Patent ID: 11915798
Assignee: FUJITSU LIMITED
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 11:
12. A non-transitory computer-readable recording medium having stored therein a program for causing a processor to execute a process for predicting characteristics of a new chemical substance, the process comprising:
determining a degree of similarity between a target material and a first material based on a structure and characteristic of each of the target material and the first material;
predicting a characteristic value of the target material based on a first value representing the characteristic of the first material;
outputting the predicted characteristic value; and
predicting characteristics of the new chemical substance based on the output predicted characteristic value, wherein
the process uses, H
     =
     
      
       
        -
        α
       
       ⁢
       
        
         ∑
         
          i
          =
          0
         
         
          n
          -
          1
         
        
        
         
          b
          i
         
         ⁢
         
          x
          i
         
        
       
      
      +
      
       β
       ⁢
       
        
         ∑
         
          i
          ,
          
           j
           =
           0
          
         
         
          n
          -
          1
         
        
        
         
          w
          ij
         
         ⁢
         
          x
          i
         
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          x
          j
         
        
       
      
     
    
   
   
    
     (
     1
     )
    
   
  
 

to search for a maximum independent set based on a molecular structure of each of the target material and the first material to determine the degree of similarity according to the characteristic,
in the formula (1),
the H is a hamiltonian for minimizing the H which searches for the maximum independent set,
the n is a number of nodes in a conflict graph of the target material and the first material,
the conflict graph is a graph created based on a rule that when a combination of each node atom of the graphed target material and each node atom of the graphed first material is defined as the node,
comparing the multiple nodes of the graph;
an edge is created between the nodes that are compared and determined to not be identical,
no edge is created between the nodes that are compared and determined to be identical to each other,
the bi is a numerical value which represents a bias for the node ordered i-th,
the wij is a positive number that is not 0 when an edge exists between the i-th node and the j-th node,
and is 0 when no edge exists between the i-th node and the j-th node,
the xi is a binary variable indicating that the node ordered i-th is 0 or 1,
the xj is a binary variable indicating that the node ordered j-th is 0 or 1, and
the α and the β are positive numbers, wherein
the process uses, S
      ⁡
      (
      
       
        G
        A
       
       ,
       
        G
        B
       
      
      )
     
     =
     
      
       δ
       ⁢
       max
       ⁢
       
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     (
     2
     )
    
   
  
 

to determine the degree of similarity according to the characteristic for a found maximum independent set,
in the above formula (2),
the GA represents the target material graphed,
the GB represents the first material graphed,
the S(GA, GB) represents a degree of similarity between the target material graphed and the first material graphed, is expressed as 0 to 1, and indicates that a degree of similarity is higher, as the S(GA, GB) approaches 1,
the VA represents a total number of node atoms in the target material graphed,
the VCA represents the number of the node atoms included in a maximum independent set of the conflict graph among the node atoms in the target material graphed,
the VB represents a total number of the node atoms in the first material graphed,
the VCB represents the number of the node atoms included in a maximum independent set of the conflict graph among the node atoms in the first material graphed, and
the δ is a number of 0 to 1,
the process adds a WL label according to a Weisfeiler-Lehman (WL) procedure to the node atom, wherein
the process, when using the formula (1) to determine the degree of similarity according to the characteristic,
selects the node atom according to an evaluation index Bi for expression of the characteristic based on information of the WL label,
the process, in order to increase a correlation coefficient determined between the degree of similarity according to the characteristic and the characteristic value according to the characteristic, updates at least one of
i) a numerical value of a contribution value ΔB for each type of atom of the node atom, serving as a criterion for calculating a value of the evaluation index B, included in information of the WL label added to the node atom of the node ordered i-th, in the formula (1),
ii) a threshold value of the evaluation index B included in information of the WL label added to the node atom constituting the node ordered i-th, in the formula (1),
iii) a numerical value of the bi, in the formula (1),
iv) a numerical value of the wij, in the formula (1), and
v) a similarity degree evaluation formula S represented by the formula (2), wherein
the update is performed according to genetic algorithm of a machine learning method.