Sharif Digital Repository

Delay Tolerant Networks are a variation of Mobile Ad Hoc Networks, in which low density of nodes in the network area results in global disconnectivity among the nodes. In these networks, communication of data throughout the networks takes place by the means of mobility; nodes store data packets and carry them around the network and forward them to other nodes they encounter along the way. In these situations, a proper selection of data to be exchanged between nodes has a great impact on the quality of data distribution in the whole networks. There is a common assumption among most of the techniques presented in category of Delay Tolerant Networks. They assume the probability of more than two... 

In this project, we intend to use intelligent and learning algorithms to forecast the U.S. presidential elections. First, we considered some economic and political variables in our model. Then by using stepwise regression, we found the most significant variables. After that, we used three data mining techniques on these data. In the next step, we used support vector regression and neural networks to predict the elections. Then we compared these two algorithms with each other. Eventually, we realized how strong and accurate these methods are to predict the U.S. presidential elections. We have, also, proved that using data mining techniques is beneficial to make models more accurate