Recent advances in neuro-fuzzy system: A survey
KV Shihabudheen, GN Pillai - Knowledge-Based Systems, 2018 - Elsevier
Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
Recent advances and effectiveness of machine learning models for fluid dynamics in the built environment
Indoor environmental quality is crucial for human health and comfort, necessitating precise
and efficient computational methods to optimise indoor climate parameters. Recent …
and efficient computational methods to optimise indoor climate parameters. Recent …
[PDF][PDF] Interval type-2 fuzzy sets and systems: Overview and outlook
WU Dongrui, Z Zhi-Gang, MO Hong, W Fei-Yue - ACTA Autom. Sin, 2020 - aas.net.cn
Type-1 fuzzy sets can model the linguistic uncertainty from a single user, ie, intra-personal
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …
Optimization study of heating performance for an impinging jet ventilation system based on data-driven model coupled with TOPSIS method
X Ye, H Qi, Y Kang, K Zhong - Building and Environment, 2022 - Elsevier
Impinging jet ventilation (IJV) is believed to create good indoor thermal comfort and air
quality (IAQ) in an energy efficient way. However, since there is little discussion about the …
quality (IAQ) in an energy efficient way. However, since there is little discussion about the …
Modelling indoor environment indicators using artificial neural network in the stratified environments
Ventilation methods that create stratified environments, eg, stratum ventilation and
displacement ventilation, can achieve a satisfactory indoor environment and energy saving …
displacement ventilation, can achieve a satisfactory indoor environment and energy saving …
Analysis and design of functionally weighted single-input-rule-modules connected fuzzy inference systems
C Li, J Gao, J Yi, G Zhang - IEEE Transactions on Fuzzy …, 2016 - ieeexplore.ieee.org
The single-input-rule-modules (SIRMs) connected fuzzy inference method can efficiently
solve the fuzzy rule explosion phenomenon, which usually occurs in the multivariable …
solve the fuzzy rule explosion phenomenon, which usually occurs in the multivariable …
On modeling of data-driven monotone zero-order TSK fuzzy inference systems using a system identification framework
A system identification-based framework is used to develop monotone fuzzy If-Then rules for
formulating monotone zero-order Takagi-Sugeno-Kang (TSK) fuzzy inference systems (FISs) …
formulating monotone zero-order Takagi-Sugeno-Kang (TSK) fuzzy inference systems (FISs) …
On the monotonicity of interval type-2 fuzzy logic systems
C Li, J Yi, G Zhang - IEEE Transactions on Fuzzy systems, 2013 - ieeexplore.ieee.org
Qualitative knowledge is very useful for system modeling and control problems, especially
when specific physical structure knowledge is unavailable and the number of training data …
when specific physical structure knowledge is unavailable and the number of training data …
Monotonic classification extreme learning machine
H Zhu, ECC Tsang, XZ Wang, RAR Ashfaq - Neurocomputing, 2017 - Elsevier
Monotonic classification problems mean that both feature values and class labels are
ordered and monotonicity relationships exist between some features and the decision label …
ordered and monotonicity relationships exist between some features and the decision label …
区间二型模糊集和模糊系统: 综述与展望
伍冬睿， 曾志刚， 莫红， 王飞跃 - 自动化学报, 2020 - aas.net.cn
一型模糊集可以建模单个用户的语义概念中的不确定性, 即个体内不确定性.
一型模糊系统在控制和机器学习中得到了大量成功应用. 区间二型模糊集能同时建模个体内不 …
一型模糊系统在控制和机器学习中得到了大量成功应用. 区间二型模糊集能同时建模个体内不 …