International Research Symposium on Pure and Applied Sciences (IRSPAS)
Permanent URI for this communityhttp://repository.kln.ac.lk/handle/123456789/15650
Browse
4 results
Search Results
Item Studying the behaviour of export quantities of Tuna fish in Sri Lanka(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Sachithra, S. A. L.; Liyanage, U. P.; Wijeyaratne, W. M. D. N.Being an island in the Indian Ocean, Sri Lanka claims a large sea area and abundant fish resource with high facilitate suitable for large scale fishery industry. According to the Central Bank of Sri Lanka, the contribution of fisheries to the Gross Domestic Production (GDP) of the country ranges between 1.3% and 1.6%. Consequently, fishery industry already plays a vital role in economics and social development of Sri Lanka. Due to weather conditions, seasonal effects, changes of government tax policies and trade agreements, e.g. GSP+ and etc., there is a high fluctuation in export quantity of fishery products in Sri Lanka. Thereby, it is essential to study the variation patterns and forecast harvest and income generated by fishery products towards monitory strategy planning. Among the various types of fish, tuna is one of the species that is important in financial earnings. Out of all fisheries exports, Sri Lanka earns the highest income worth 50.8% by exporting tuna fish in 2016, according to the statistics from Ministry of Fisheries and Aquatic Development of Sri Lanka (SLMFAD). This study was conducted to analyze the export quantities of tuna fish and forecast the future export quantities. Monthly export quantities from January, 2010 to June, 2018 were collected from SLMFAD. In preliminary analysis, United States, Japan, and Canada are identified as the top countries in which Sri Lanka exports the highest quantity of tuna fish. To study the changes in export patterns and their associated relations, Statistical Change-Point Analysis was conducted. The results revealed a high correlation between the changes of export patterns with events such as country’s peace restoration, economic stability, infrastructure facilities, introduction of different capacity changes and termination of development projects. Towards forecasting the export patterns time series data analysis techniques were used. Unit root tests; Augmented-Dickey-Fuller Test (ADF) and Kwiatkowski-Phillips-Schmidt-Shin test (KPSS) were used to test the stationarity of the time series data. Based on Akaike information criterion (AIC) value, SARIMA (1,1,2)(1,0,0)12 model was identified as the best. Ljung-Box test, Jarque-Bera test and Heteroscedasticsity test were used to check the behavior of the residuals of this fitted models. Accuracy of the models were compared by root mean squared error (RMSE), and mean squared error (MSE). With 0.8485 of RMSE and 0.6038 of MSE, SARIMA (1,1,2)(1,0,0)12 model can be considered as the most suitable model to forecast the export tuna quantity from Sri Lanka.Item Modelling and forecasting the income of pepper exports in Sri Lanka(4th International Research Symposium on Pure and Applied Sciences, Faculty of Science, University of Kelaniya, Sri Lanka, 2019) Weerasinghe, W. P. M. C. N.; Jayasundara, D. D. M.Pepper is the most significant and widely used spice in the world. Currently about 60% of pepper production of Sri Lanka is exported while the remainder is consumed domestically. Sri Lanka is the fifth largest exporter of pepper in the world where India buys 62% of pepper exports from Sri Lanka. In 2018 Sri Lanka exported a total pepper crop which had brought in earnings to the tune of Rs.11.5 billion. Fluctuations in export income of different commodities are a matter of concern for consumers, farmers and policymakers in a country. Hence an accurate forecast is extremely important for efficient monitoring and planning of export commodities. The demand for Sri Lankan pepper is increasing rapidly due to its richer piperine content which is two to six times higher than in the other pepper producing countries. Thus, Sri Lanka has the potential to become a key player in the high value export markets. There is no existing literature about forecasting the pepper export income of Sri Lanka. This study presents a statistical time series model for forecasting the income of pepper exports in Sri Lanka by using Seasonal Auto Regressive Integrated Moving Average (SARIMA) model. The data used in this study are monthly export income of pepper in Sri Lanka from January 2000 to December 2018 that were obtained from Sri Lanka Exports Development Board. 