Liu, T., Jiang, H., & Chen, Q. (2022). Input features and parameters optimization improved the prediction accuracy of support vector regression models based on colorimetric sensor data for detection of aflatoxin B1 in corn. Microchemical journal, 178, 107407. https://doi.org/10.1016/j.microc.2022.107407
Citace podle Chicago (17th ed.)Liu, Tao, Hui Jiang, a Quansheng Chen. "Input Features and Parameters Optimization Improved the Prediction Accuracy of Support Vector Regression Models Based on Colorimetric Sensor Data for Detection of Aflatoxin B1 in Corn." Microchemical Journal 178 (2022): 107407. https://doi.org/10.1016/j.microc.2022.107407.
Citace podle MLA (9th ed.)Liu, Tao, et al. "Input Features and Parameters Optimization Improved the Prediction Accuracy of Support Vector Regression Models Based on Colorimetric Sensor Data for Detection of Aflatoxin B1 in Corn." Microchemical Journal, vol. 178, 2022, p. 107407, https://doi.org/10.1016/j.microc.2022.107407.