Results 91 to 100 of about 149,415 (266)

Foundational Machine‐Learning Interatomic Potential for Simulating Chemically Complex Ni‐Based Superalloys

Advanced Engineering Materials, EarlyView.
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma, Sarath Menon, Fritz Körmann, Thomas Hammerschmidt, Ralf Drautz   +4 more
wiley   +1 more source

Efficient and Robust Parameter Tuning for Heuristic Algorithms

International Journal of Industrial Engineering and Production Research, 2013
The main advantage of heuristic or metaheuristic algorithms compared to exact optimization methods is their ability in handling large-scale instances within a reasonable time, albeit at the expense of losing a guarantee for achieving the optimal solution.
Hossein Akbaripour, Ellips Masehian
doaj  

Lottery Rank-Pruning Adaptation Parameter Efficient Fine-Tuning

Mathematics
Recent studies on parameter-efficient fine-tuning (PEFT) have introduced effective and efficient methods for fine-tuning large language models (LLMs) on downstream tasks using fewer parameters than required by full fine-tuning.
Juhyeong Kim, Gyunyeop Kim, Sangwoo Kang
doaj   +1 more source

Deep learning classification of urinary sediment crystals with optimal parameter tuning. [PDF]

Sci Rep, 2022
Nagai T, Onodera O, Okuda S.
europepmc   +1 more source

Microstructure Modification of Additively Manufactured Mo–9Si–8B by Annealing and Its Effects on High‐Temperature Mechanical Properties

Advanced Engineering Materials, EarlyView.
Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt, Yong Chen, Georg Hasemann, Benjamin Wahlmann, Carolin Körner, Manja Krüger   +5 more
wiley   +1 more source

High-accuracy ECG image interpretation using parameter-efficient Low-Rank Adaptation (LoRA) fine-tuning with multimodal LLaMA V.3.2

BMJ Digital Health & AI
Objective To develop and evaluate a high-accuracy ECG image interpretation model using parameter-efficient Low-Rank Adaptation (LoRA) fine-tuning with the multimodal LLaMA V.3.2 model.Methods and analysis We fine-tuned the multimodal LLaMA V.3.2 model ...
Nandakishor Mukkunnoth, Anjali Mukkunnoth, Meenakshi Khapre, Sudarshan Benamanahalli Puttaswamy   +3 more
doaj   +1 more source

The Improved Particle Swarm Optimization Method: An Efficient Parameter Tuning Method with the Tuning Parameters of a Dual-Motor Active Disturbance Rejection Controller. [PDF]

Sensors (Basel), 2023
Deng Y, Zhu J, Liu H.
europepmc   +1 more source

Uniform Amorphization of Crystalline Silicon Surfaces Enabled by Deep Ultraviolet Femtosecond Laser Pulses

Advanced Engineering Materials, EarlyView.
Deep‐UV (258 nm) femtosecond pulses enable uniform amorphous silicon writing on Si(100)/(111) with a six‐fold larger fluence amorphization window than NIR methods. Optimized fluence and overlap yield 20–45 nm uniform and continuous amorphous layers. Microscopy shows sharp interfaces, and real‐time reflectivity reveals nanosecond melt–resolidification ...
Wissal Benali, Magali Gregoire, Matys Guyard, Tatiana Itina, David Grojo, Pol Sopeña   +5 more
wiley   +1 more source

Zasada szczególnego dostrojenia w kontekście układów z chaosem deterministycznym

Zagadnienia Filozoficzne w Nauce, 2008
From the beginning of the deterministic chaos research, the unpredictability has been its central theme. Interesting questions arise here: What are the consequences of chaos for the fine tuned processes? Are there fine tuning systems in reality?
Bartłomiej Brus, Marek Szydłowski
doaj  

M-Race: A Racing Algorithm for the Tuning of Meta-Heuristics Based on Multiple Performance Objectives

Applied Sciences
The performance of meta-heuristic algorithms on optimisation problems depend on the values of control parameters. These parameters greatly influence the behaviour of algorithms and affect the quality of the solutions.
Christoff Jordaan, Andries Engelbrecht, Kian Anderson   +2 more
doaj   +1 more source