Tea export plays a vital role in the Sri Lankan economy. It is of immense importance to forecast the prices in the Colombo Tea Auction Center (CTAC) at which a majority of the Sri Lankan tea is marketed. There was no evidence of former studies on forecasting prices of tea at CTAC. The most familiar and the standard practice in the conventional context for forecasting a series varying with time is the building of time series models based on the stationarity and the characteristics of the relevant series, which are autoregressive (AR) terms and moving average (MA) terms. But the auction prices of tea are inherently noisy, non-stationary and chaotic in nature and therefore, the conventional methods cannot be applied. Alternatively, time series regression with generalized least as two suitable methods for forecasting the price for a unit of Sri Lankan tea at the CTAC one month ahead. Models were centers worldwide and assessed and compared using the mean absolute percentage error (MAPE), mean squared error to perform well, ANN performing slightly better.

Abstract:the maximum or minimum response in a cause and effect of boundary points especially when there are not any multiple responses at values of the explanatory variable is ad hoc. Existing methods involve dividing the range of explanatory variable into bins and considering points with the maximum response or the response above some value in each bin. However, the results depend heavily on the way of dividing into bins and the number of bins. There is no agreement on the best way of dividing or the number of bins. Furthermore, the least square line is not consistent with the theory of limiting response because it goes through the points rather than going above all the points or below all the points, representing the boundary. This paper presents a new method that avoids all the above drawbacks. It involves the theory of linear programming. The proposed method has been compared with commonly used methods by using simulated data and shown to perform better. The method is illustrated by applying to experimental data on the response of latex yield of natural rubber to leaf nutrient concentrations.

The General Certificate of Education (Ordinary Level) (G.C.E O/L) examination is the first most important public certificate examination in Sri Lanka. Most of the candidates „fail‟ the G.C.E (O/L) examination due to their failure in Mathematics, leaving them without any viable option for their future. Identification of factors related to the results of Mathematics is essential to rectify this problem. This paper presents some findings of a study carried out in 2008 to explore the factors related to the results of Mathematics of the G.C.E (O/L) examination. The necessary data were collected from a survey conducted in the Piliyandala Educational Zone. The components of the syllabus that are most weighted in the marking scheme and the components preferred by the students were identified. The external factors that are associated with Mathematics marks were also identified through analysis of variance and regression analysis. Findings are useful to those who design curricula as well as to the teachers and parents.

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