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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    Assessing the Impact of ESG Factors on Firm Performance: Empirical Evidence from CRIP Sector
    (Springer Science and Business Media Deutschland GmbH, 2025) Rajath, B.S.; Abhilash, G.; Devarajappa, S.; Geetha, V.; Devi, G.; Jain, S.K.; Priyanka, H.B.; Kalli, R.
    In recent times, managers and politicians have been impacted by key variables such as ethics, corporate governance, and ESG, leading to investment choices and the establishment of strong rules. There is an increasing focus on the understanding of environmental stability and the socio-economic growth of nation-states, which has led to the priority of sustainable and responsible investment methods. Nevertheless, there remains a void in investigating the CSR- and associated corporate characteristics that impact business performance The main purpose of the current research is to explore the influence of ESG factors on company performance, with a special emphasis on the Infrastructure, Construction, Real Estate, Infrastructure, and Project (CRIP) sectors. The research employed the Crisil ESG database, providing comprehensive financial data and ESG ratings of 42 organizations. Fixed effect panel regression was performed to evaluate the impact of ESG disclosure on company performance. The data revealed that the combined ESG score has a positive and large effect on the (WACC) Weighted Average Cost of Capital. The findings from the study are meant to aid varied stakeholders for policy-making and strategic decision-making in the Indian CRIP business. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.