Development of Regression Process for Storage Time of Natural Rubber Latex Classification using Microwave frequencies
Keywords:
Storage time of natural latex, Dielectric properties, Microwave transmission, Artificial neural networksAbstract
This work presents a low complex time storage measurement of natural latex using the microwave transmission technique. The transmission power obtained from natural latex measurements are simulated and then analyzed by artificial neural networks to classify storage time. The storage time of natural latex was analyzed by continuously measuring the dielectric properties for 12 hours. Then they were used to model in simulation. In the simulation, two pairs of double frequencies transmitting and receiving antennas: the first pair at the frequencies of 10.2 and 10.4 GHz and the second one at the frequencies of 10.2 and 10.6 GHz, were used to transmit and receive the microwave signals through natural latex. The transmission power, |S12|, |S21|, |S34|, and |S43| were used in training the artificial neural networks to develop the accurate decision-making process. The optimum structure of artificial neural networks consisted of four input nodes, eight hidden nodes, and one output node with the learning rate 0.1 that provided 97.62% accuracy. It shows that the efficiency of the presented decision-making process with artificial neural networks is suitable for storage time classification of natural latex application.
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