TY  - JOUR
T1  - Functional Dependency and Performance Strategy in Deception Detection using Fuzziness and Uncertainty with Underlying Randomness Syndromes
AU - Rajkumar, S. AU - Narayani, V. AU - Victor, S.P. 
JO  - Research Journal of Applied Sciences
VL  - 7
IS  - 5
SP  - 282
EP  - 285
PY  - 2012
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2012.282.285
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2012.282.285
KW  - Deception
KW  -detection
KW  -uncertainty
KW  -randomness
KW  -fuzziness
AB  - Deception detection is an essential strategy for the efficient and secure communication. The implementation of soft computing techniques such as fuzzy logic, uncertainty, randomness, neural networks and genetic algorithm plays a vital role in identifying the deception in an information sharing system. The combined implementation of fuzziness, randomness and uncertainty provides the maximum output than compare it with the individual implementations is an obvious result. In this study, researchers analyze the combined performance and dependency computation for the combined application of randomness, fuzziness and uncertainty towards deception detection. Researchers considers two different domains for the proposed model and the final results are discussed.
ER  -