Results 131 to 140 of about 1,115,378 (357)
Learning Invariants using Decision Trees
, 2015 15 pages, 2 ...
Krishna, Siddharth +2 more
openaire +2 more sources
Hierarchically MOF‐Based Porous Monolith Composites for Atmospheric Water Harvesting
Advanced Materials, EarlyView.This review explores the design of hierarchical porous materials for atmospheric water harvesting, focusing on metal‐organic frameworks (MOFs) and porous monoliths. Emphasis is placed on integrating MOF nanoscale porosity with the microscale channels of monolithic scaffolds to enhance sorption‐desorption performance.
Mahyar Panahi‐Sarmad +7 more
wiley +1 more source
State‐of‐the‐Art, Insights, and Perspectives for MOFs‐Nanocomposites and MOF‐Derived (Nano)Materials
Advanced Materials, EarlyView.Different approaches to MOF‐NP composite formation, such as ship‐in‐a‐bottle, bottle‐around‐the‐ship and in situ one‐step synthesis, are used. Owing to synergistic effects, the advantageous features of the components of the composites are beneficially combined, and their individual drawbacks are mitigated.
Stefanos Mourdikoudis +6 more
wiley +1 more source
Scientific Reports, 2017 Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival.
Kyung Don Yoo +8 more
doaj +1 more source
Multiple thresholds and trajectories of microbial biodiversity predicted across browning gradients by neural networks and decision tree learning. [PDF]
ISME Commun, 2021 Fontaine L +6 more
europepmc +1 more source
Possibilistic Induction in Decision-Tree Learning [PDF]
, 2002 We propose a generalization of Ockham's razor, a widely applied principle of inductive inference. This generalization intends to capture the aspect of uncertainty involved in inductive reasoning. To this end, Ockham's razor is formalized within the framework of possibility theory: It is not simply used for identifying a single, apparently optimal model,
openaire +2 more sources
Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning [PDF]
, 2014 A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and
Kurbatsky, Victor +5 more
core +2 more sources
Machine‐Learning‐Aided Advanced Electrochemical Biosensors
Advanced Materials, EarlyView.Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan +9 more
wiley +1 more source
Learning kμ decision trees on the uniform distribution [PDF]
, 1993 Thomas R. Hancock
openalex +1 more source
Advanced Materials, EarlyView.Reversible protonic ceramic electrochemical cells (R‐PCECs) face challenges from sluggish and unstable oxygen reduction and evolution reactions in the air electrode. This review discusses recent progress in triple‐conducting air electrodes, emphasizing mechanisms, performance factors, and design strategies, offering guidance for creating efficient and ...
Xi Chen +8 more
wiley +1 more source