Abstract Water security and urban flooding have become major sustainability issues. This paper presents a novel method to introduce rates of change as the state-of-the-art approach in artificial intelligence model development for agenda. Multi-layer perceptron (MLP) deep learning long short-term memory (LSTM) models were considered flood forecasting. Historical rainfall data from 2008 2021 at 1...

This paper presents a comprehensive error analysis of the day-ahead photovoltaic (PV) production multi-step forecasting model that uses chained support vector regression (SVR). A principal component (PCA) is also implemented to investigate possible improvements SVR prediction accuracy. Special attention was given hyper-parameter tuning and PCA+SVR models; specifically, dispersion errors when fi...

Results: There was no impact of the intervention on change in BMI from baseline to 12 ( 0.272; 95% CI 0.271, 0.782) or 24 months ( 0.276; 95% CI 0.338, 0.890) in intention-to-treat analysis. When intervention exposure (scale 0 to 100) was used as the independent variable, there was a decrease of 0.012 BMI units (95% CI 0.025, 0.001) for each unit increase in intervention participation at the 24...

Short-term wind and wind power forecasts are required for the reliable and economic operation of power systems with significant wind power penetration. This thesis presents new statistical techniques for producing forecasts at multiple locations using spatiotemporal information. Forecast horizons of up to 6 hours are considered for which statistical methods outperform physical models in general...

In Malaysia, Air Pollution Index (API) is used to assess the status of background air quality. The computation API involved six major pollutants including PM10, PM2.5, O3, CO, SO2 and NOx. Due harmful effect pollution, forecasting important. This paper introduces application Functional Time Series (FTS) model in monthly diurnal maximum curves at two selected sites Peninsular Malaysia; namely Sh...

This paper aims to propose a two-step approach for day-ahead hourly scheduling in a distribution system operation, which contains two operation costs, the operation cost at substation level and feeder level. In the first step, the objective is to minimize the electric power purchase from the day-ahead market with the stochastic optimization. The historical data of dayahead hourly electric power...

Precise forecasting of reference evapotranspiration (ET0) is one the critical initial steps in determining crop water requirements, which contributes to reliable management and long-term planning world’s scarce sources. This study provides daily prediction multi-step forward ET0 utilizing a long short-term memory network (LSTM) bi-directional LSTM (Bi-LSTM) model. For predictions, model’s accur...

This paper evaluates the effectiveness of selected volatility models in forecasting Value-at-Risk (VaR) for 1-day and 10-day horizons. The latter is the actual reporting horizon required by the Basel Committee on Banking Supervision, but not considered in existing studies. The autoregressive stochastic volatility (Taylor, 1982) is found to be less effective than simpler ARCH type models such as...