Underwater object detection: architectures and algorithms–a comprehensive review
S Fayaz, SA Parah, GJ Qureshi - Multimedia Tools and Applications, 2022 - Springer
Underwater object detection is an essential step in image processing and it plays a vital role
in several applications such as the repair and maintenance of sub-aquatic structures and …
in several applications such as the repair and maintenance of sub-aquatic structures and …
[HTML][HTML] Autonomous learning for fuzzy systems: a review
As one of the three pillars in computational intelligence, fuzzy systems are a powerful
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy …
Fuzzy broad learning system: A novel neuro-fuzzy model for regression and classification
A novel neuro-fuzzy model named fuzzy broad learning system (BLS) is proposed by
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …
merging the Takagi-Sugeno (TS) fuzzy system into BLS. The fuzzy BLS replaces the feature …
Evolving fuzzy and neuro-fuzzy approaches in clustering, regression, identification, and classification: A survey
Major assumptions in computational intelligence and machine learning consist of the
availability of a historical dataset for model development, and that the resulting model will, to …
availability of a historical dataset for model development, and that the resulting model will, to …
Command-filter-based adaptive fuzzy finite-time control for switched nonlinear systems using state-dependent switching method
The adaptive fuzzy finite-time tracking control problem of a class of switched nonlinear
systems is investigated in this study. Fuzzy logic systems are introduced to handle the …
systems is investigated in this study. Fuzzy logic systems are introduced to handle the …
Maximum likelihood least squares based iterative estimation for a class of bilinear systems using the data filtering technique
M Li, X Liu - International Journal of Control, Automation and …, 2020 - Springer
Maximum likelihood methods are based on the probability and statistics theory, and
significant for parameter estimation and system modeling. This paper combines the …
significant for parameter estimation and system modeling. This paper combines the …
Two-stage gradient-based iterative estimation methods for controlled autoregressive systems using the measurement data
F Ding, L Lv, J Pan, X Wan, XB Jin - International Journal of Control …, 2020 - Springer
This paper considers the parameter identification problems of controlled autoregressive
systems using observation information. According to the hierarchical identification principle …
systems using observation information. According to the hierarchical identification principle …
Risk evaluation in failure modes and effects analysis: hybrid TOPSIS and ELECTRE I solutions with Pythagorean fuzzy information
M Akram, A Luqman, JCR Alcantud - Neural Computing and Applications, 2021 - Springer
This article proposes two novel modified techniques, namely Pythagorean fuzzy hybrid
Order of Preference by Similarity to an Ideal Solution (PFH-TOPSIS) method and …
Order of Preference by Similarity to an Ideal Solution (PFH-TOPSIS) method and …
Deep sequence to sequence Bi-LSTM neural networks for day-ahead peak load forecasting
N Mughees, SA Mohsin, A Mughees… - Expert Systems with …, 2021 - Elsevier
The power industry is currently facing the problem of an electricity supply–demand
imbalance. The most inexpensive and efficient solution to alleviate this imbalance is to …
imbalance. The most inexpensive and efficient solution to alleviate this imbalance is to …
A type-3 logic fuzzy system: Optimized by a correntropy based Kalman filter with adaptive fuzzy kernel size
In this study, a self-organizing interval type-3 fuzzy logic system (SO-IT3FLS) with a new
learning algorithm is presented. An adaptive kernel size using fuzzy systems is introduced to …
learning algorithm is presented. An adaptive kernel size using fuzzy systems is introduced to …