Results 91 to 100 of about 31,169 (266)
DESIGN OF SMART TOURISM SYSTEMS TO FORECAST FOREIGN TOURIST ARRIVAL RATE USING DEEP LEARNING TECHNIQUES [PDF]
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 +3 more
doaj +1 more source
Real‐Time Biomass Estimation in High‐Density Yeast Fermentations Using Soft Sensor Modeling
Accurate biomass measurements, both offline and online, are essential to improve prediction and control in yeast fermentation. This study develops regression‐based predictive models to correlate offline measurements (Dry Cell Weight and OD600 from a spectrophotometer) with online OD860 probe signals to provide accurate real‐time biomass estimations and
Ana G. Del Hierro +3 more
wiley +1 more source
Digital Technology's Role in Circular Waste Management: A Systematic Review
ABSTRACT Combining circular economy ideas with digital tools offers a game‐changing way to tackle global sustainability problems. This paper focuses on how digital changes and circular economy models link up. A review has been conducted for 112 articles from 2021 to September 2025, using PRISMA‐2020 methodology. This study covered new tech like AI, IoT,
Reza Eslamipoor
wiley +1 more source
This comprehensive review presents a progressive roadmap for perovskite vision detectors. Centered on perovskite‐based artificial perception, the graphic illustrates a systematic evolution: starting with fundamental material engineering and device architectures, advancing toward complex functional strategies such as flexible neuromorphic imaging ...
Chenglong Li +14 more
wiley +1 more source
Neural network analysis in time series forecasting
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
针对目前大部分PM2.5 预测模型预测效果不稳定、泛化能力不强的现状,以记忆能力较强的循环神经网络(RNN) 和特征表达能力较强的卷积神经网络(CNN) 为基础,采取Stacking 集成策略对两者进行融合,提出了RNN-CNN 集成深度学习预测模型。该模型不仅充分利用时间轴上的前后关联信息去预测未来的浓度,而且在不同层次上将自动提取的高维时序数据通用特征用于预测,以保证预测结果的稳定性。最后,对集成之前的 RNN、CNN 和集成之后的RNN-CNN 模型,以2016 年中国大陆地区1 466 ...
HUANGJie(黄婕) +4 more
doaj +1 more source
This work explores generative AI for automated revision of Piping and Instrumentation Diagrams (P&IDs). We frame P&ID correction as a translation problem, converting attributed P&ID graphs into sequences and learning revisions with a transformer‐based model.
Lukas Schulze Balhorn +5 more
wiley +1 more source
GAN‐LSTM‐3D: An efficient method for lung tumour 3D reconstruction enhanced by attention‐based LSTM
Abstract Three‐dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN‐LSTM‐3D method is proposed for 3D reconstruction of lung cancer tumours from 2D CT images. Our method consists of three phases: lung segmentation, tumour segmentation, and tumour 3D reconstruction. Lung
Lu Hong +12 more
wiley +1 more source
Hybrid FSO/RF Networks with Neural Prediction of RSSI and Weather
This paper investigates neural network models for predicting weather parameters and received signal strength indicator (RSSI) to enable adaptive handover in hybrid free space optics (FSO)/radio frequency (RF) systems.
Liščinská Zuzana +2 more
doaj +1 more source
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 +6 more
wiley +1 more source

