5 results for “Gaussian process regression”

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Research ArticleOpen accessPhrase in the titleSoft Sensor Modeling of Product Concentration in Glutamate Fermentation using Gaussian Process RegressionRongjian Zheng, Feng PanThe on-line control of glutamate fermentation process is difficult, owing to the typical uncertainties of biochemical process and the lack of suitable on-line sensors for primary process variables. A prediction model based on Gaussian Process Regression (GPR) is presented to predict glutamate concentration online. First, Partial Least Squares (PLS) is applied to extract the features of the input secondary variables … …American Journal of Biochemistry and Biotechnology, Vol. 12, Issue 3 · 17 Sep 2016 · 7,663 accessesView PDF Cite

Research ArticleOpen accessPhrase in the titleA Gaussian Process Regression Model for the Traveling Salesman ProblemWanatchapong Kongkaew, Juta PichitlamkenProblem statement: Traveling Salesman Problem (TSP) is a famous NP hard problem. Many approaches have been proposed up to date for solving TSP. We consider a TSP tour as a dependent variable and its corresponding distance as an independent variable. If a predictive function can be formulated from arbitrary sample tours, the optimal tour may be predicted from this function. … …Journal of Computer Science, Vol. 8, Issue 10 · 30 Aug 2012 · 7,367 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCalculation of the Hubble Constant, the Minimum Mass and the Proton Charge Radius Using the Dirac's Hypothesis on the Ratio of the Electrostatic Force to the Gravitational ForcePaul TalbotAtoui, M., Barbaro, M. B., Hoballah, M., Keyrouz, C., Lassaut, M., Marchand, D., Quéméner, G., & Voutier, E. (2023). Determination of the Moments of the Proton Charge Density. ArXiv, 13521. https://doi.org/10.48550/arXiv.2304.13521 Berman, M. S. (1992). Large Number Hypothesis. International Journal of Theoretical Physics, 31, 1447–1450. https://doi.org/10.1007/bf00673977 Beyer, A., Maisenbacher, L., Matveev, A., Pohl, R., Khabarova, K., Grinin, A., Lamour, T., … …Physics International, Vol. 14, Issue 1 · 2 Sep 2023 · 9,106 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAccessing the Appropriateness of a Spatial Regression Using Generalized (h1h2-)Slepian Random FieldWayan Somayasa, Jamhir Safani, La Ode Ngkoimani, Muhamad Zamrun F.In this study we derived asymptotic goodness-of-fit test (model check) for spatial regression where the critical region as well as the p-value of the tests are approximated based on the distribution of a type of the integral functional of the generalized (h1h2-)-Slepian field and the set-indexed Gaussian white noise. Such random fields are obtained as the limit process of the … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 2 May 2017 · 7,362 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Novel Algorithmic Cost Estimation Model Based on Soft Computing TechniqueIman Attarzadeh, Siew Hock OwProblem statement: Software development effort estimation is the process of predicting the most realistic use of effort required for developing software based on some parameters. It has always characterized one of the biggest challenges in Computer Science for the last decades. Because time and cost estimate at the early stages of the software development are the most difficult to obtain … …Journal of Computer Science, Vol. 6, Issue 2 · 28 Feb 2010 · 7,927 accessesView PDF Cite