Accelerating materials discovery using machine learning
Y Juan, Y Dai, Y Yang, J Zhang - Journal of Materials Science & …, 2021 - Elsevier
The discovery of new materials is one of the driving forces to promote the development of
modern society and technology innovation, the traditional materials research mainly …
modern society and technology innovation, the traditional materials research mainly …
Rebooting data-driven soft-sensors in process industries: A review of kernel methods
Soft-sensors usually assist in dealing with the unavailability of hardware sensors in process
industries, thus allowing for less fault occurrence and better control performance. However …
industries, thus allowing for less fault occurrence and better control performance. However …
Modeling the SOFC by BP neural network algorithm
S Song, X **ong, X Wu, Z Xue - International Journal of Hydrogen Energy, 2021 - Elsevier
Solid oxide fuel cells (SOFCs) are complex systems in which electrochemistry,
thermophysics and ion conduction occur simultaneously. The coupling of the multi-physics …
thermophysics and ion conduction occur simultaneously. The coupling of the multi-physics …
Assessing credit risk of commercial customers using hybrid machine learning algorithms
Given the large amount of customer data available to financial companies, the use of
traditional statistical approaches (eg, regressions) to predict customers' credit scores may …
traditional statistical approaches (eg, regressions) to predict customers' credit scores may …
A decision-theoretic rough set model with q-rung orthopair fuzzy information and its application in stock investment evaluation
Stock investment is characterized by high risk and massive profit, so it is necessary to
propose a scientific and accurate stock assessment and selection method for avoiding …
propose a scientific and accurate stock assessment and selection method for avoiding …
Forecasting agricultural commodity prices using model selection framework with time series features and forecast horizons
D Zhang, S Chen, L Liwen, Q **a - IEEE access, 2020 - ieeexplore.ieee.org
The fluctuations of agricultural commodity prices have a great impact on people's daily lives
as well as the inputs and outputs of agricultural production. An accurate forecast of …
as well as the inputs and outputs of agricultural production. An accurate forecast of …
Machine learning‐based model for lithium‐ion batteries in BMS of electric/hybrid electric aircraft
SR Hashemi… - … Journal of Energy …, 2021 - Wiley Online Library
Reliable operation and control of battery packs can lead to increasing applications of
batteries as energy sources for mobile power systems such as electric/hybrid electric aircraft …
batteries as energy sources for mobile power systems such as electric/hybrid electric aircraft …
Two-dimensional improved attribute reductions based on distance granulation and condition entropy in incomplete interval-valued decision systems
B Chen, X Zhang, Z Yuan - Information Sciences, 2024 - Elsevier
Attribute reductions rely on knowledge granulation and information measurement. Aiming at
incomplete interval-valued decision systems (IIVDSs), an attribute reduction (with the FSR …
incomplete interval-valued decision systems (IIVDSs), an attribute reduction (with the FSR …
Fuzzy probability theory
M Beer - Granular, Fuzzy, and Soft Computing, 2023 - Springer
Fuzzy probability theory is an extension to probability theory to dealing with a mix of
probabilistic uncertainty and non-probabilistic imprecision. It provides a theoretical basis to …
probabilistic uncertainty and non-probabilistic imprecision. It provides a theoretical basis to …
Machine-learning approaches for the discovery of electrolyte materials for solid-state lithium batteries
S Hu, C Huang - Batteries, 2023 - mdpi.com
Solid-state lithium batteries have attracted considerable research attention for their potential
advantages over conventional liquid electrolyte lithium batteries. The discovery of lithium …
advantages over conventional liquid electrolyte lithium batteries. The discovery of lithium …