This thesis explores the enhancement of photovoltaic (PV) system reliability through the development and optimisation of machine learning algorithms for proactive fault detection. Utilising data from
本数据集名为‘Rare Event Classification in Multivariate Time Series’，由ProcessMiner, Inc.创建，主要用于预测纸张生产中的罕见事件——纸张断裂。数据集包含18,398条记录，涵盖了61个预测变量和1个二元响应变量。数据来源于纸浆和纸张制造行业的多传感器实时监测，旨在通过机器学习模型提前预测并防止纸张断裂事件。创建过程中，数据经过中
