8 results about "Operating model" patented technology

The invention discloses a multi-risk management method based on a conditional value-at-risk model in a worst scene, and the method comprises the steps: setting an operation mode of a virtual power plant in a single power market, and analyzing the bidding profit and constraint of the virtual power plant; a typical distribution scene of uncertain variables which can bring risks is constructed by adopting a Monte Carlo simulation method and a fast preceding elimination technology based on probability distance, and then a conditional value-at-risk model under the worst scene is constructed and the maximization of the conditional value-at-risk under the worst scene is taken as a target. And converting a max-min problem into a semi-definite programming problem by adopting a duality theory, and solving to obtain an optimal bidding strategy of the virtual power plant after the management risk. The method can be used as a powerful tool for assisting decision making, theoretical support is provided for a virtual power plant to make a scheme for improving random variable prediction precision, market risks caused by prediction errors are minimized, and a transaction strategy is closer to an optimal strategy in an accurate situation.

A closed dialog-based input system (200) for generating a binding operating model with a fixed execution reference, comprising: a stepwise dialog acquisition unit (210) with a receiving interface for successive dialog-based inputs via any physical or logical input channel, wherein separate dialog stages are storable and referenceable; a dialog state fixing unit (220) for fixing an operational state after each dialog stage; and a dialog conversion unit (230) with an extraction unit for a predefined set of operational parameters from each fixed dialog stage, as well as a generation unit for referential operational parameters in the absence of explicit input of certain parameters.- a unit for generating a fixed dialogic and execution-related reference as well as a unique identifier of an independent execution cycle (240), - a unit for structural dialogic validation (250) with a validation structure for ensuring the reference consistency of all dialogic stages and operational parameters within the execution cycle, - a dialogic execution lock (260), and - a stepwise dialog and execution protocol (270), characterized in that the input system (200) is configured such that - after each dialogic stage, a fixed operational state data record is generated and stored in a reference-bound manner, and - the system architecture technically blocks a transition to a subsequent dialogic stage as well as the transfer of operational parameters or the generation of operational outputs before all operational parameters are extracted or generated, fixed,bound to the fixed execution reference, structurally validated and fixed in a final dialog and execution protocol (270) with a single unchanging reference.

The invention provides a model compiling method and device. The method comprises the following steps: determining a hardware feature vector of target hardware and analysis data of a to-be-operated model on the target hardware; based on the hardware feature vector and the analysis data of the to-be-operated model, generating a first optimization strategy and a second optimization strategy by using a decision rule and a machine learning model; fusing the first optimization strategy and the second optimization strategy to obtain a target optimization strategy; and under the condition that the confidence evaluation result of the target optimization strategy meets the requirement, the target optimization strategy is applied to the compiler, so that the compiler compiles the to-be-operated model according to the target optimization strategy.

The invention discloses a method for allocating contract tasks, which comprises the following steps of: acquiring characteristics of an operator, and establishing personnel portrait information of the operator based on the characteristics of the operator; acquiring features of a current contract, and establishing task portrait information of the current contract based on the features of the current contract; determining the matching degree of the task portrait information and the personnel portrait information according to the task portrait information and the personnel portrait information; and selecting a current contract allocated to the operator based on the determined matching degree. The contract management efficiency can be promoted to be continuously improved, and the operation mode is more efficient. The invention further discloses a computer storage medium and a computer program product.

The application belongs to the field of industrial internet, and particularly relates to a kind of intelligent interaction three-dimensional modeling method, device, equipment and storage medium. First, in response to the interaction operation triggered by the client, the modeling text is determined, then the workpiece to be assembled and its three-dimensional modeling parameters are determined according to the modeling text, the corresponding three-dimensional modeling template is found out and spliced with the parameters to generate a three-dimensional modeling scheme, then the scheme is input into the preset modeling model to obtain a three-dimensional target model, and finally the model is output. The method automatically analyzes the modeling text and completes three-dimensional modeling with the help of the preset template and model, solves the problem that non-professional users cannot operate modeling software for modeling, realizes efficient and convenient three-dimensional modeling, and reduces the modeling threshold.

This invention relates to the field of power system technology and discloses a capacity configuration optimization method, device, equipment, medium, and program product. By acquiring multiple operating models, this invention can gain a deep understanding of the operating patterns and interrelationships of various components within the system. Furthermore, by setting the highest renewable energy consumption ratio as the objective and establishing an objective function based on multiple operating models and initial installed capacity values, the complex operating conditions and optimization requirements of the system can be transformed into mathematical expressions. This achieves effective integration of system information, enabling the objective function to comprehensively reflect the system's operating characteristics and constraints. Consequently, it can determine the system's renewable energy consumption under different installed capacity scales. Through particle swarm optimization, it can quickly search within a vast space of installed capacity combinations to find the combination of installed capacity that maximizes the renewable energy consumption ratio and determine the final capacity configuration optimization result, thereby improving the renewable energy consumption ratio.

The invention provides a GPU resource scheduling method and device. According to the embodiment of the invention, the feedback of the user is used as a standard for determining whether the model can obtain resources, and more users can enjoy high-quality reasoning service through flexible and dynamic resource adjustment. Besides, GPU resources (such as peak-valley allocation, elastic capacity reduction and the like) are more scientifically and reasonably scheduled to a to-be-operated model task according to the GPU resources required by the new model during training and reasoning in combination with sorting and peak-valley time period judgment of the deployed model, so that the GPU resources are ensured to be obtained by more tasks, the resource utilization rate of the GPU is greatly improved, and the resource utilization rate of the new model is increased. And the GPU purchase cost of a client (a model service provider) is indirectly reduced.

The invention relates to the technical field of power systems, and discloses a capacity configuration optimization method and device, equipment, a medium and a program product, and the method can deeply master the operation rules and mutual relations of all components in a system through obtaining a plurality of operation models. Furthermore, a target function is established by taking the highest renewable energy consumption proportion as a target and combining a plurality of operation models and a plurality of initial installation scale values, so that the complex operation condition and optimization demand of the system can be converted into a mathematical expression, and effective integration of system information is realized; therefore, the objective function can comprehensively reflect the operation characteristics and constraint conditions of the system, so that the consumption conditions of the renewable energy sources by the system under different installation scales can be determined. Therefore, through the particle swarm algorithm, the installation scale combination which enables the renewable energy consumption proportion to reach the highest can be quickly searched in a huge installation scale combination space, and a final capacity configuration optimization result is determined, so that the renewable energy consumption proportion is improved.