Social Sciences

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Subject: search.filters.subject.Forecasting

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    Statistical and Mathematical Models for a Sustainable Cultivation Plan - A Brief Review of the Literature
    (International Conference on Applied Social Statistics (ICASS) - 2019, Department of Social Statistics, Faculty of Social Sciences, University of Kelaniya, Sri Lanka, 2019) Hakmanage, N.M.; Chandrasekara, N.V.; Jayasundara, D.D.M.
    Due to rapid increase of population, demand for food is increasing. If the agricultural sector fails to supply and meet the rising demand of foods, it will affect the economy. This however requires finding viable solution that is balanced supply demand food chain. To fulfil subsistence food needs there should be a stationary state with proper cultivation plans in agricultural sector in a country. This study presents a review of the literature published between 1998 and 2019 on cultivation plans in the areas of statistics and/ or mathematics which have considered major influential factors for cultivation. This study aims at reviewing the most appropriate sub sections: arable land selection, cultivating methodologies and climatic factors effect on cultivation to build an optimal cultivation plan. Review was conducted using separate articles as searching strategy was failed to identify published articles which studied for these three aspects together. Hence the significance of this study is to discuss how to apply statistical and/ or mathematical models which are used to implement the cultivation plan including all influential factors together
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    Model for Tourism Forecasting and Policy in Complex Situations
    (University of Kelaniya, 2005) Cooray, T.M.J.A.
    Information about the current and forecast levels of tourism and its contribution to the economy is important for policymaking by businesses and governments. Traditional forecasting methods can provide reasonable forecasts in the context of predicable changes. However, forecasting becomes problematic in the context of both predictable changes and less predictable domestic or international shocks. This paper demonstrates the ways in which an integrated model, combining traditional forecasting methods and quantifiable scenario forecasts, can be used to examine complex combinations of events. The model is applied to Sri Lanka’s tourism indicators, which provide a picture of tourism in the Sri Lankan economy, with traditional forecasting methods and quantifiable scenario forecasts. Results are provided for a combination of changes in relative exchange rates, income of major origin countries and a positive shock to tourism demand, to demonstrate the integrated model's ability to take account of the complex multiple events that affect tourism destinations.