Data Estimation and Distribution Map Using CQSAR: Compensation Quantitative Structure-Activity Relationships
-A Case of Seoul, Korea, on April 13, 14, 2008-

Junko KAMBEa, Eiko NAKAYAMAb, Umpei NAGASHIMAc* and Tomoo AOYAMAd

aFaculty of Media Communication, Edogawa University
474 Komaki, Nagareyama, Chiba 270-0198, Japan
bFaculty of Human Life and Environmental Science, Showa Women's University
1-7 Taishido, Setagaya-ku, Tokyo 154-8533, Japan
cResearch Institute for Computational Science (RICS), National Institute of Advanced Industrial Science and Technology (AIST)
1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
dFaculty of Technology, Miyazaki University
Gakuenkihanadai Nishi, Miyazaki 889-2192, Japan

(Received: September 18, 2008; Accepted for publication: April 23, 2009; Advance publication: June 6, 2009)

In this note, we present a method to draw a distribution map of materials observed at a few, sparse and localized data points, such situations frequently appear in the problems of chemistry and environmental science. In these situations, it is usually difficult to draw a distribution map because data on triangular or square lattice are required for drawing. We generate additional points where the amount of materials is estimated by CQSAR: Compensation Quantitative Structure-Activity Relationships based on perceptron type neural network after learning of 31 observation data taken at Seoul, Korea on April 13-14, 2008. Then the generated data were used for drawing a distribution map. The distribution map using the additional points generated by CQSAR is useful to understanding the overview of material distributions.

Keywords: Suspended particular material, Distribution map, CQSAR, Neural network, Seoul

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