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Peer-to-peer mode parallel processing method and frame based on optimization algorithm

An optimization algorithm and parallel processing technology, applied in computational models, genetic models, electrical digital data processing, etc., to achieve the effect of improving overall efficiency

Active Publication Date: 2020-05-19
COMP NETWORK INFORMATION CENT CHINESE ACADEMY OF SCI +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0008] The purpose of the present invention is to solve the above-mentioned problems that exist when the existing model parameters are acquired

Method used

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  • Peer-to-peer mode parallel processing method and frame based on optimization algorithm
  • Peer-to-peer mode parallel processing method and frame based on optimization algorithm
  • Peer-to-peer mode parallel processing method and frame based on optimization algorithm

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Embodiment Construction

[0023] The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0024] figure 1 It is a schematic structural diagram of a peer-to-peer parallel processing framework based on an optimization algorithm provided by an embodiment of the present invention. Such as figure 1As shown, the overall framework adopted in the embodiment of the present invention is a multi-level peer-to-peer parallel framework composed of the main management process, sub-management process and calculation process, wherein the main management process, sub-management process and calculation process are determined by the following method:

[0025] Extract the process whose process number is 0 in the current first communication domain as the main management process, form the process with a process number other than 0 in the first communication domain into the second communication domain, and divide the processes in...

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Abstract

The invention provides a peer-to-peer mode parallel processing method and a frame based on an optimization algorithm. The method comprises the steps that a main management process carries out non-blocking type receiving, receives convergence signals from sub-management processes, carries out hydrological simulation and Nash coefficient calculation according to a first preset algorithm, generates aset of adaptation values, carries out sorting processing on the adaptation values and selects an optimal solution; the sub-management processes receive broadcast in a non-blocking manner, receive exit signals from the main management process, receive convergence signals from the calculation process in a non-blocking manner, perform hydrological simulation and Nash coefficient calculation according to a second preset algorithm, generate a group of adaptive values, sort the adaptive values and select an optimal solution; the computing process receives the broadcast in a non-blocking manner andis used for receiving an exit signal from the sub-management process; hydrological simulation and Nash coefficient calculation are performed according to a first preset algorithm, a group of adaptivevalues are generated, the adaptive values are sorted, and an optimal solution is selected.

Description

technical field [0001] The invention relates to hydrological simulation computing technology, in particular to a peer-to-peer mode parallel processing method and framework based on an optimization algorithm. Background technique [0002] When using a hydrological model for hydrological simulation and forecasting, an important task for hydrologists is to find the optimal parameter set of the hydrological model. The quality of the hydrological model simulation mainly depends on the selection of the parameter set of the hydrological model. Therefore, the parameter calibration part in the hydrological model is very important, because it determines the simulation accuracy of the model to a certain extent. Different watersheds contain their own model parameters. To obtain a set of parameters suitable for the current watershed, the traditional method either relies on experience or searches through calibration algorithms, and the dimension of the parameter space is usually as high a...

Claims

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Application Information

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IPC IPC(8): G06F9/54G06N3/00G06N3/12
CPCG06F9/542G06N3/006G06N3/126
Inventor 李强聂宁明全婷王彦棡
Owner COMP NETWORK INFORMATION CENT CHINESE ACADEMY OF SCI