Results 61 to 70 of about 118,790 (360)
An Active Set Algorithm for Nonlinear Optimization with Polyhedral Constraints [PDF]
, 2016 A polyhedral active set algorithm PASA is developed for solving a nonlinear optimization problem whose feasible set is a polyhedron. Phase one of the algorithm is the gradient projection method, while phase two is any algorithm for solving a linearly ...
Hager, William W., Zhang, Hongchao
core +3 more sources
New Investigation for the Liu-Story Scaled Conjugate Gradient Method for Nonlinear Optimization
, 2020 This article considers modified formulas for the standard conjugate gradient (CG) technique that is planned by Li and Fukushima. A new scalar parameter for this CG technique of unconstrained optimization is planned.
Eman T. Hamed +2 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.PARP inhibitors are used to treat a small subset of prostate cancer patients. These studies reveal that PARP1 activity and expression are different between European American and African American prostate cancer tissue samples. Additionally, different PARP inhibitors cause unique and overlapping transcriptional changes, notably, p53 pathway upregulation.
Moriah L. Cunningham +21 more
wiley +1 more source
FEBS Open Bio, EarlyView.Tandem VHH targeting distinct EGFR epitopes were engineered into a monovalent bispecific antibody (7D12‐EGA1‐Fc) with more potent ADCC without increasing affinity to EGFR. Structural modeling of 7D12‐EGA1‐Fc showed cross‐linking of separate EGFR domains to enhance CD16a engagement on NK cells.
Yuqiang Xu +5 more
wiley +1 more source
Diagonal preconditioned conjugate gradient algorithm for unconstrained optimization [PDF]
, 2014 The nonlinear conjugate gradient (CG) methods have widely been used in solving unconstrained optimization problems. They are well-suited for large-scale optimization problems due to their low memory requirements and least computational costs.
Leong, Wah June +2 more
core
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
Abstract and Applied Analysis, 2013 The nonlinear conjugate gradient method is of particular importance for solving unconstrained optimization. Finitely many maximum functions is a kind of very useful nonsmooth equations, which is very useful in the study of complementarity problems ...
Yuan-yuan Chen, Shou-qiang Du
doaj +1 more source
A survey on the Dai-Liao family of nonlinear conjugate gradient methods
RAIRO Oper. Res., 2023 At the beginning of this century, which is characterized by huge flows of emerging data, Dai and Liao proposed a pervasive conjugacy condition that triggered the interest of many optimization scholars. Recognized as a sophisticated conjugate gradient (CG)
S. Babaie-Kafaki
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView.Laser surface texturing significantly improves the corrosion resistance and mechanical strength of 3D‐printed iron polylactic acid (Ir‐PLA) for marine applications. Optimal laser parameters reduce corrosion by 80% and enhance tensile strength by 25% and ductility by 15%.
Mohammad Rezayat +6 more
wiley +1 more source
Shape Optimization with Nonlinear Conjugate Gradient Methods
, 2022 In this chapter, we investigate recently proposed nonlinear conjugate gradient (NCG) methods for shape optimization problems. We briefly introduce the methods as well as the corresponding theoretical background and investigate their performance numerically.
openaire +2 more sources