80% and 20% of data was used in model building and model validation respectively. ARIMA(4,1,4)(1,1,1)12 was selected as the best model with the lowest Akaike Information Criterion (AIC) for forecasting the income of pepper exports in Sri Lanka among many candidate models that were evaluated by the investigation of Auto Correlation Function(ACF) and Partial Auto Correlation Function (PACF) of the differenced series. Forecasting accuracy of the model was evaluated with error metrics, Root Mean Square Error(RMSE) and Mean Absolute Error(MAE) which are equal to 5.70 and 4.76 and it suggests that the ARIMA(4,1,4)(1,1,1)12 model has a strong potential in forecasting the income of pepper exports in Sri Lanka. As the forecasts from the model shows an increasing pepper export market which will need a higher production of pepper, the government can improve the awareness of farmers about the requirements of pepper in export market by providing infra-structure facilities. Forecasts also depicts an important piece of information for Sri Lankan pepper exporters and potential investors to consider about long term investment decisions in the pepper export marketItem Statistical modelling of monthly electricity sales in Colombo: ARIMA approach(Research Symposium on Pure and Applied Sciences, 2018 Faculty of Science, University of Kelaniya, Sri Lanka, 2018) Herath, H. M. R. D. S.; Varathan, N.Electricity is the most essential form of energy, used all over the globe. It has influenced the economy, public health, technological growth and all other spheres of human activities. The electricity sales are growing day by day with the population growth and industrialization, etc. Even though Sri Lanka is a developing country, it has shown a huge progress, showing a national electrification ratio of 99.7% in 2017. Colombo; the capital of Sri Lanka, is the main commercial hub with the largest population and by far the most developed city in Sri Lanka. This study investigates to develop a suitable time series model for the monthly electricity sales of Colombo City. The monthly electricity sales data was obtained from Ceylon Electricity Board during the period of January 1982 to December 2016. The data analysis has been done using the Box-Jenkin’s Auto Regressive Integrated Moving Average (ARIMA) procedure. Results reveal that, the SARIMA (0,1,2)(0,1,1)12 is the most appropriate model for the monthly electricity sales data. Moreover, Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Mean Square Error (MSE) were used to select the best model. Further, adequacy of the best model has been checked using Ljung-Box Chi-Squared test. Finally, the monthly electricity sales for the year 2017 were predicted using the selected best model.Item Forecasting monthly household water consumption supplied by NWSD, Sri Lanka(Faculty of Science, University of Kelaniya, Sri Lanka, 2016) Perera, M.L.D.M.; Hewaarachchi, A.P.Water is an essential element for the survival of mankind and water supply is a pressing issue in this century. Household water use is generally the most important component of water consumption. In Sri Lanka, lack of freshwater has become a serious problem due to factors like population growth, overall expansion in economic activities, increased urbanization and changing climate patterns. Then as a country, managing water resources more efficiently has become a priority. This it is vital to forecast future monthly water consumption of households for planning purposes of further developments of the country. In this research, we aim to determine a suitable model for monthly household water consumption supplied by National Water Supply & Drainage Board (NWSDB), Sri Lanka in order to forecast future household water consumption. We consider monthly household water consumption data in Sri Lanka for the period from January 2005 to August 2016. The data shows an upward trend which suggests that the series is non-stationary. Also, data displays increasing variability and there’s a need to apply data transformation to stabilize the variance. Then, differencing techniques are applied to obtain a stationary series. Using Box-Jenkins methodology SARIMA (Seasonal Autoregressive Integrated Moving Average) model is identified as a reasonable model for the data. The result showed among several plausible ARIMA models, ARIMA (2, 1, 0) (1, 0, 1)12 model was appropriate for forecasting future values as it has the smallest AIC (Akaike information criterion) value. As a model validation technique, this model is then used to forecast last 5% of observations of data set. The accuracy of forecast error was assessed by mean percent error (MPE), mean absolute squared error (MASE) and mean absolute percent error (MAPE). The measures were 0.488, 0.287 and 2.213 respectively. As a future work it will be worthwhile to forecast water consumption for different regions. Also, to improve the accuracy of forecasts, models, which incorporate influential factors such as monthly precipitation, number of new connection will be considered.