CROWD CONGESTION FORECASTING FRAMEWORK USING ENSEMBLE LEARNING MODEL AND DECISION MAKING ALGORITHM: UMRAH USE CASE

Crowd Congestion Forecasting Framework Using Ensemble Learning Model and Decision Making Algorithm: Umrah Use Case

Forecasting crowd congestion is a critical aspect of crowd management, particularly in dynamic and densely populated areas, such as urban centers, events, or pilgrimage sites.In this paper, Vintage Parts we proposed the first crowd congestion forecasting framework for the pilgrimage of Umrah.We addressed the crowd congestion forecasting problem by

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Global perspective of environmental distribution and diversity of Perkinsea (Alveolata) explored by a meta-analysis of eDNA surveys

Abstract Perkinsea constitutes a lineage within the Alveolata eukaryotic superphylum, mainly composed of parasitic organisms.Some described species represent significant ecological and economic threats due to their invasive ability and pathogenicity, which can lead to mortality events.However, the genetic diversity of these described species is jus

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