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Full-Text Articles in Engineering
Predicting River Stage Using Recurrent Neural Networks, Eric Rohli
Predicting River Stage Using Recurrent Neural Networks, Eric Rohli
LSU Master's Theses
River stage prediction is an important problem in the water transportation industry. Accurate river stage predictions provide crucial information to barge and tow boat operators, port terminal captains, and lock management officials. Shallow river levels caused by prolonged drought impact the loading capacity of barges and tow boats. High river levels caused by excessive rainfall or snowmelt allow for greater tow capacities but make downstream transportation and lock management risky. Current academic river height prediction systems utilize either time series statistical analysis or machine learning algorithms to forecast future river heights, but systems that combine these two areas often limit …
Distributed Iterative Graph Processing Using Nosql With Data Locality, Ayam Pokhrel
Distributed Iterative Graph Processing Using Nosql With Data Locality, Ayam Pokhrel
LSU Master's Theses
A tremendous amount of data is generated every day from a wide range of sources such as social networks, sensors, and application logs. Among them, graph data is one type that represents valuable relationships between various entities. Analytics of large graphs has become an essential part of business processes and scientific studies because it leads to deep and meaningful insights into the related domain based on the connections between various entities. However, the optimal processing of large-scale iterative graph computations is very challenging due to the issues like fault tolerance, high memory requirement, parallelization, and scalability. Most of the contemporary …