Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
Session: Artificial Neural Network
7 articles
Proceedings Article
Gesture Segmentation Using Spiking Neural Networks Inspired by the Visual System
L.P. Huang, Q.X. Wu, G.R. Zhang, X. Wang
The human visual system demonstrates powerful image processing functionalities. Inspired by the behaviour of the human visual system, a method of gesture segmentation with the complex background is investigated based on fusion of outputs from two kinds of spiking neural networks. The structures and the...
Proceedings Article
Anomalous Propagation Echo Detection Using Neural Network and Discrete Wavelet Transform
H. Lee, E.K. Kim, S. Kim
Anomalous propagation echo belongs to representative non-precipitation echoes which have very similar characteristics of precipitation echoes. It occurs due to super-refraction or ducting phenomenon of radar beam by temperature or humidity. There are a lot of ongoing researches about detecting and removing...
Proceedings Article
Sensitivity Analysis of Factors Influencing the Anchorage Force of Soil Anchor Rods Based on the Orthogonal Experiment – ANN
B.Q. Wang, J.B. Hao
Based on the BP algorithm of artificial neural network (ANN), an intelligent model which is used to predict the anchorage force of soil anchor rods is established in this article, under the comprehensive consideration of the anchor rod diameter, strength of the grouting body, length of anchoring segment,...
Proceedings Article
Parameter Sensitivity Analysis of Geotechnical Engineering System Using Neural Network Ensemble
L.X. Pan, Y.R. Zhang, M.S. Cao, D. Novak
Neural networks-based sensitivity analysis of parameters of geotechnical engineering systems has become a research focus of increasing interest. This study presents a neural network ensemble–based parameter sensitivity analysis method to investigate the sensitivity of variables leading to lateral deformation...
Proceedings Article
Neural Network Approach for Underwater Acoustic Communication in the Shallow Water
K.C. Park, J.R. Yoon
The transmitted acoustic signals are severely influenced by boundaries like as sea surface and bottom in the shallow water. Very large reflection signals from boundaries cause inter-symbol interference effect, the performance of the communication are degraded. Usually, to compensate the reflected signals...
Proceedings Article
Application of Artificial Neural Network to Predict Water Levels in Virginia Key, Florida
W. Huang, S.D. Xu, Y.N. Chao
This paper presents the application of the artificial neural network to predict long-term water level in Virginia Key, south Florida. Model input is based on the NOAA observed data at a remote station, Cedar Key station located at about 584 km away. Results indicate that, even though the long distance...
Proceedings Article
Neural Network Modelling of Flow In Yinluoxia Station Based on Flow in Zhamashike Station in Heihe River, China
W. Huang, Y.N. Chao, S.D. Xu, Y. Cai, F. Teng, B.B. Wang
Artificial neural network model was established between two river flow in two hydrological stations, Yinluoxia Station and Zhamashike Station in upper Heihe River basin. Results indicate very good correlations for the general trend of the flow data at two stations with correlation coefficients of 0.86...