Results 31 to 40 of about 96,386 (319)

Fuzzy Rule Interpolation With $K$-Neighbors for TSK Models

open access: yesIEEE transactions on fuzzy systems, 2022
When a fuzzy system is presented with an incomplete (or sparse) rule base, fuzzy rule interpolation (FRI) offers a useful mechanism to infer conclusions for unmatched observations.
Pu Zhang, C. Shang, Q. Shen
semanticscholar   +1 more source

Hierarchical Bidirectional Fuzzy Rule Interpolation [PDF]

open access: yes2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 2018
The “curse of dimensionality” and “sparse rule base” are two common and important problems in conventional fuzzy systems. Using hierarchical fuzzy systems is an effective way to deal with the “curse of dimensionality” problem, whilst fuzzy rule interpolation offers a useful means for enhancing the robustness of fuzzy models, making inference possible ...
Shangzhu Jin   +3 more
openaire   +1 more source

New correlation features for dissolved gas analysis based transformer fault diagnosis based on the maximal information coefficient

open access: yesHigh Voltage, 2022
Online monitoring of gases dissolved in transformer oil is widely applied. Improving the performance of dissolved gas analysis (DGA)‐based fault diagnosis methods by exploring new features of time‐series data has become an appealing topic. In this study,
Yongliang Liang   +3 more
doaj   +1 more source

An Accurate Detection Approach for IoT Botnet Attacks Using Interpolation Reasoning Method

open access: yesInformation, 2022
Nowadays, the rapid growth of technology delivers many new concepts and notations that aim to increase the efficiency and comfort of human life. One of these techniques is the Internet of Things (IoT). The IoT has been used to achieve efficient operation
Mohammad Almseidin, Mouhammd Alkasassbeh
doaj   +1 more source

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems [PDF]

open access: yes, 2012
This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem
Al-Hadithi, Basil M.   +2 more
core   +2 more sources

Neuro-fuzzy chip to handle complex tasks with analog performance [PDF]

open access: yes, 2003
This Paper presents a mixed-signal neuro-fuzzy controller chip which, in terms of power consumption, input-output delay and precision performs as a fully analog implementation. However, it has much larger complexity than its purely analog counterparts.
Navas González, Rafael   +2 more
core   +5 more sources

A multiplexing architecture for mixed-signal CMOS fuzzy controllers [PDF]

open access: yes, 1998
Limits to precision impose limits to the complexity of analog circuits, hence fuzzy analog controllers are usually oriented to fast low-power systems with low-medium complexity.
A. Rodríguez-Vázquez   +6 more
core   +3 more sources

A multiplexed mixed-signal fuzzy architecture [PDF]

open access: yes, 1998
Analog circuits provide better area/power efficiency than their digital counterparts for low-medium precision requirements. This limit in precision as well as the lack of design tools when compared to the digital approach, imposes a limit of complexity ...
Navas González, Rafael   +2 more
core   +1 more source

A mixed-signal fuzzy controller and its application to soft start of DC motors [PDF]

open access: yes, 2000
Presents a mixed-signal fuzzy controller chip and its application to control of DC motors. The controller is based on a multiplexed architecture presented by the authors (1998), where building blocks are also described.
Navas González, Rafael   +2 more
core   +1 more source

Towards sparse rule base generation for fuzzy rule interpolation [PDF]

open access: yes2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
Fuzzy inference systems have been successfully applied to many real-world applications. Traditional fuzzy inference systems are only applicable to problems with dense rule bases by which the entire input domain is fully covered, whilst fuzzy rule interpolation (FRI) is also able to work with sparse rule bases that may not cover certain observations ...
Yao Tan   +5 more
openaire   +1 more source

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