Results 101 to 110 of about 273,096 (313)
Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites
Advanced Functional Materials, EarlyView.A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou +5 more
wiley +1 more source
IS ARTIFICIAL NEURAL NETWORK INTELLIGENT?
International Journal of Computing, 2011 This article was originally written for the purpose of breaking the ice in the round table discussion held in the conference. Since the name of the conference is ‘Neural Network and Artificial Intelligence’ the topic of this article is, “What is intelligence?” when we talk about artificial intelligence in general, and artificial neural network in ...
openaire +2 more sources
Advanced Functional Materials, EarlyView.Field‐free spin‐orbit torque domain‐wall synapses integrated with stochastic MTJ neurons enable compact hardware Boltzmann machines. Leveraging intrinsic stochasticity and multi‐level conductance, the system achieves efficient probabilistic learning with high accuracy, demonstrating a scalable spintronic platform for energy‐efficient edge AI.
Aijaz H. Lone +8 more
wiley +1 more source
An Overview of the Use of Neural Networks for Data Mining Tasks [PDF]
, 2012 In the recent years the area of data mining has experienced a considerable demand for technologies that extract knowledge from large and complex data sources.
Frederic Stahl +5 more
core +1 more source
Advanced Functional Materials, EarlyView.A fully programmable, dual‐inductive switchable halide perovskite memristor is demonstrated through precise BDAI2‐mediated interface engineering. This ion‐modulating layer suppresses stochastic filamentary growth, enabling stable, non‐filamentary switching via dynamic barrier modulation.
So‐Yeon Kim, Juan Bisquert
wiley +1 more source
Artificial neural networks in biomedical engineering: a review
, 2001 This paper presents a review of applications of artificial neural networks in biomedical engineering area. Artificial neural networks in general are explained; some limitations and some proven benefits of neural networks are discussed.
L.C. Jain +5 more
core +1 more source
Artificial Neural Networks [PDF]
Journal of the Royal Society of Medicine, 1999 D, Partridge, S, Rae, W J, Wang
openaire +2 more sources
Future Business Journal, 2016 The purpose of this study is to investigate the customer–service provider relationship in the insurance industry using artificial neural networks and linear regression. Using a sample of 389 customers from 10 different startup insurance companies, it was
Azarnoush Ansari, Arash Riasi
doaj +1 more source
Advanced Functional Materials, EarlyView.Backbone modulation in glycolated conjugated polymers governs ion accessibility to side chains, strengthes anion adsorption, and suppresses back‐diffusion. As the number of thiophene units increases, structural reorganization, retention, and synaptic plasticity are enhanced, leading to improved neuromorphic performance in electrolyte‐gated organic ...
Junho Sung +10 more
wiley +1 more source
Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage
Brain SciencesBackground: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing ...
Yongqiang Zhang +5 more
doaj +1 more source