Results 61 to 70 of about 54,005 (235)

Data‐Driven Feedback Identifies Focused Ultrasound Exposure Regimens for Improved Nanotheranostic Targeting of the Brain

Advanced Science, EarlyView.
Machine learning models predict in real time the onset of harmful microbubble collapse during microbubble‐enhanced focused ultrasound (MB‐FUS) and enable dynamic adjustment of sonication to prevent cavitation‐induced damage. This predictive control expands the safe operating window for bloodbrain barrier opening, enhancing nanoparticle delivery and ...
Hohyun Lee, Victor Menezes, Shiqin Zeng, Chulyong Kim, Cynthia M. Baseman, Jae Hyun Kim, Samhita Padmanabhan, Pranav Premdas, Naima Djeddar, Anton Bryksin, Nikhil Pandey, Pavlos Anastasiadis, Anthony J. Kim, Tobey J. MacDonald, Chetan Bettegowda, Graeme F. Woodworth, Felix J. Herrmann, Costas Arvanitis   +17 more
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

An accelerated adaptive two-step Levenberg–Marquardt method with the modified Metropolis criterion

AIMS Mathematics
In this paper, aiming at the nonlinear equations, a new two-step Levenberg–Marquardt method was proposed. We presented a new Levenberg–Marquardt parameter to obtain the trial step. A new modified Metropolis criterion was used to adjust the upper bound of
Dingyu Zhu, Yueting Yang, Mingyuan Cao
doaj   +1 more source

Modeling Leachate Generation Using Artificial Neural Networks [PDF]

آب و فاضلاب, 2011
In this study, a neural network model is proposed for modeling leachate flow-rate in a municipal solid waste landfill site. After training, the neural network model predicts leachate generation based on meteorological data and leachate characteristics ...
Mohammad Javad Zoqi, Mohsen Saeedi
doaj  

Parameter identification problems in the modelling of cell motility [PDF]

, 2014
We present a novel parameter identification algorithm for the estimation of parameters in models of cell motility using imaging data of migrating cells.
A Friedman, A Mogilner, AM Stuart, AS Ackleh, AS Ackleh, B Onken, Björn Stinner, C Hogea, C Jiang, C Weston, Cathryn Weston, Chandrasekhar Venkataraman, Charles M. Elliott, CT Kelley, D Bray, D Dormann, DW Marquardt, F Haußer, FD Kelly, G Dziuk, G Dziuk, G Dziuk, G Dziuk, Graham Ladds, H Tatebe, I Hecht, IF Sbalzarini, J Alamo Del, J Barrett, J Barrett, J Nocedal, J Satulovsky, JF Monahan, K Deckelnick, K Deckelnick, L Bosgraaf, M Burger, M Herant, M Lombardi, M Mos, M Neilson, MA Dewar, MA Iglesias, MJ Pittet, MR Garvie, O Lakkis, R Lefever, T Drake, TF Chan, V Isakov, Wayne Croft   +50 more
core   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

Comparative performance of some popular ANN algorithms on benchmark and function approximation problems

, 2009
We report an inter-comparison of some popular algorithms within the artificial neural network domain (viz., Local search algorithms, global search algorithms, higher order algorithms and the hybrid algorithms) by applying them to the standard ...
A. Bora, A. Bora, A. K. Tickoo, A. S. Miller, B. P. Dubey, C. L. Giles, C. Lanczos, C. T. Lin, D. Barry, D. E. Rumelhart, E. W. M. Lee, G. A. Carpenter, H. P. Singh, H. P. Singh, J. C. Jia, J. Hertz, J. Lee, L. Breiman, L. Breiman, L. Canal, M. Abramowitz, M. Bazarghan, M. Caudill, M. F. Moller, N. Metropolis, R. A. Fisher, R. Gupta, R. K. Bock, R. Koul, R. Sinkus, R. Tagliaferri, S. Chen, S. Kirkpatrick, T. Denoeux, T. Hastie, V. K. Dhar, V. K. Dhar, W. Bryc, X. Wang   +38 more
core   +1 more source

ANN‐Enabled Analysis of Nanoparticle Aggregation and Hall Effects on Ag‐H2O Nanofluid Flow Over a Spinning Disk With Convective Heating and Thermal Radiation

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT The exceptional characteristics of nanofluids have turned out to be a significant development in revolutionizing heat transfer mechanisms in several electronic cooling devices and industrial manufacturing processes. The present study deals with the investigation of the second law of thermodynamics applied to the steady MHD fluid flow above a ...
Dixita Sonowal, Bidyasagar Kumbhakar
wiley   +1 more source

Diagnostic and prognostic analysis of oil and gas pipeline with allowable corrosion rate in Niger Delta Area, Nigeria

Journal of Applied Sciences and Environmental Management, 2019
This paper presents diagnostic and prognostic analysis of oil and gas pipeline industries with allowable corrosion rate using artificial neural networks approach.
M. Obaseki
doaj   +1 more source

Fitting in a complex chi^2 landscape using an optimized hypersurface sampling

, 2011
Fitting a data set with a parametrized model can be seen geometrically as finding the global minimum of the chi^2 hypersurface, depending on a set of parameters {P_i}. This is usually done using the Levenberg-Marquardt algorithm.
A. Benveniste, A. Patil, D. Sivia, J. -F. Moulin, J. Ll. Tamarit, L. C. Pardo, M. Rovira-Esteva, O. Gereben, S. Busch, T. Bayes, V. S. Borkar, W. H. Press   +11 more
core   +1 more source