Forecasting international bandwidth capacity using linear and ANN methods [PDF]
An artificial neural network (ANN) can improve forecasts through pattern recognition of historical data. This article evaluates the reliability of ANN methods, as opposed to simple extrapolation techniques, to forecast Internet bandwidth index data that ...
Madden, Gary G, Tan, Joachim
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Testing Artificial Neural Network (ANN) for Spatial Interpolation
Journal of Geology & Geosciences, 2014 The aim of this research is to test Artificial Neural Network (ANN) package in GRASS 6.4 software for spatial interpolation and to compare it with common interpolation techniques IDW and ordinary kriging. This package was also compared with neural networks packages nnet and neuralnet available in software R Project. The entire packages uses multi-layer
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Advanced Electronic Materials, EarlyView.ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez +10 more
wiley +1 more source
Application of a generative adversarial network for multi-featured fermentation data synthesis and artificial neural network (ANN) modeling of bitter gourd-grape beverage production. [PDF]
Sci Rep, 2023 Gbashi S +6 more
europepmc +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Agribusiness, EarlyView.ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani +3 more
wiley +1 more source
Artificial neural network (ANN)-based estimation of the influence of COVID-19 pandemic on dynamic and emerging financial markets. [PDF]
Technol Forecast Soc Change, 2023 Naveed HM +5 more
europepmc +1 more source
AI in chemical engineering: From promise to practice
AIChE Journal, EarlyView.Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Forecasting blood demand for different blood groups in Shiraz using auto regressive integrated moving average (ARIMA) and artificial neural network (ANN) and a hybrid approaches. [PDF]
Sci Rep, 2022 Sarvestani SE +5 more
europepmc +1 more source
Rainfall-Runoff Modelling Using Artificial Neural Networks (ANNs). [PDF]
, 2007 Over the last decades or so, artificial neural networks (ANNs) have become one of the most promising tools for modelling hydrological processes such as rainfall-runoff processes. In most studies, ANNs have been demonstrated to show superior result compared to the traditional modelling approaches.
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