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Strategies for constructing mathematical models of nonlinear systems based on multiple linear regression models


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Qin-feng, D., Shuai, H., et. al. (2015). Application of support vector machine in drag reduction effect prediction of nanoparticles adsorption method on oil reservoir’s micro-channels. Journal of Hydrodynamics, 27(1), 99-104. Search in Google Scholar

Durst, P., Roth, V. L. (2015). Mainland size variation informs predictive models of exceptional insular body size change in rodents. Proceedings of the Royal Society of London B: Biological Sciences, 0239. Search in Google Scholar

Bandara, D., Velipasalar, S., Bratt, S., & Hirshfield, L. (2018). Building predictive models of emotion with functional near-infrared spectroscopy. International Journal of Human-Computer Studies, 110, 75-85. Search in Google Scholar

Sher, M. (2022). Flavor-changing neutral currents in the Higgs sector. Modern Physics Letters A, 37(22), 2230011. Search in Google Scholar

Mi, J. K., Han, S. K., Min, J. L., et al. (2017). Quality predictive models for whole flour of immature wheat during storage and consumer acceptance on its baked product. LWT - Food Science and Technology, 83, 42-49. Search in Google Scholar

Li, X., Dai, Y., Cheng, J. (2019). Research On Neural Network Quality Prediction Model Based On Genetic Algorithm. IOP Conference Series: Earth and Environmental Science, 267(4), 042026. Search in Google Scholar

Helms, D., Eilers, R., Metzdorf, M., et al. (2017). Leakage Models for High-Level Power Estimation. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 37(8), 1627-1639. Search in Google Scholar

Wu, M. Y., Lin, Y. H., Tseng, T. H., et al. (2019). A Small Cell Outage Prediction Method Based on RNN Model, 30(5), 268-278. Search in Google Scholar

Xie,, Y., Tuoyu, W. U., Sun J., et al. (2018). Sediment Compaction and Pore Pressure Prediction in Deepwater Basin of the South China Sea: Estimation from ODP and IODP Drilling Well Data. Journal of Ocean University of China, 17(1), 25-34. Search in Google Scholar

Anyama, Uzoma O., Igiri, et al. (2015). An Application of Linear Regression & Artificial Neural Network Model in the NFL Result Prediction. International Journal of Engineering Research & Technology. ESRSA Publications, 4, 457-461. Search in Google Scholar

Yan-Hong, G., Nan-Jing, Z. et al. (2016). Monitoring the Heavy Element of Cr in Agricultural Soils Using a Mobile Laser-Induced Breakdown Spectroscopy System with Support Vector Machine. Supported by the National High-Technology Research and Development Program of China under Grant Nos 2014AA06A513. Chinese Physics Letters, 33(8), 085201 (5pp). Search in Google Scholar

Bonomini, V., Zucchelli, L., Re, R., Ieva, F., Spinelli, L., Contini, D., et al. (2015). Linear regression models and k-means clustering for statistical analysis of fNIRS data. Biomedical Optics Express, 6(2), 615-630. Search in Google Scholar

Finkelstein-Shapiro, D., Calatayud, M., Atabek, O., et al. (2016). Nonlinear Fano interferences in open quantum systems: An exactly solvable model. Physical Review A, 063414. Search in Google Scholar

Brewick, P. T., Masri, S. F., Carboni, B., et al. (2017). Enabling reduced-order data-driven nonlinear identification and modeling through naïve elastic net regularization. International Journal of Non-Linear Mechanics, 94, 46-58. Search in Google Scholar

Yang, S., Park, S. Y., Ha, S. D. (2016). A predictive growth model of Aeromonas hydrophila on chicken breasts under various storage temperatures. LWT - Food Science and Technology, 69, 98-103. Search in Google Scholar

Mondal, C. (2022). Density dependence of symmetry energy and neutron skin thickness revisited using relativistic mean field models with nonlinear couplings. Physical Review C, 105(3), 034305. Search in Google Scholar

Lin, X. (2021). The Application of Machine Learning Models in the Prediction of PM2.5/PM10 Concentration, 94-101. Search in Google Scholar

Gyllenhammer, L. E., Alderete, T. L., Toledo-Corral, C. M., et al. (2016). Saturation of subcutaneous adipose tissue expansion and accumulation of ectopic fat associated with metabolic dysfunction during late and post-pubertal growth. International Journal of Obesity, 40(4), 601. Search in Google Scholar

Barnaby, N., Alison, R., et al. (2019). Importance of Variable Selection in Multimodal Prediction Models in Patients at Clinical High Risk for Psychosis and Recent-Onset Depression. JAMA psychiatry, 339. Search in Google Scholar

Talele, V., Vadaje, Y. (2022). An ANN-based data-predictive approach for comparative study between CFD finite difference and finite volume method. International Journal of Modern Physics C, 33(10), 22501039. Search in Google Scholar

Cheng, L., & Xia, X. (2019). Fusion Chaotic Prediction Model for Bearing Performance by Computer Technique. In 2019 2nd International Conference on Safety Produce Informatization (IICSPI) (pp. 627-629). IEEE. Search in Google Scholar

Berg, K. H., Rohde, G. E., Prøven, A., Benestad, E. E. P., Østensen, M., & Haugeberg, G. (2019). Sexual quality of life in patients with axial spondyloarthritis in the biologic treatment era. The Journal of rheumatology, 46(9), 1075-1083. Search in Google Scholar

Fitzray, B. J. (2015). Alzheimer’s Activities: Hundreds of Activities for Men and Women With Alzheimer’s Disease and Related Disorders: Vol 1. Journal of Rheumatology, 42(6), 1173–1174. Search in Google Scholar

Xiao, Q., Lu, J., Charles, M., et al. (2022). 0156 Rest-activity profiles among U.S. adults in a nationally representative sample: a functional principal component analysis. SLEEP, (Supplement 1), 1-13. Search in Google Scholar

Leung, Y. M., Cave, N. J., et al. (2018). Creation of a predictive equation to estimate fat-free mass and the ratio of fat-free mass to skeletal size using morphometry in lean working farm dogs. New Zealand veterinary journal, 66(5), 248-256. Search in Google Scholar

Pandey, A., Bahl, C., Sharma, S., Singh, N., & Behera, D. (2018). Functional role of CyclinD1 polymorphism (G870A) in modifying susceptibility and overall survival of North Indian lung cancer patients. Tumori Journal, 104(3), 179-187. Search in Google Scholar

Sabir, Z., Amin, F., Pohl, D., et al. (2020). Intelligence computing approach for solving second order system of Emden–Fowler model. Journal of Intelligent & Fuzzy Systems, 38(6), 7391-7406. Search in Google Scholar

eISSN:
2444-8656
Language:
English
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Volume Open
Journal Subjects:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics