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A Molecular Structure Graph Retrieval Method Based on Evolutionary Computing Multi-View Fusion

A technology of molecular structure diagram and evolution calculation, which is applied in still image data retrieval, calculation, computer parts, etc., can solve the problem that the depth model cannot capture features well, and achieve high retrieval efficiency, convenient retrieval, and easy-to-use Effect

Active Publication Date: 2022-05-31
SHANXI UNIV
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Problems solved by technology

Effective feature representation plays a core and fundamental role in molecular structure retrieval performance, however, a single deep model cannot capture its features well

Method used

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  • A Molecular Structure Graph Retrieval Method Based on Evolutionary Computing Multi-View Fusion
  • A Molecular Structure Graph Retrieval Method Based on Evolutionary Computing Multi-View Fusion
  • A Molecular Structure Graph Retrieval Method Based on Evolutionary Computing Multi-View Fusion

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Embodiment Construction

[0051]

[0052]

[0053] Among them: dense(input, units) represents a fully connected layer, input and units represent its two parameters,

[0054] Finally, the output of the fusion network is mapped to the category space using formula (3),

[0055]

[0057] Step 4.4, population initialization: randomly generate T individuals according to step 4.2, denoted as P

[0058] Step 4.5, fitness value function: train each multi-view fusion network by minimizing the cross-entropy loss,

[0059]

[0060] Among them: y is the real category of the sample x, and the category predicted by the pre-y fusion multi-view network, that is, the multi-view fusion network

[0061] Step 4.6, through selection, crossover, and mutation to generate the next generation population: define a set Q that temporarily stores the population

[0062] Crossover process: randomly in the previous generation population P

[0063]o

[0064]...,p

[0065]o

[0066]...,p

[0071] Step 5, based on the EF model, two retrieval...

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Abstract

The invention relates to a method for retrieving molecular structure diagrams based on evolutionary calculation and multi-view fusion. Including: step 1, use operations such as rotation, translation, and scaling to enhance data; step 2, use the enhanced data to train multiple deep models as multi-view feature extractors; step 3, use the trained multi-view extractor to extract enhanced data The multi-view feature; step 4, search for a multi-view fusion model with excellent performance through the evolutionary algorithm to obtain the fusion feature of the classification model of the molecular structure diagram and the data set; step 5, directly use the classification model or use the fusion feature to calculate The ranking value of the similarity between the search graph and the molecular graph in the search database completes the search for the molecular structure graph to be retrieved. The invention is used to solve the problem of image-based chemical molecular structural formula retrieval without relying on molecular structural formula coding characters in the field of chemical informatics.

Description

A Molecular Structure Graph Retrieval Method Based on Evolutionary Computing Multi-view Fusion technical field The present invention relates to chemical informatics chemical molecular structure retrieval field, be specifically related to a kind of multi-view based on evolution calculation Molecular structure graph retrieval method for graph fusion. Background technique Retrieval of chemical structure formula is one of the core work in the field of chemical informatics, which is a kind of input chemical molecular structure. The figure is the chemical information search method of the retrieval content. This method is for the current chemical and chemical talents in scientific research or ordering chemical reagents Frequent searches. [0003] At present, chemical structure retrieval mainly adopts the method of pre-defined molecular structure encoding. For example, based on the simplified score Structural search of sub-linear input specification (SMILES), the method fi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/55G06F16/583G06V10/32G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06F16/583G06F16/55G06N3/08G06V10/32G06N3/045G06F18/25G06F18/241
Inventor 梁新彦郭倩钱宇华朱哲清彭甫镕
Owner SHANXI UNIV
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