Self-Organizing Map is an unsupervised learning algorithm.It has the ability of self-organization,self-learning and side associative thinking.Based on the principle it can identified the complex volcanic lithology.Acc...Self-Organizing Map is an unsupervised learning algorithm.It has the ability of self-organization,self-learning and side associative thinking.Based on the principle it can identified the complex volcanic lithology.According to the logging data of the volcanic rock samples,the SOM will be trained,The SOM training results were analyzed in order to choose optimally parameters of the network.Through identifying the logging data of volcanic formations,the result shows that the map can achieve good application effects.展开更多
This paper uses Abductive network to predict global solar radiation in any location in the Kingdom of Saudi Arabia （KSA） based on sunshine duration, month number, latitude, longitude, and altitude of the location. R...This paper uses Abductive network to predict global solar radiation in any location in the Kingdom of Saudi Arabia （KSA） based on sunshine duration, month number, latitude, longitude, and altitude of the location. Results indicate good agreement between measured and predicted GSR values for each of the 35 locations with known GSR values. Finally, the data from all available stations are used to train an abductive network to estimate the GSR values anywhere in the Kingdom based on latitude and longitude. GSR values are estimated using the developed method at 25 additional locations throughout the kingdom and used with the measured data from the 35 available measurement stations to draw a comprehensive contour map of GSR values for KSA.展开更多
基金Supported by National Oil-gas Project:No XQ-2004-07
文摘Self-Organizing Map is an unsupervised learning algorithm.It has the ability of self-organization,self-learning and side associative thinking.Based on the principle it can identified the complex volcanic lithology.According to the logging data of the volcanic rock samples,the SOM will be trained,The SOM training results were analyzed in order to choose optimally parameters of the network.Through identifying the logging data of volcanic formations,the result shows that the map can achieve good application effects.
文摘This paper uses Abductive network to predict global solar radiation in any location in the Kingdom of Saudi Arabia （KSA） based on sunshine duration, month number, latitude, longitude, and altitude of the location. Results indicate good agreement between measured and predicted GSR values for each of the 35 locations with known GSR values. Finally, the data from all available stations are used to train an abductive network to estimate the GSR values anywhere in the Kingdom based on latitude and longitude. GSR values are estimated using the developed method at 25 additional locations throughout the kingdom and used with the measured data from the 35 available measurement stations to draw a comprehensive contour map of GSR values for KSA.
