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This paper presents a Flood Prediction Model (FPM) to predict flood in rivers using Artificial Neural Network (ANN) approach. This model predicts river water level from rainfall and present river water level data. Though numbers of factors are responsible for changes in water level, only two of them are considered. Flood prediction problem is a non-linear problem and to solve this nonlinear problem, ANN approach is used. Multi Linear Perceptron (MLP) based ANN's Feed Forward (FF) and Back Propagation (BP) algorithm is used to predict flood. Statistical analysis shows that data fit well in the model. We present our simulation results for the predicted water level compared to the actual water level. Results show that our model successfully predicts the flood water level 24 hours ahead of time.

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Vehicle to vehicle communication can give us better results by avoiding the major problems in road like collision of vehicles, better route selection in case of traffic congestion, fuel consumption, suitable selection of parking place etc. This paper presents a protocol to avoid the collision of vehicles. High mobility and fast topology changes are the characteristics of Vehicular Adhoc Networks (VANETs). To establish the real world environment for VANETs, network simulator NS2 is used. Medium Access Control (MAC) Protocol is used to avoid the collision of transmitted data. The Simulation is done using the proposed Vehicular Adhoc On-demand Distance Vector (VAODV) routing protocol, which is a modification of Ad-hoc On-demand Distance Vector (AODV) routing protocol. The proposed VAODV protocol is continuously checks the distance, speed of each vehicle and if it finds that the distance between vehicles is continuously decreasing then in this case it will send a warning textual message to those vehicles that are in accidental situation. Based on this textual information these vehicles will take particular action like vehicle may choose new route if it exists or it may slow down its own speed or it may stop moving by pressing brake. The experimental results are used to find out the performance of VAODV protocol. The performance of VAODV protocol is analyzed with different parameters like end to end delay, throughput, packet delivery ratio, normalized routing load etc.

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