relationship analysis diagram, generating a target execution queue, performing scheduling processing through an operation and maintenance scheduling method, generating a target operation and maintenance analysis scheduling result, and feeding back the target operation and maintenance analysis scheduling result to operation and maintenance personnel. The problems of poor operation and maintenance analysis effect, poor flexibility, complex management and inflexible scheduling caused by adoption of a fixed sequence or a manually defined process are solved, the operation and maintenance analysis accuracy and efficiency are improved, and the operation and maintenance scheduling processing flexibility is improved.

The application discloses an operating system vulnerability tracing method and device, a terminal and a storage medium, and comprises the following steps: generating a component list at version formation; generating a component directed graph for each externally delivered version, taking whether to enter the delivery and the scope of action as a judgment result, performing dependency edge pruning on the component directed graph according to the judgment result, performing topological sorting or loop convergence processing on the remaining ring part to obtain a version component directed dependency graph; combining the vulnerability entry information in the externally delivered version with necessary binary or symbol features to generate an impact component combination, and generating the impact component combination based on the version component directed dependency graph, projecting the impact component combination into the component list of each externally delivered version, and establishing a three-dimensional record of vulnerabilities-component-versions; determining a slice perspective according to a business scenario, slicing the three-dimensional record according to the slice perspective, and obtaining an operating system vulnerability tracing result.

This invention specifically relates to a browser-based human-computer collaborative multi-agent graphical programming system and method, belonging to the field of intelligent programming technology. It includes: acquiring input information submitted by a user through a browser interface; classifying the input information into non-deterministic and deterministic inputs based on their type; performing intent recognition and semantic parsing on the non-deterministic inputs; performing direct mapping on the deterministic inputs; and generating a unified format token stream. In this invention, the task planning module Planner hierarchically decomposes the task objective into a set of subtasks labeled with dependencies, and converts it into a directed acyclic graph for topological sorting. This solves the technical problem of the difficulty in automatically and orderly scheduling complex industrial programming tasks, achieving the technical effect of supporting dependency-driven ordered execution and concurrent scheduling of dependency-free subtasks.

The application discloses a kind of fusion knowledge graph big model carbon neutralization course intelligent generation method and system, belong to intelligent education technical field, including: constructing prerequisite dependence directed graph;Prerequisite dependence directed graph is detected in loop;The knowledge node not being covered is marked as to be learned node;Prerequisite dependence directed graph is executed topological sorting, and the cognitive load value is calculated for each to-be-learned node, and the candidate teaching sequence set satisfying prerequisite constraint is obtained;Filtering candidate teaching sequence outputs optimal teaching sequence.The application constructs prerequisite dependence directed graph with loop resolution, accurately locks knowledge point logical association, fundamentally eliminates cognitive fault caused by knowledge order inversion, generates multidimensional knowledge gap vector based on historical record, accurately locates blind area, realizes the differentiation of course customization across industries, introduces cognitive load quantification model, generates teaching sequence conforming to cognitive progressive law by minimizing adjacent node difficulty transition.

The application provides a kind of intelligent terminal computing power distribution and processing control method based on vehicle-mounted video stream, which comprises: generating video processing task based on vehicle-mounted video stream and user service intention, constructing task dependency graph based on the interdependence of each video processing task in input data area, output data use and execution timing;Topological sorting is carried out on the task dependency graph to generate a task execution sequence;Based on the computing complexity characteristics of each task in the task execution sequence and the total amount of schedulable computing power resources of the intelligent terminal, allocate corresponding computing power resource share for each task;According to the computing power resource share, generate binding instructions for processor core and acceleration unit to obtain task scheduling instruction set;After monitoring that each task in the task execution sequence completes its computing process, release the occupied computing power resources.The application improves the real-time response certainty and computing power resource utilization rate of the vehicle-mounted intelligent terminal in complex and variable road environment.

This invention specifically relates to an intelligent management method for information system integration projects, specifically within the field of information system integration project management and scheduling technology. It includes: updating particles based on a dynamic equation containing nonlinear weights and dual acceleration factors, and performing discretization rounding and boundary bounce repair. In this invention, the complex tasks and heterogeneous resources of the integration project are abstracted into a low-level mathematical model, and a global dynamic resource state tensor and strict topological sorting rules are introduced to achieve deep control at both the physical and logical levels. During the optimization decoding stage, a forward push repair operator and a full resource deduction pre-simulation mechanism are embedded to forcibly correct scheduling instructions that violate objective reality, ensuring that the generated control instructions are implementable.

The application discloses a kind of multi-dimensional resource perception edge flow task processing methods based on distributed hash table, it is applied to the edge network environment of the heterogeneous edge computing node group composition.To each node establishes resource description model, flow processing application is abstracted as directed acyclic graph topology;Three-tier decentralized flow processing architecture including edge physical network layer, structured overlay network layer of fusion multi-dimensional resource perception routing algorithm and dynamic flow data abstraction layer is built;According to topological sorting, each operator calculates independent hash routing key and encapsulates deployment message injection overlay network;In the process of hop-by-hop routing of deployment message, node computing load, available memory, physical communication delay and logical hash distance are included in comprehensive cost evaluation;Through instant interception mechanism, intermediate node actively carries operator instance, realize the efficient adaptation of logical topology and physical resource, reduce flow processing application deployment time and end-to-end query delay.

The application provides a knowledge graph-based alarm root cause positioning method and device, medium and equipment, relating to the technical field of big data. The method obtains a plurality of historical alarm data, constructs a network device topology graph based on the cleaned and labeled device identifiers and device link relationships, and the network device topology graph is used to represent the connection relationship between devices. Feature engineering is constructed and data is compressed, alarm type entity extraction and relationship extraction are performed, an alarm type causal knowledge graph is constructed, and the alarm type causal knowledge graph is used to represent the generation relationship between alarm types. According to the network device topology graph and the alarm type causal knowledge graph, an alarm propagation graph is generated based on a fusion rule. According to the alarm propagation graph, an alarm root cause propagation link graph is obtained by reasoning based on a graph search algorithm and a topological sorting algorithm, network device alarm root cause positioning is performed, and automatic positioning of the root cause is realized, which can improve the root cause positioning efficiency and reduce the labor cost.

The application discloses a development environment deployment method and device, a terminal and a storage medium, belongs to the field of software development, and utilizes operating system and architecture information to generate a basic environment identifier containing at least two layers of subordinate hierarchical fields; the identifier is matched in a global index file; when accurate matching fails, a version number and an OS type are peeled off according to a hierarchical priority to perform multi-level back-off addressing, and a configuration file path is determined; the configuration file is loaded, and depth merging is performed on array appending and object covering from low to high according to the hierarchy to generate a final configuration; a dependency and mutual exclusion relationship of a package or a task is acquired by parsing the final configuration, a directed acyclic graph is generated, and topological sorting is performed to generate a linear task sequence; the sequence is executed according to a parameter sequence by using an installation script, and mutually exclusive tasks are scheduled in a sandbox. The application improves cross-platform environment adaptation fault tolerance, solves mutual exclusion dependency conflicts, and realizes one-key safe deployment of a complex environment.