Enumeration Method for Structural Isomers Containing User-Defined Structures Based on Breadth-First Search Approach

2016 ◽  
Vol 23 (8) ◽  
pp. 625-640 ◽  
Author(s):  
Jira Jindalertudomdee ◽  
Morihiro Hayashida ◽  
Tatsuya Akutsu
2018 ◽  
Vol 1019 ◽  
pp. 012038 ◽  
Author(s):  
Robbi Rahim ◽  
Dahlan Abdullah ◽  
Saiful Nurarif ◽  
Mukhlis Ramadhan ◽  
Badrul Anwar ◽  
...  

2013 ◽  
Vol 11 (06) ◽  
pp. 1343007 ◽  
Author(s):  
YANG ZHAO ◽  
MORIHIRO HAYASHIDA ◽  
JIRA JINDALERTUDOMDEE ◽  
HIROSHI NAGAMOCHI ◽  
TATSUYA AKUTSU

Molecular enumeration plays a basic role in the design of drugs, which has been studied by mathematicians, computer scientists, and chemists for quite a long time. Although many researchers are involved in developing enumeration algorithms specific to drug design systems, molecular enumeration is still a hard problem to date due to its exponentially increasing large search space with larger number of atoms. To alleviate this defect, we propose efficient algorithms, BfsSimEnum and BfsMulEnum to enumerate tree-like molecules without and with multiple bonds, respectively, where chemical compounds are represented as molecular graphs. In order to reduce the large search space, we adjust some important concepts such as left-heavy, center-rooted, and normal form to molecular tree graphs. Different from many existing approaches, BfsSimEnum and BfsMulEnum firstly enumerate tree-like compounds by breadth-first search order. Computational experiments are performed to compare with several existing methods. The results suggest that our proposed methods are exact and more efficient.


Author(s):  
R Ratnadewi ◽  
E M Sartika ◽  
R Rahim ◽  
B Anwar ◽  
M Syahril ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Yanbo Che ◽  
Yuancheng Zhao ◽  
Jianmei Xu ◽  
Jinhuan Zhou

Minimal cut sets are the basis of reliability analysis using analytical techniques. At the present stage, minimal cut sets are mainly obtained by dealing with minimal path sets, which involves cumbersome steps and slower operational speed. The speed of reliability analysis is limited by that of calculating minimal cut sets. In consideration of the characteristics of microgrid, a hierarchical approach for fast calculating minimal cut sets is proposed in this paper. Firstly, an equivalent principle is proposed to convert topology structure into network node diagram; then grades of nodes are designated based on their original connection and the breadth-first search approach; afterwards, root-leaf matrices and selected matrix are created to specify the direction and order of the search. Next, all possible combinations of minimal cut sets are vertically traversed out by replacing root nodes with leaf nodes to achieve a more rapid access to minimal cut sets. Finally, taking the electrical structure of type A380 more electric aircraft as an example, mainstream methods are compared to show the correctness and advantage of our proposed method.


2018 ◽  
Vol 1019 ◽  
pp. 012036 ◽  
Author(s):  
Robbi Rahim ◽  
Dahlan Abdullah ◽  
Saiful Nurarif ◽  
Mukhlis Ramadhan ◽  
Badrul Anwar ◽  
...  

2017 ◽  
Author(s):  
Ratnadewi Ratnadewi ◽  
Robbi Rahim

This paper has been presenting at The 2nd Annual Applied Science and Engineering Conference (AASEC 2017) in Bandung, Indonesia on 24 August 2017, this paper had upload in InArXIV for other researcher before the paper publish by IOP Publisher


Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 275
Author(s):  
Benjamin Ricaud ◽  
Nicolas Aspert ◽  
Volodymyr Miz

Studying real-world networks such as social networks or web networks is a challenge. These networks often combine a complex, highly connected structure together with a large size. We propose a new approach for large scale networks that is able to automatically sample user-defined relevant parts of a network. Starting from a few selected places in the network and a reduced set of expansion rules, the method adopts a filtered breadth-first search approach, that expands through edges and nodes matching these properties. Moreover, the expansion is performed over a random subset of neighbors at each step to mitigate further the overwhelming number of connections that may exist in large graphs. This carries the image of a “spiky” expansion. We show that this approach generalize previous exploration sampling methods, such as Snowball or Forest Fire and extend them. We demonstrate its ability to capture groups of nodes with high interactions while discarding weakly connected nodes that are often numerous in social networks and may hide important structures.


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