Artificial neural network-based ocean engineering equipment project work structure decomposition system and method

An artificial neural network and network structure technology, which is applied in the field of work structure decomposition of offshore engineering equipment projects, can solve problems such as inapplicability of offshore engineering equipment projects, and achieve the effects of solving time-consuming and labor-intensive, reducing errors and improving production efficiency.

Inactive Publication Date: 2017-05-31
HARBIN ENG UNIV
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Problems solved by technology

The general project work structure decomposition method is not suitable for offshore equipment projects

Method used

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  • Artificial neural network-based ocean engineering equipment project work structure decomposition system and method
  • Artificial neural network-based ocean engineering equipment project work structure decomposition system and method
  • Artificial neural network-based ocean engineering equipment project work structure decomposition system and method

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Embodiment Construction

[0023] The work structure decomposition system of marine equipment project based on artificial neural network includes: OBS information module, project view module, work decomposition module and system management module. The OBS information module is used to describe the specific organizational unit responsible for each project activity, including functions such as OBS addition, responsibility scope division, etc., linking work items, work packages, etc. Engineers can select the person in charge when they decompose the project work structure, and finally form the mutual connection between the OBS structure and the internal data of the project; the project view module is used for adding project information and storing historical project data, including adding projects and importing historical project data , Project characteristic parameter editing and other functions, can add and view the name of the project, classification society, start time, start time, priority, responsible ...

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Abstract

The invention provides an artificial neural network-based ocean engineering equipment project work structure decomposition system and method. The system comprises an OBS information module, a project view module, a work decomposition module and a system management module, wherein the OBS information module is a specific organization unit used for describing and taking charge of each project activity; the project view module is used for adding project information and storing historical project data; the work decomposition module is used for decomposing a project work structure; and the system management module is used for system management and maintenance. According to the system and the method, the problems of time and labor consuming of work structure decomposition of ocean engineering enterprises at present are solved, the workload and errors caused by knowledge blind zones are greatly reduced, a good foundation is laid for project execution and management, better structure decomposition improves production efficiency of shipyards, the economic benefits are increased, and the product quality is improved.

Description

technical field [0001] The present invention relates to a system and a method for realizing the decomposition of the work structure of a marine engineering equipment project through a computer, specifically a system and a method for decomposing the work structure of a marine engineering equipment project based on an artificial neural network. Background technique [0002] ANN (Artificial Neural Network) is a kind of artificial intelligence, which simulates human intelligence activities from a physiological point of view, and uses mathematical or physical methods to study the structure and function of human brains. The general idea of ​​using artificial neural network to solve problems is to simulate the method of human learning knowledge, and use training samples to train the neural network so that it has the ability to "remember" or even "reason" for certain types of knowledge. Artificial neural network can solve complex nonlinear mapping problems, and has good fault tolera...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/10G06N3/04
CPCG06N3/04G06Q10/103
Inventor 李敬花茆学掌孙苗苗郭辉
Owner HARBIN ENG UNIV
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