Results 121 to 130 of about 212,585 (307)

Comparative evaluation of deep learning and machine learning techniques for sentiment analysis of electronic product review data [PDF]

ITM Web of Conferences
The primary thoughts, perceptions, attitudes, feedback, and even emotions expressed by people on social networking and e-commerce sites are the primary focus of sentiment analysis also referred to as opinion mining.
Nagelli Archana, Saleena B., Prakash B.
doaj   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Large‐Scale and Highly Reliable Hopfield Neural Networks Using Vertical NAND Flash Memory for the In‐Memory Associative Computing

Advanced Intelligent Systems, EarlyView.
Large‐scale Hopfield neural networks (HNNs) for associative computing are implemented using vertical NAND (VNAND) flash memory. The proposed VNAND HNN with the asynchronous update scenario achieve robust image restoration performance despite fabrication variations, while significantly reducing chip area (≈117× smaller than resistive random‐access ...
Jin Ho Chang, Jae Seung Woo, Suk‐Kang Sung, Ki‐Whan Song, Woo Young Choi   +4 more
wiley   +1 more source

Prediction Analysis of Greeting Gestures Based on Recurrent Neural Networks

JOIV: International Journal on Informatics Visualization
Human activity recognition, such as rehabilitation, sports, human behavior, etc., is developing rapidly. A Recurrent Neural Network (RNN) is a practical approach to human activity recognition research and sequential data.
Angga Wibowo, - Kurnianingsih, Eri Sato-Shimokawara   +2 more
doaj   +1 more source

A Review of Trans‐Dimensional Kirigami: From Compliant Mechanism to Multifunctional Robot

Advanced Intelligent Systems, EarlyView.
This review outlines recent advancements in the geometric design and mechanical properties of kirigami. The kirigami is classified into two categories from a compliant mechanism perspective, highlighting their applications in metamaterials and robotic systems. Finally, the future research directions, is explored focusing on the potential of integrating
Yang Yu, Jinyao Zhang, Dengchen Wang, Yanqi Yin, Yehui Wu, Ruiyu Bai, Jiaqiang Yao, Yupei Zhang, Jingwen Yin, Chao Tang, Alexey S. Fomin, Wenjie Sun, Chen Liu, Bo Li, Guimin Chen   +14 more
wiley   +1 more source

Multivariate Contrastive Predictive Coding with Sliding Windows for Disease Prediction from Electronic Health Records

Advanced Intelligent Systems, EarlyView.
Adaptive multi‐indicator contrastive predictive coding is introduced as a self‐supervised pretraining framework for multivariate EHR time series. An adaptive sliding‐window algorithm and 2D convolutional neural network encoder capture localized temporal patterns and global indicator dependencies, enabling label‐efficient disease prediction that ...
Hongxu Yuan, Xiaozhu Jing, Yuzheng Yan, Wuman Luo   +3 more
wiley   +1 more source

DESIGN OF SMART TOURISM SYSTEMS TO FORECAST FOREIGN TOURIST ARRIVAL RATE USING DEEP LEARNING TECHNIQUES [PDF]

Proceedings on Engineering Sciences
India's tourism potential is vast, driven by its rich history, diverse ecology, and extensive natural beauty. The country offers various niche tourism experiences, including cruises, adventure, medical, wellness, sports, MICE, eco-tourism, film, rural ...
Ratna Kanth Gudala , Ravi Kumar Suggala , Venkata Nagaraju Datla , Sri Krishna Adusumalli   +3 more
doaj   +1 more source

Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm

, 2019
Due to their prevalence, time series forecasting is crucial in multiple domains. We seek to make state-of-the-art forecasting fast, accessible, and generalizable. ES-RNN is a hybrid between classical state space forecasting models and modern RNNs that achieved a 9.4% sMAPE improvement in the M4 competition. Crucially, ES-RNN implementation requires per-
Redd, Andrew, Khin, Kaung, Marini, Aldo
openaire   +2 more sources

A Fully Soft Sensing Suit With Optimal Sensor Placement for Real‐Time Motion Tracking

Advanced Intelligent Systems, EarlyView.
A fully soft, skin‐conformable sensing suit integrating stretchable sensors, liquid metal wiring, and soft electrodes was developed using direct ink writing, with sensor placement optimized through an automated algorithmic pipeline. This system enables accurate and unobtrusive real‐time motion tracking, providing a scalable, material‐based solution to ...
Jinhyeok Oh, Joonbum Bae
wiley   +1 more source

Neural network analysis in time series forecasting

Российский технологический журнал
Objectives. To build neural network models of time series (LSTM, GRU, RNN) and compare the results of forecasting with their mutual help and the results of standard models (ARIMA, ETS), in order to ascertain in which cases a certain group of models ...
B. Pashshoev, D. A. Petrusevich
doaj   +1 more source