Browsing by Author "Balasooriya, S"

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    PublicationOpen Access
    Predictive Model for Monthly Made Tea Production in Sri Lanka
    (Department of Mathematics and Statistics, Faculty of Humanities and Sciences, SLIIT, 2025-10-10) Subasinghe, C; Wattegedara, N; Silva, T; Balasooriya, S; Dassanayake, K; Guruge, M.L
    This study forecasts monthly tea production in Sri Lanka by developing a suitable time series model to identify future trends in the national tea industry. The analysis is based on monthly made tea production data from January 2000 to June 2025, obtained from the Central Bank of Sri Lanka and the Sri Lanka Tea Board. After confirming the non-stationarity of the original series through the Augmented Dickey-Fuller test, both first-order and seasonal differencing were applied to achieve stationarity. The Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plotswere used to identify potential model structures.
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    PublicationEmbargo
    Using CNNs RNNs and Machine Learning Algorithms for Real-time Crime Prediction
    (IEEE, 2019-12-05) Rajapakshe, C; Balasooriya, S; Dayarathna, H; Ranaweera, N; Walgampaya, N; Pemadasa, N
    Over the recent years crime rates in Sri Lanka have drastically increased. Main priority of police is to prevent crime occurrences in order to enhance public safety. Criminals use advanced technologies, which make the crime investigations cumbersome. Police officers spend lot of time and effort on these investigations. A wide range of researches are being conducted in the areas of Artificial Intelligence (AI) and Neural Networks to automate crime detection and prediction. In this paper, we present machine learning and deep learning based E-police system to enhance public safety and support law enforcement. Main objective of the system is prevention of crimes. E-Police is an application that helps police officers to get informed about the incidents happening around in real-time. In addition, system provides predictions about possible crimes likely to take place in future so that precautions can be taken to prevent those.