Results 131 to 140 of about 30,189 (295)

Evaluation of precipitation forecasting methods and an advanced lightweight model

Environmental Research Letters
Precipitation forecasting is crucial for warning systems and disaster management. This study focuses on deep learning-based methods and categorizes them into three categories: Recurrent Neural Network (RNN-RNN-RNN), Convolutional Neural Network (CNN-CNN ...
Nan Yang, Chong Wang, Xiaofeng Li
doaj   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Analysis of Recurrent Neural Network and Predictions

, 2020
This paper analyzes the operation principle and predicted value of the recurrent-neural-network (RNN) structure, which is the most basic and suitable for the change of time in the structure of a neural network for various types of artificial intelligence
Jieun Park, Dokkyun Yi, Sangmin Ji
core   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

An Introduction to Recurrent Neural Networks (RNNs)

<strong> Understanding how RNNs work and its applications </strong> <strong> Author </strong> Wenyi Pi ( <strong> ORCID </strong> : 0009–0002–2884–2771) Introduction In the ever-evolving landscape of artificial intelligence (AI), bridging the gap between humans and machines has seen remarkable progress.
openaire   +1 more source

Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
wiley   +1 more source

Vehicle classification using a recurrent neural network (RNN)

, 2018
A device can receive GPS data or values for a set of metrics at a set of GPS points that form a GPS track of a vehicle. The device can determine additional values for additional metrics using the GPS data or the values for the set of metrics.
Samuele Salti, Francesco Sambo, Alessandro Lori, Luca Bravi, Leonardo Taccari, Matteo Simoncini   +5 more
core  

TAMNet: Temporal and adaptive‐frequency network with MixStyle for cross‐region oil and fluid production forecasting

Deep Underground Science and Engineering, EarlyView.
This paper presents temporal and adaptive‐frequency network with MixStyle (TAMNet), a deep time‐series modeling framework for accurate and robust multi‐well oil productivity forecasting. TAMNet integrates transformer and long short‐term memory architectures to capture both short‐ and long‐term temporal dependencies, enhanced by a temporal gate unit ...
Chunxi Yang, Leifeng Meng, Qinghu Fan, Ziang Guo, Ting Bao, Pingdong Zhong, Fulin Luo   +6 more
wiley   +1 more source

Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie, Arianna Damiani, Mahsa Khoshkhou, Luis A. Sanchez, Rachel J. Smith, Shruti H. Agashe, Jorge A. Gonzalez‐Martinez, Jennifer Hopp, Adam S. Charles, Sridevi V. Sarma, Joon‐Yi Kang   +10 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source