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Nomenclature Abbreviation LSTM Long Short-Term Memory FATCN Fusion Attention Temporal Convolutional Network GFA Gasified Fly Ash NO Nx Nitrogen Oxides CO 2 Carbon Dioxide NTP Non-Thermal Plasma TiO 2 Titanium Dioxide PM2.5 Particulate Matter 2.5 (fine particulates) RR-TENG Rabbit hair-based Rotary friction Triboelectric Nanogenerator CTO Catalytic Thermal Oxidation CO Catalytic Thermal Oxidation RNN Recurrent Neural Networks HDT Hot Air Flow (Airflow Drying Machine) NaHCO 3 Sodium Bicarbonate Na 2 CO 3 Sodium Carbonate [BMM] PF 6 Supported Ionic Liquid Membrane RH Relative Humidity MSE Mean Squared Error O Oxygen atoms OH Hydroxyl Radicals HO 2 Hydrogen Peroxide Radicals NO Nitric Oxide O 3 Ozone SPWM Sine Wave Pulse Width Modulation Symbol d Number of input features h Size of the hidden layer n Number of tobacco samples F Number of features (specifically 16 features) L Length of a certain monitoring data sequence N Number of roasting data samples PT Pressure Sensor OT Oxygen Content Sensor TT Temperature Sensor MT Online Moisture Meter PDT Differential Pressure Sensor A Grade of tobacco leaves B Grade of tobacco leaves i t Input Gate f t Forget Gate o t Output Gate (LSTM) c t Memory Cell (Current time step) c t-1 Memory Cell (Previous time step) h t Hidden layer state (Current time step) h t-1 Hidden state (Previous time step) x t Input (Moisture content at current time step) y t Output of LSTM Q Query Matrix (FATCN) K Key Matrix (FATCN) V Value Matrix (FATCN) Greek symbol Sigmoid Activation function or general Activation function Time span (FATCN) Length of the sliding window (LSTM) s Sliding step (LSTM) Average deviation Weight parameters Data availability The datasets used and analysed during the current study are available from the corresponding author on reasonable request

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