  In this paper we propose a wet lab algorithm for prediction of radiation fog
by DNA computing. The concept of DNA computing is essentially exploited for
generating the classifier algorithm in the wet lab. The classifier is based on
a new concept of similarity based fuzzy reasoning suitable for wet lab
implementation. This new concept of similarity based fuzzy reasoning is
different from conventional approach to fuzzy reasoning based on similarity
measure and also replaces the logical aspect of classical fuzzy reasoning by
DNA chemistry. Thus, we add a new dimension to existing forms of fuzzy
reasoning by bringing it down to nanoscale. We exploit the concept of massive
parallelism of DNA computing by designing this new classifier in the wet lab.
This newly designed classifier is very much generalized in nature and apart
from prediction of radiation fog this methodology can be applied to other types
of data also. To achieve our goal we first fuzzify the given observed
parameters in a form of synthetic DNA sequence which is called fuzzy DNA and
which handles the vague concept of human reasoning.
