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However, the difficulty in generating rich reservoir states using two\u2010terminal devices remains challenging, which hinders its hardware implementation. Herein, the 1D array of ferroelectric field\u2010effect transistor (Fe\u2010FET) based on <jats:italic>\u03b1<\/jats:italic>\u2010In<jats:sub>2<\/jats:sub>Se<jats:sub>3<\/jats:sub> channel, which shows volatile memory effect for realizing various RC systems, is demonstrated. The fading effect in <jats:italic>\u03b1<\/jats:italic>\u2010In<jats:sub>2<\/jats:sub>Se<jats:sub>3<\/jats:sub> is sufficiently investigated by polarization dynamic model. The proposed Fe\u2010FET is capable of experimentally classifying images using MNIST dataset with a high accuracy of 91%. Furthermore, time\u2010series real\u2010life chaotic system, for example, Earth's weather, can be accurately forecasted using our Ferro\u2010RC based on the Jena climate dataset recorded in a 1\u2009year period. Remarkable determination coefficient (<jats:italic>R<\/jats:italic>\n<jats:sup>2<\/jats:sup>) of 0.9983 and normalized root mean square error (NRMSE) of 8.3\u2009\u00d7\u200910<jats:sup>\u22123<\/jats:sup> are achieved using a minimized readout network. 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