Search alternatives:
property optimization » process optimization (Expand Search), policy optimization (Expand Search), robust optimization (Expand Search)
linear based » lines based (Expand Search), linear unbiased (Expand Search), linear lagged (Expand Search)
property optimization » process optimization (Expand Search), policy optimization (Expand Search), robust optimization (Expand Search)
linear based » lines based (Expand Search), linear unbiased (Expand Search), linear lagged (Expand Search)
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The Effect of Machine Learning Algorithms on the Prediction of Layer-by-Layer Coating Properties
Published 2023Subjects: -
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Nonparametric and Semiparametric Quantile Regression via a New MM Algorithm
Published 2023“…Hunter and Lange proposed an MM algorithm for solving optimization problems in parametric quantile regression models. …”
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Cut-based matheuristic algorithms to detect tacit collusion in deregulated electricity markets
Published 2025“…The performance of the algorithms is compared with each other based on their capacity in identifying collusive states and the required computational effort.…”
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An Asymptotic Analysis of Random Partition Based Minibatch Momentum Methods for Linear Regression Models
Published 2022“…Despite the great popularity of the MGDM methods in practice, their theoretical properties are still underexplored. To this end, we investigate the theoretical properties of MGDM methods based on the linear regression models. …”
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Buffer allocation problem in production flow lines: A new Benders-decomposition-based exact solution approach
Published 2021“…This work proposes a new Mixed-Integer Linear Programming (MILP) formulation for exact solution of sample-based BAP. …”
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Table1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.docx
Published 2024“…The single, double, and triple kernel functions were RBF kernel function, the integration of RBF and polynomial kernel functions, and the integration of RBF, polynomial, and linear kernel functions respectively. The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”
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DataSheet1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.ZIP
Published 2024“…The single, double, and triple kernel functions were RBF kernel function, the integration of RBF and polynomial kernel functions, and the integration of RBF, polynomial, and linear kernel functions respectively. The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”
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