EXPLORING MACHINE LEARNING AND DEEP LEARNING APPROACHES FOR MULTI-STEP FORECASTING IN MUNICIPAL SOLID WASTE GENERATION

Exploring Machine Learning and Deep Learning Approaches for Multi-Step Forecasting in Municipal Solid Waste Generation

Municipal Solid Waste (MSW) management enact a significant role in protecting public health and the environment.The main objective of this paper is to explore the utility of using Lotions state-of-the-art machine learning and deep learning-based models for predicting future variations in MSW generation for a given geographical region, considering i

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An experimental study and a proposed theoretical solution for the prediction of the ductile/brittle failure modes of reinforced concrete beams strengthened with external steel plates

An experimental study is conducted and a theoretical solution is proposed in the present study to investigate the ductile/brittle failure mode of reinforced concrete (RC) beams strengthened with an external steel plate.In the present experimental study, 6 steel plate-strengthened RC beams and 1 non-strengthened RC beam are fabricated and tested und

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Mitochondrial COI Sequence Variations within and among Geographic Samples of the Hemp Pest Psylliodes attenuata from China

The hemp flea beetle Psylliodes attenuata (Coleoptera: Chrysomelidae: Psylliodes) is a common pest of Cannabis sativa, including cultivars of both industrial hemp and medicinal marijuana.Both the larval and adult stages of this beetle can cause significant damages to C.sativa, resulting in substantial crop losses.At present, little is known about t

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