Results 211 to 220 of about 171,350 (313)

An Analysis of Elusive Relationships in Floating Zone Growth Using Data Mining Techniques

Advanced Theory and Simulations, EarlyView.
Ultra‐pure silicon single‐crystals can be grown by the Floating Zone (FZ) method. This study investigates intricate relationships between process stability measures and multiple growth parameters by applying data mining techniques on FZ simulations. Regression Trees identified multivariate relationships that help explaining complex interactions between
Lucas Vieira, Robert Menzel, Martin Holena, Natasha Dropka   +3 more
wiley   +1 more source

Q-Learning-Driven Butterfly Optimization Algorithm for Green Vehicle Routing Problem Considering Customer Preference. [PDF]

Biomimetics (Basel)
Meng W, He Y, Zhou Y.
europepmc   +1 more source

A path planning approach for mobile robots using short and safe Q-learning. [PDF]

PLoS One, 2022
Du H, Hao B, Zhao J, Zhang J, Wang Q, Yuan Q.   +5 more
europepmc   +1 more source

Machine learning approach for crude oil price prediction with Artificial Neural Networks-Quantitative (ANN-Q) model [PDF]

, 2010
Siti Norbaiti binti Abdullah, Xiao‐Jun Zeng   +1 more
openalex   +1 more source

SyMO: A Hybrid Approach for Multi‐Objective Optimization of Crystal Growth Processes

Advanced Theory and Simulations, EarlyView.
The hybrid SyMO (Symbolic regression Multi‐objective Optimization) framework combines Computational Fluid Dynamics (CFD), machine learning, and mathematical optimization techniques to investigate the effects of various process parameters, furnace geometries, and radiation shield material properties on key crystal quality metrics in Czochralski silicon (
Milena Petkovic, Natasha Dropka
wiley   +1 more source

Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering. [PDF]

PLoS One
Wang G.
europepmc   +1 more source

An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking. [PDF]

Sensors (Basel), 2022
Qu Z, Zhao X, Xu H, Tang H, Wang J, Li B.   +5 more
europepmc   +1 more source

The Frequency‐Domain Lattice Boltzmann Method (FreqD‐LBM): A Versatile Tool to Predict the QCM Response Induced by Structured Samples

Advanced Theory and Simulations, EarlyView.
FreqD‐LBM simulates the oscillatory flow at the surface of a QCM‐D resonator in the presence of structured adsorbates. It derives shifts of frequency and bandwidth (equivalent to dissipation) on different overtones. Applications include rough surfaces, adsorbed rigid particles, adsorbed viscoelastic particles, spheres floating freely above the surface,
Diethelm Johannsmann, Paul Häusner, Arne Langhoff, Christian Leppin, Ilya Reviakine, Viktor Vanoppen   +5 more
wiley   +1 more source

Improving predictions of rock tunnel squeezing with ensemble Q-learning and online Markov chain. [PDF]

Sci Rep
Fard HS, Parvin H, Mahmoudi M.
europepmc   +1 more source

Dynamic sub-route-based self-adaptive beam search Q-learning algorithm for traveling salesman problem. [PDF]

PLoS One, 2023
Zhang J, Liu Q, Han X.
europepmc   +1 more source