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This study evaluates the effectiveness of a Novel Recurrent Neural Network (RNN) against Natural Language Processing (NLP) methods for nutrient extraction from soaked and steamed nut water. Research Instruments and Methodologies: Ten nutrients were retrieved utilizing advanced RNN and NLP approaches. The iteration value was estimated using G-power analysis with a power of 0.8 and a 95% confidence range. The findings indicated that the Novel RNN method attained an accuracy of 84.10%, surpassing the NLP approach's 71.48%. A statistical analysis indicated that the two approaches exhibited a substantial difference, evidenced by a two-tailed p-value of 0.000 (p < 0.05). The results indicate that the Novel RNN surpasses NLP methods in nutrient extraction accuracy, rendering it a more dependable option for this work.
Lekhya et al. (Sun,) studied this question.