Results 11 to 20 of about 70 (64)

Emulating Present and Future Simulations of Melt Rates at the Base of Antarctic Ice Shelves With Neural Networks

Journal of Advances in Modeling Earth Systems, Volume 15, Issue 12, December 2023., 2023
Abstract Melt rates at the base of Antarctic ice shelves are needed to drive projections of the Antarctic ice sheet mass loss. Current basal melt parameterizations struggle to link open ocean properties to ice‐shelf basal melt rates for the range of current sub‐shelf cavity geometries around Antarctica.
C. Burgard, N. C. Jourdain, P. Mathiot, R. S. Smith, R. Schäfer, J. Caillet, T. S. Finn, J. E. Johnson   +7 more
wiley   +1 more source

Comparative evaluation of bioethanol fermentation process parameters using RSM, ANN and ANFIS

Biofuels, Bioproducts and Biorefining, Volume 17, Issue 4, Page 961-975, July/August 2023., 2023
Abstract The drive for renewable energy as an alternative to fossil fuel is on the increase globally. Modeling a renewable energy process is crucial for increasing process monitoring and control of plant efficiency for the ultimate objective of optimal biorefinery operations.
Abiola E. Taiwo, Paul Musonge
wiley   +1 more source

Salt‐and‐pepper denoising method for colour images based on tensor low‐rank prior and implicit regularization

IET Image Processing, Volume 17, Issue 3, Page 886-900, 28 February 2023., 2023
1) In our article, color images are no longer three independent matrixes, but a tensor with a low‐rank structure. Under this assumption, the noise‐contaminated color image is regarded as the sum of a tensor with missing data and a salt and pepper noise tensor.
Jun Zhang, Zhao‐yang Li, Ling‐zhi Wang, Ying‐pin Chen   +3 more
wiley   +1 more source

Hybrid Time‐Series Prediction Method Based on Entropy Fusion Feature

International Journal of Intelligent Systems, Volume 2023, Issue 1, 2023., 2023
High‐precision time sequence forecasting is a complicated cyber‐physical system (CPS) task. Due to the diversity of data scales and types, the classic time‐series prediction model meets the challenge to deliver accurate prediction results for many forms of time‐series data.
Jing Zhang, Yang Yang, Yong Feng, Alexander Hošovský   +3 more
wiley   +1 more source

T‐Spherical 2‐Tuple Linguistic Aggregation Operators and Their Applications in the Decision‐Making Strategy

Mathematical Problems in Engineering, Volume 2023, Issue 1, 2023., 2023
The decision‐making technique is very important and valuable and is used for evaluating the best decision from the collection of preferences. In this manuscript, we elaborated the novel concept of the T‐spherical 2‐tuple linguistic (TS2‐TL) set and its operational laws in the consideration of t‐norm and t‐conorm.
Tahir Mahmood, Zeeshan Ali, Amrullah Awsar, Ardashir Mohammadzadeh   +3 more
wiley   +1 more source

MSPCIFormer: A Multi‐Scale Patching Channel‐Independent Transformer for Cryptocurrency Price Forecasting

Expert Systems, Volume 43, Issue 9, September 2026.
ABSTRACT Forecasting cryptocurrency prices remains challenging due to extreme volatility, regime‐dependent dynamics, and unstable cross‐asset correlations. Statistical methods such as ARIMA and GARCH assume stationarity and linear dependence structures, making them inadequate for capturing non‐linear temporal patterns in high volatile cryptocurrency ...
Huali Zhao, Martin Crane, Marija Bezbradica   +2 more
wiley   +1 more source

Integration of Colorimetric Sensing Dyes and Multi‐Substrate Arrays for Food Quality and Safety Monitoring: Design, Optimization, and Analysis

Comprehensive Reviews in Food Science and Food Safety, Volume 25, Issue 1, January 2026.
ABSTRACT As food safety issues gain increasing attention, the need for rapid, accurate, and low‐cost detection techniques becomes essential. Colorimetric sensors, known for their rapid response, high sensitivity, low cost, and readily observable results, are playing an increasingly important role in food quality inspection. This review article provides
Jingfei Shen, Qisheng Liu, Ruxin Zhang, Zhengzhu Zhang, Quansheng Chen, Jingming Ning, Luqing Li   +6 more
wiley   +1 more source

Proximity to Natural Habitat Is Not Consistently Associated With Pollination Services in Tropical Smallholder Farms: A Systematic Review and Meta‐Analysis

Ecology Letters, Volume 28, Issue 12, December 2025.
We conducted a systematic review and meta‐analysis of 35 studies to examine the relationship between distance to natural habitat and pollinator abundance, species richness and crop fruit set in tropical smallholder farms. We found no consistent effects on abundance or fruit set, and only a slight, highly variable negative effect on pollinator richness,
Ennia Bosshard, Mark E. Harrison, Frank van Veen, Chris J. Kettle, Nagaraja Badenahally Chikkarangappa, John E. Banks, Parthiba Basu, Quebin Bosbely Casiá‐Ajché, Bo Dalsgaard, Aditi Dutta, Eunice Enríquez, Natalia Escobedo‐Kenefic, Hugo Eduardo Fierros‐López, Barbara Gemmill‐Herren, Jaboury Ghazoul, Katrine Hansen, Annika L. Hass, Juliana Hipólito, Oliver Honnay, John Muo Kasina, Alexandra‐Maria Klein, Iris Kormann Motzke, Smitha Krishnan, Patricia Landaverde, Anderson Oliveira Latini, Kevin Li, Rodrigo Lucas‐García, Theodore Munyuli, Deepthi Narasimhaiah, Diana Obregon, J. Javier G. Quezada‐Euán, Mónica E. Riojas‐López, Victor Rosas‐Guerrero, Julian Schrader, Fernando Severiano‐Galeana, Tegegne Molla Sitotaw, Tuanjit Sritongchuay, Pornpimon Tangtorwangsakul, Manuel Toledo‐Hernandez, Teja Tscharntke, Poornima Viswanathan, Cassandra Vogel, Thomas C. Wanger, Kanuengnit Wayo, Catrin Westphal, Matt Lloyd Jones, Christopher N. Kaiser‐Bunbury   +46 more
wiley   +1 more source

Efficient learning of uncertainty distributions in coupled multidisciplinary systems through sensory data

IET Cyber-Physical Systems: Theory &Applications, Volume 10, Issue 1, January/December 2025.
Coupled multidisciplinary systems are crucial in fields like aerospace and robotics, where accurate analysis depends on effectively estimating uncertainties. This paper introduces a framework using a non‐linear/non‐Gaussian hidden Markov model (HMM) to capture the stochastic nature of these systems, employing particle filtering and Bayesian ...
Negar Asadi, Seyede Fatemeh Ghoreishi
wiley   +1 more source

Integrated, Artificial‐Intelligence‐Based Power Management for Building Electrical Microgrids

IET Energy Systems Integration, Volume 7, Issue 1, January/December 2025.
ABSTRACT As global energy demand continues to rise alongside the push for green technologies, artificial intelligence (AI) based power management systems play a pivotal role in achieving energy efficiency, grid stability and carbon footprint reduction, making them a vital component of future‐ready building infrastructures.
Eleftherios G. Kyriakou, Dimitra G. Kyriakou, Fotios D. Kanellos, Dimitris Ipsakis   +3 more
wiley   +1 more source