Energy use is on the rise due to an increase in the number of households and general consumptions. It is important to estimate and forecast the number of houses and the resultant energy consumptions to address the effective and efficient use of energy in future planning. In this paper, the number of houses in Brunei Darussalam is estimated by using Spline interpolation and forecasted by using two methods, namely an autoregressive integrated moving average (ARIMA) model and nonlinear autoregressive (NAR) neural network. The NAR model is more accurate in forecasting the number of houses as compared to the ARIMA model. The energy required for water heating and other appliances is investigated and are found to be 21.74% and 78.26% of the total energy used, respectively. Through analysis, it is demonstrated that 9 m² solar heater and 90 m² of solar panel can meet these energy requirements.

中文翻译：

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家庭应用能源需求的建模和预测。


由于家庭数量和一般消费的增加，能源使用量不断增加。估计和预测房屋数量以及由此产生的能源消耗对于在未来规划中有效和高效地利用能源非常重要。本文利用样条插值法估算文莱达鲁萨兰国的房屋数量，并采用自回归综合移动平均（ARIMA）模型和非线性自回归（NAR）神经网络两种方法进行预测。与 ARIMA 模型相比，NAR 模型在预测房屋数量方面更加准确。调查发现，热水器和其他器具所需的能源分别占总能源消耗的21.74%和78.26%。通过分析，证明9 m ²太阳能加热器和90 m ²太阳能电池板可以满足这些能源需求。