9 results about "Decision scheme" patented technology

The invention belongs to the field of project group decision making, and particularly relates to a dynamic strategic target-oriented project group reconstruction method and system, and the method comprises the steps: obtaining a project adjustment decision scheme according to a constraint condition; inputting the strategic targets, the project attributes and the decision-making schemes into a large language model to obtain preference scores of the decision-making schemes, and then sorting the decision-making schemes to obtain a sorting result; setting a state; the strategy network generates a corresponding weight vector according to the sorting result and selects an execution action to obtain a selection strategy; according to the initial state and the execution action, state conversion is carried out to obtain a next state, and the extraction weight of each training sample is calculated; updating the strategy network according to the extraction weight and the training sample to obtain an optimized strategy network; and obtaining a project group adjustment result according to the sorting result and the optimization strategy network. The method has the effects that the project is objectively decided, and the project combination is accurately changed according to the changing dynamic strategy target.

The invention belongs to the field of multi-objective optimization, and particularly relates to a project combination optimization method and system considering execution capability deviation repair, and the method comprises the steps: obtaining a plurality of decision schemes according to the constraint conditions and strategic objectives of a project, taking the decision schemes as an initial population, carrying out the rapid non-dominated sorting, obtaining a plurality of non-dominated leading edges, and carrying out the rapid non-dominated sorting of the decision schemes; carrying out crowding degree, carrying out a tournament selection method on the temporary population, generating subgroups, obtaining a final subgroup after the last iteration, carrying out crossover and variation on the final subgroup to obtain a population to be corrected, and carrying out rolling constraint correction on the population to be corrected to obtain an optimal decision scheme group; and randomly selecting a decision scheme from the optimal decision scheme group as an optimization result. The method has the effect of remarkably improving the enterprise strategic planning project combination execution feasibility and income stability.

The invention discloses a finance and taxation task execution decision scheme generation method and device, equipment and a storage medium, and relates to the technical field of finance and taxation, and the method comprises the steps: analyzing a natural language finance and taxation task to obtain a triad of a finance and taxation task semantic graph, an initial constraint set and a target weight, constructing a target rule twin graph containing time and version labels, and obtaining a target rule twin graph; converting a rule sub-graph in the graph into a rule constraint set with a space-time label, performing satisfiability judgment, performing sub-task decomposition and workflow arrangement based on the finance and tax task semantic graph to generate a target workflow skeleton after satisfiability judgment, determining a strategy set according to the finance and tax task semantic graph, and determining a target workflow skeleton according to the strategy set; a target rule twin map and a tense label are combined to form a tense caliber set, the two tense caliber sets form an evaluation space, strategy and tense anti-fact evaluation and Pareto optimization are performed on the evaluation space by using a target workflow skeleton to obtain a finance and taxation index evaluation vector, and a decision scheme set of finance and taxation tasks is generated through comparison and screening of a Pareto dominance relationship. The generation efficiency is improved.

The application discloses an intelligent decision support system based on big data and artificial intelligence, and relates to the technical field of decision support, comprising: a decision data acquisition module, which is used for acquiring decision data, and performing feature extraction and anchoring effect feature marking; a propagation path identification module, which constructs a decision participant opinion influence bipartite graph based on a graph neural network, identifies a core anchor source and a strong cascading propagation path thereof, and outputs an anchoring effect strength value; a weight adjustment module, which is used for generating a weight adjustment factor based on the anchoring effect strength value, generating a weight through iterative adjustment and correlation correction, and generating a decision scheme according to weighted statistics; and a decision correction module, which is used for decomposing a historical decision implementation effect signal to identify a deviation component, generating an counterfactual decision scheme based on causal inference, and correcting a deviation of an actual decision scheme; and effectively solves the information cascade and collective irrationality problems caused by over-amplification of a few opinions or authority influence in traditional group decision-making.

The invention discloses an intelligent decision-making method and system based on ecological-social dual-network coupling and functional character conduction, and relates to the technical field of intelligent ecological management, and the method comprises the steps: constructing an ecological network module and a social network module, and superposing the output of the ecological network module and the output of the social network module into an ecological-social dual-network coupling model; based on the model, ecological and social agents are created, then the agents are utilized to form a double-agent coordinator to optimize the model, and a final decision scheme is generated. According to the invention, ecological function evaluation, social benefit accounting and dynamic optimization decision making are split into independent agent modules, and cross-system collaboration is realized; the states of ecological and social indexes are balanced through a coordinator, scheme re-optimization is automatically triggered, and an evaluation-decision-calibration continuous improvement mechanism is formed; and the ecological driving module and the social driving module output an optimal scheme which simultaneously meets ecological protection requirements and social feasibility constraints through an intelligent negotiation mechanism.

The invention discloses a decision-making scheme recommendation method driven by a decision-making style, which relates to the technical field of intelligent recommendation, and comprises the following steps of: acquiring feature vectors of attributes in a decision-making scheme after comprehensively considering all attribute information by adopting a style-driven scheme evaluation network based on an attention mechanism; the feature vectors are obtained after attention mechanism fusion and all attribute information is comprehensively considered, the probability that a decision scheme belongs to a decision style is obtained, and then a trained style-driven scheme evaluation network is obtained; and finally, obtaining a score of a new task decision scheme according to the trained style-driven scheme evaluation network, and realizing recommendation of the new task decision scheme. According to the method, the scheme according with the decision-making style of the user is adopted to evaluate the network for recommendation according to the decision-making style of the individual user, the recommended decision-making scheme can be consistent with the decision-making preference style of the individual user to the maximum extent, and the consistency between the recommendation result and the individual user is improved.

This invention discloses a rule-embedded intelligent strategy decision-making method and system, belonging to the field of artificial intelligence technology. It obtains decision schemes corresponding to game-based adversarial data based on a strategy model. The strategy model includes: a backbone network for generating a situation vector based on the game-based adversarial data; a situation encoder for converting the situation vector into a situation representation matrix reflecting spatial relationships and environmental influences; a rule constraint layer for generating mathematical constraints based on the situation representation matrix; and a scheme generation layer for generating decision schemes based on the situation representation matrix and mathematical constraints. This invention can overcome the key bottleneck from pixel perception to semantic decision-making, meeting the urgent needs of modern large-scale interactive systems for real-time, accurate, and intelligent situational awareness.

The application discloses an intelligent decision-making method and system based on ecological-social double-network coupling and functional trait transmission, relates to the technical field of intelligent ecological management, and comprises the following steps: constructing ecological and social network modules, and superimposing outputs of the modules into an ecological-social double-network coupling model. Based on the model, ecological and social intelligent agents are created, and then the intelligent agents are used to form a double-intelligent-agent coordinator to optimize the model and generate a final decision scheme. The ecological function evaluation, social benefit accounting and dynamic optimization decision are split into independent intelligent agent modules, and cross-system collaboration is realized. The coordinator balances the states of ecological and social indexes, automatically triggers scheme re-optimization, and forms a continuous improvement mechanism of evaluation-decision-calibration. The ecological driving module and the social driving module output an optimal scheme that simultaneously satisfies ecological protection requirements and social feasibility constraints through an intelligent negotiation mechanism.