Results 111 to 120 of about 122,614 (295)

Advanced Design for Weakly Coupled Resonators by Automatic Active Optimization

Advanced Materials Technologies, EarlyView.
An Automatic Active Optimization (AAO) strategy integrates machine learning predictors and genetic algorithms in a closed‐loop workflow. By iteratively expanding its dataset with new discoveries, AAO overcomes the limits of conventional methods. This approach finds superior microstructural designs beyond the initial sample space. We demonstrate this on
Wei Yue, Yuan Gao, Fanping Sui, Jason Wang, Megan Teng, Peggy Tsao, Huicong Deng, Yande Peng, Liwei Lin   +8 more
wiley   +1 more source

A Two-Step Simulated Annealing Algorithm for Spectral Data Feature Extraction. [PDF]

Sensors (Basel), 2023
Pei J, Xu L, Huang Y, Jiao Q, Yang M, Ma D, Jiang S, Li H, Li Y, Liu S, Zhang W, Zhang J, Tan X.   +12 more
europepmc   +1 more source

UN ALGORITMO DI SIMULATED ANNEALING PER LA SOLUZIONE DI UN PROBLEMA DI SCHEDULING [PDF]

An algorithm of "Simulated Annealing" for solving scheduling problems is presented. The issues related to scheduling are discussed, together with the Simulated Annealing approximation method and its main parameters (freezing, temperature, cooling, number
Crescenzio Gallo
core  

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

Optimization of a Simulated Annealing Algorithm for S-Boxes Generating. [PDF]

Sensors (Basel), 2022
Kuznetsov A, Wieclaw L, Poluyanenko N, Hamera L, Kandiy S, Lohachova Y.   +5 more
europepmc   +1 more source

Simulated Annealing Clusterization Algorithm for Studying the Multifragmentation [PDF]

, 2000
We present the details of the numerical realization of the recently advanced algorithm developed to identify the fragmentation in heavy ion reactions.
Aichelin, Jörg, Puri, R K
core   +1 more source

AutomataGPT: Transformer‐Based Forecasting and Ruleset Inference for Two‐Dimensional Cellular Automata

Advanced Science, EarlyView.
We introduce AutomataGPT, a generative pretrained transformer (GPT) trained on synthetic spatiotemporal data from 2D cellular automata to learn symbolic rules. Demonstrating strong performance on both forward and inverse tasks, AutomataGPT establishes a scalable, domain‐agnostic framework for interpretable modeling, paving the way for future ...
Jaime A. Berkovich, Noah S. David, Markus J. Buehler   +2 more
wiley   +1 more source

基于混合退火遗传算法的圆柱蜗杆传动模糊优化设计

Jixie chuandong, 2006
The limitations of the primary genetic algorithm applied to practice are discussed, including poor local search ability, premature convergence etc.
马景槐, 王江涛
doaj  

Slow Heat-Based Hybrid Simulated Annealing Algorithm in Vehicular Ad Hoc Network. [PDF]

Comput Intell Neurosci, 2023
Pagadala PK, Kumari PLS, Thakur D, Bhardwaj V, Shahid M, Buradi A, Razak A, Ketema A.   +7 more
europepmc   +1 more source

An improved simulated annealing algorithm for standard cell placement [PDF]

Simulated annealing is a general purpose Monte Carlo optimization technique that was applied to the problem of placing standard logic cells in a VLSI ship so that the total interconnection wire length is minimized.
Banerjee, Prithviraj, Jones, Mark
core   +1 more source