Conference Papers

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    Weekly prediction of tides using neural networks
    (Elsevier Ltd, 2015) Salim, A.M.; Dwarakish, G.S.; Liju, K.V.; Thomas, J.; Devi, G.; Rajeesh, R.
    Knowledge of tide level is essential for explorations, safe navigation of ships in harbour, disposal of sediments and its movements, environmental observations and in many more coastal engineering applications. Artificial Neural Network (ANN) is being widely applied in coastal engineering field for solving various problems. Its ability to learn highly complex interrelationships based on the provided data sets, along with less amount of data requirement, makes it a powerful modelling tool. The present work is related to predicting the hourly tide levels at Mangalore, Karnataka, using a week's hourly tidal levels as input. The data has been obtained from NMPT, Mangalore and is made use of in predicting tide level using Feed Forward Back Propagation (FFBP) and Non-linear Auto Regressive with eXogenous input (NARX) network. FFBP network yielded correlation coefficient value of 0.564 and NARX network yielded very high correlation coefficient of the order 0.915 for predictions of yearlong hourly tide levels. The study proves that ANN technique can be successfully utilized for the prediction of tides at Mangalore. © 2015 Published by Elsevier Ltd.
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    Urbanization Challenges in Emerging Economies
    (American Society of Civil Engineers (ASCE) onlinejls@asce.org, 2017) Mendi, V.; Reddy, N.A.; Lokeshwari, M.; Raghavendra, T.; Seelam, J.K.
    Tidal inlet is an opening along the coast which facilitates the exchange of water and nutrients. The energy extracted at the tidal inlet using tides is called tidal energy. Tidal energy is reliable and not depleting. Since the density of seawater is 800 times denser than air, the energy extraction is much favorable and reliable resource. Because of the above said advantages, tidal energy production has become an important energy source at global platform. The study area chosen is the Sri Lankan coast. The tidal condition along the Sri Lankan coast is semi diurnal. Identification of the locations for energy extraction is important as the width of the identified inlet at the coast plays an important role in energy extraction. Also, parameters like tidal range, basin area have to be taken into account in order to consider the inlet suitable for energy extraction. In this paper, tidal inlets will be identified along the Sri Lankan coast, the data will be collected for the parameters that are required to consider an inlet for energy extraction and the potential energy that can be extracted at the inlets will be assessed. © 2018 American Society of Civil Engineers.