Grey- and rough-set-based seasonal disaster predictions: an analysis of flood data in India

摘要: In a globally competitive market, companies attempt to foresee the occurrences of any catastrophe that may cause disruptions in their supply chains. Indian subcontinent is prone frequent disasters related floods and cyclones. It essential for chain operating India predict occurrence such disasters. By doing so, disaster management relief teams can prepare worst. This research makes use grey seasonal prediction model forecast possible flood-related India. Flood data major flood period 10 years (2007–2017) have been taken analysis this context. We established first order with one variable, GM (1, 1), prediction; from results, we observe there are high chances during early monsoon (June–August), both 2018 2020. observing sequences on fatalities, likelihood death toll rise above 100 result disastrous consequences. Also, results compared using an enhanced rough-set-based model. From model, severe mid-2018 The will be useful organizations, NGOs State Governments carefully plan logistics network event Proposed methodology floods.