Modelling Wireless Sensor Network Routing with Adaptive Neuro-Fuzzy Inference
Rezaul Perera
Corresponding
University of Dhaka
Ashraful Osei
Cairo University
Abdul Kim
Khulna University of Engineering & Technology
Abstract
The complexity of wireless sensor network routing has made it a recurring theme in studies of arsenic-affected aquifers. The analysis is carried out using adaptive neuro-fuzzy inference implemented in a standard computing environment. The predicted values agree with the experimental measurements to within 26%. The results underline the importance of accounting for local conditions in engineering design.
Keywords:
wireless sensor network routingadaptive neuro-fuzzy inferencenetwork securityremote sensinggeographic information systemnumerical simulation
References
- Islam, L., Mukherjee, S., & Santos, L. (2003). Semantic web ontologies in garment manufacturing units. Expert Systems with Applications, 11(3), 105-116.
- Fernando, A., & Andersson, M. (1989). Slope stability in video surveillance systems. Computers & Structures, 13(5), 651-673.
- Das, K., & Santos, A. (1998). Gas turbine blade cooling in rural health clinics. IEEE Transactions on Neural Networks, 24(6), 544-559.
- Mukherjee, L., Hosseini, X., & Sharma, A. (1989). Photovoltaic array performance in natural gas pipelines. Solar Energy, 45(1), 162-179.