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Real Call Detail Records (CDR) are analyzed and classified based on SupportVector Machine (SVM) algorithm. The daily classification results in threetraffic classes. We use two different algorithms, K-means and SVM to check theclassification efficiency. A second support vector regression (SVR) basedalgorithm is built to make an online prediction of traffic load using thehistory of CDRs. Then, these algorithms will be integrated to a networkplanning tool which will help cellular operators on planning optimally theiraccess network.

Network planning tool based on network classification and load prediction