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50results about "Molecular computers" patented technology

Molecular generation model training method and device, equipment and storage medium

ActiveCN111695702AHigh molecular propertiesMolecular property optimizationMolecular computersTheoretical computer scienceGraph Node
The invention provides a training method of a molecular generation model. The method comprises the steps of obtaining basic molecules and target molecules; encoding the basic molecule through an encoding layer to obtain a first graph node feature and a first tree node feature, and encoding the target molecule to obtain a second graph node feature and a second tree node feature; matching the firstgraph node feature with the second graph node feature through the alignment layer to obtain a first similarity feature, and matching the first tree node feature with the second tree node feature to obtain a second similarity feature; generating a graph node feature through a generation layer according to the first similarity feature and the first graph node feature, and generating a tree node feature according to the second similarity feature and the first tree node feature; respectively decoding the graph node characteristics and the tree node characteristics through a decoding layer to obtain prediction molecules; updating model parameters based on the difference between the prediction molecule and the target molecule; and through the obtained model, generating high-attribute molecules with partial structures of basic molecules reserved.
Owner:TENCENT TECH (SHENZHEN) CO LTD

Computer aided design system for predicting energetic molecule based on machine learning performance

The invention discloses a computer aided design system for predicting energetic molecules based on machine learning performance, and belongs to the technical field of computer aided design systems. The system comprises: a molecule rapid generation module, which is used for generating all possible molecular structural formulas according to permutation and combination of a molecular mother ring anda substituent group input by a user, and removing a repeated structure; a molecular data set module used for recording reported energetic molecular performance data, and the energetic molecular performance data being mainly used as a training set of the machine learning model training module; a molecular descriptor generation module used for calculating molecular descriptors of molecules generatedby the molecular rapid generation module or molecules in the molecular data set module or molecules input by a user; a machine learning model training module used for training and storing a model byadopting a machine learning algorithm according to the data of the molecular descriptor set; and a performance prediction module used for reading the model and carrying out performance prediction on the molecules generated by the molecule rapid generation module or the molecules input by the user.
Owner:INST OF CHEM MATERIAL CHINA ACADEMY OF ENG PHYSICS

Microfluidic chip-based DNA computer

The present invention relates to computer science, molecular biology and microfluidics technique which provides a DNA molecular computer based on microfluidic chip. The objective is to provide a DNA molecular computer which uses the microfluidic chip as a operation platform, mainly including: using DNA molecules as operation media, using the microfluidic chip as the operation platform of a DNA molecular operator; using DNA molecules as storage media, using the microfluidic chip as the operation platform of a DNA molecular storage; using a electronic computer and a detector as the kernel of a controller; said microfluidic chip includes a DNA molecular computation region and a DNA molecular storage region. The microfluidic chip consists of digestion, ligation, PCR amplification and chip electrophoresis unit connected by microchannels in turn, and carries out the liquid control through micropumps and microvalves.
Owner:DALIAN INST OF CHEM PHYSICS CHINESE ACAD OF SCI

Prediction method of nanoparticle migration and influence factor analysis method and system thereof

The invention provides a prediction method of nanoparticle migration and an influence factor analysis method and system thereof, and the method comprises the steps: extracting parameters and result data from a nanoparticle migration experiment in a porous medium, and obtaining training features and target features; preprocessing the data by using a one-hot coding method and a random forest method,and filling missing values while coding category type features; and carrying out data balance by using an SMOTE technology, establishing and training a model in combination with a support classification characteristic gradient elevator, and carrying out regression or classification prediction on indexes representing nanoparticle migration; finally, analyzing the direction and size of the influence of different characteristics on the migration of the nano particles through a salpril accumulation interpretation method. Generalization of prediction is improved while the cost of a nanoparticle migration experiment is saved; the unbalanced data is subjected to data processing, so that the sample data quality and the prediction precision are improved; A model interpretation method is used for characteristic analysis, so that the nanoparticle migration behavior has interpretability.
Owner:HUAZHONG UNIV OF SCI & TECH

Transformer winding fault diagnosis method based on atomic sparse decomposition

The invention provides a transformer winding fault diagnosis method based on atomic sparse decomposition. The method comprises the following steps of using a three-phase transformer test to simulate transformer winding faults under different working conditions; collecting vibration signals, and carrying out atomic sparse decomposition on the vibration signals to obtain an attenuation modal parameter; carrying out data preprocessing on the attenuation modal parameter to obtain characteristic vectors of a transformer winding under different fault types; dividing the characteristic vectors into atraining sample and a test sample; taking the training sample as input, and the fault types of the transformer winding as output, establishing a transformer winding GSO-SOM network fault diagnosis model; training the fault diagnosis model to acquire the trained transformer winding GSO-SOM network fault diagnosis model based on the atomic sparse decomposition; and inputting the test sample into the trained fault diagnosis model to judge a transformer winding fault, and outputting a diagnosis result. The method has characteristics of high reliability, good accuracy and the like and can be widely applied to the fault diagnosis field.
Owner:HENAN POLYTECHNIC UNIV
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