36 results about "Heuristics" patented technology

The current invention uses structural data mining methods and systems, combined with partitioning hints and heuristics, to locate high level library functional blocks in a gate level netlist of an integrated circuit (IC). In one embodiment of the invention, the library is created by synthesizing various design blocks and constraints. The method supports characterization matching between a netlist and a library, between libraries and between netlists. The data mining method described herein uses a subgraph growing method to progressively characterize the graph representation of the netlist of the IC. In one embodiment of the invention, alternative hashing is used to perform subgraph characterization. Further, the located high level functional blocks may be used to substitute the corresponding portions of the target netlist having the matched characterizations, and may be annotated accordingly in the resulting netlist.

A method using machine learned, scenario based control heuristics including: providing a simulation model for predicting a system state vector of the dynamical system in time based on a current scenario parameter vector and a control vector; using a Model Predictive Control, MPC, algorithm to provide the control vector during a simulation of the dynamical system using the simulation model for different scenario parameter vectors and initial system state vectors; calculating a scenario parameter vector and initial system state vector a resulting optimal control value by the MPC algorithm; generating machine learned control heuristics approximating the relationship between the corresponding scenario parameter vector and the initial system state vector for the resulting optimal control value using a machine learning algorithm; and using the generated machine learned control heuristics to control the complex dynamical system modelled by the simulation model.

The invention discloses a pilot assignment method and device based on an improved intelligent water drop algorithm, and relates to the field of ship pilot assignment. The method includes the following steps in sequence: determining problem constraints according to a problem description, and establishing a pilot assignment model; based on the improved intelligence The water drop algorithm solves the pilot assignment model and finds out the optimal pilot assignment plan; the invention proposes a selection strategy based on the optimal candidate node subgroup for the shortcomings of the intelligent water drop algorithm, such as insufficient heuristics and easy to fall into local optimum. search efficiency and algorithm accuracy. The improved intelligent water drop algorithm is used to solve the pilot assignment model, which effectively improves the accuracy of the solution results.

The invention discloses a cloud workflow segmented online scheduling optimization method integrating heuristics and intelligent computing, which comprises the following steps: obtaining information required for scheduling optimization; calculating the sorting value and level value of tasks; The heuristic method generates the task scheduling optimization scheme of the first stage; obtains the task scheduling optimization scheme of the second stage based on the genetic algorithm; outputs the scheduling optimization scheme. The present invention adopts a segmented scheduling optimization method that combines heuristics and intelligent computing, and the solution time is equal to that of the heuristic method, while the quality of the solution is similar to that obtained by the intelligent computing method. Therefore, the present invention adapts to real-time online scheduling. Effectively improve the quality of understanding under the premise.

The disclosure relates generally to a parallel computing framework designed to accelerate intensive kernel operations and address the complex physics in numerical reservoir simulations by effectively using the ‘many-core’ computing platform. Specifically, this Many-core Advanced Parallel Simulation (MAPS) uses heuristics to decide the optimal hardware configurations and optimal software components for a given problem's characteristics to efficiently design a model.

The invention provides a sparse technology-based fast Gauss-Seidel power flow algorithm for a power system and belongs to the analyzing and computing field of the power system. According to the technical scheme of the algorithm, data only containing non-zero elements in a data file are quickly read into an array Y(n, d), so that the reading time of a storage unit and the data file is greatly reduced. Vi and the Qi of a PV node are quickly calculated based on the array Y(n, d), so that the invalid computation of a large amount of zero elements is avoided. Meanwhile, an optimal acceleration factor is quickly determined based on the improved heuristics method, so that the iterative computation speed is greatly improved. The above algorithm is completely applicable to the checking calculation process of all IEEE systems, such as an IEEE-118 system. Compared with the prior art, the time spent in reading the data file is reduced by about 85%, and the time spent on the power flow iteration process is reduced by about 90%. Moreover, the entire computation time is reduced by about 88%. In addition, the more the nodes of a system, the greater the advantages of the algorithm.