Articles with "fuzzy modeling" as a keyword



Photo from archive.org

Neuro-fuzzy modeling of deformation parameters for fusion-barriers

Sign Up to like & get
recommendations!
Published in 2020 at "Nuclear Engineering and Technology"

DOI: 10.1016/j.net.2020.10.017

Abstract: Abstract The fusion-barrier distribution is very sensitive to the structure of the colliding nuclei such as nuclear quadrupole and hexadecapole deformation parameters and their signs. If the nuclei that enter the fusion reaction are deformed,… read more here.

Keywords: neuro fuzzy; deformation; deformation parameters; fuzzy modeling ... See more keywords
Photo by nci from unsplash

A New Fuzzy Modeling Framework for Integrated Risk Prognosis and Therapy of Bladder Cancer Patients

Sign Up to like & get
recommendations!
Published in 2018 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2017.2735939

Abstract: This paper presents a new fuzzy modeling approach for analyzing censored survival data and finding risk groups of patients diagnosed with bladder cancer. The proposed framework involves a new procedure for integrating the frameworks of… read more here.

Keywords: bladder cancer; risk; framework; modeling framework ... See more keywords

A Dirichlet Process Based Type-1 and Type-2 Fuzzy Modeling for Systematic Confidence Bands Prediction

Sign Up to like & get
recommendations!
Published in 2019 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2019.2892347

Abstract: This paper presents a new methodology for fuzzy logic systems modeling based on the Dirichlet process Gaussian mixture models (DPGMM). The proposed method simultaneously allows for the systematic elicitation of confidence bands as well as… read more here.

Keywords: confidence bands; systematic confidence; dirichlet process; confidence ... See more keywords

A New Rule Reduction Method for Fuzzy Modeling

Sign Up to like & get
recommendations!
Published in 2020 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2019.2947225

Abstract: The Takagi–Sugeno fuzzy model (T–S fuzzy model) has been successfully applied to a wide range of problems due to its accurate modeling ability. However, its rule redundancy and dimension disaster remain an open and unsolved… read more here.

Keywords: method; model; rule; fuzzy modeling ... See more keywords

Passivity-Based Adaptive Fuzzy Control for Stochastic Nonlinear Switched Systems via T–S Fuzzy Modeling

Sign Up to like & get
recommendations!
Published in 2023 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2022.3195645

Abstract: In this note, state-estimator-based adaptive control is under consideration for a sort of nonlinear stochastic switched systems by Takagi–Sugeno (T–S) fuzzy modeling and sliding mode technique. A new fuzzy sliding surface is established by a… read more here.

Keywords: switched systems; fuzzy modeling; passivity; control ... See more keywords

Canonical Fuzzy Modeling of Disease State

Sign Up to like & get
recommendations!
Published in 2024 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2024.3372905

Abstract: We propose a new theoretical framework for quantification and sensitization of a disease state (DS). This is in contrast to the traditional discrete description of the disease, where the inherent characteristic of its progression is… read more here.

Keywords: disease; fuzzy modeling; canonical fuzzy; disease state ... See more keywords

Context-Aware Audio-Visual Speech Enhancement Based on Neuro-Fuzzy Modeling and User Preference Learning

Sign Up to like & get
recommendations!
Published in 2024 at "IEEE Transactions on Fuzzy Systems"

DOI: 10.1109/tfuzz.2024.3435050

Abstract: It is estimated that by 2050 approximately one in ten individuals globally will experience disabling hearing impairment. In the presence of everyday reverberant noise, a substantial proportion of individual users encounter challenges in speech comprehension.… read more here.

Keywords: neuro fuzzy; preference learning; preference; fuzzy modeling ... See more keywords

Data-Driven Fuzzy Modeling Using Restricted Boltzmann Machines and Probability Theory

Sign Up to like & get
recommendations!
Published in 2020 at "IEEE Transactions on Systems, Man, and Cybernetics: Systems"

DOI: 10.1109/tsmc.2018.2812156

Abstract: Fuzzy modeling has many advantages over nonfuzzy methods, such as robustness with respect to uncertainties and less sensitivity to the varying dynamics of nonlinear systems. Data-driven fuzzy modeling needs to extract fuzzy rules from input… read more here.

Keywords: probability theory; probability; fuzzy modeling; data driven ... See more keywords
Photo from wikipedia

Screening for Combination Cancer Therapies With Dynamic Fuzzy Modeling and Multi-Objective Optimization

Sign Up to like & get
recommendations!
Published in 2021 at "Frontiers in Genetics"

DOI: 10.3389/fgene.2021.617935

Abstract: Combination therapies proved to be a valuable strategy in the fight against cancer, thanks to their increased efficacy in inducing tumor cell death and in reducing tumor growth, metastatic potential, and the risk of developing… read more here.

Keywords: combination; modeling multi; multi objective; cancer ... See more keywords

Three-Dimensional Fuzzy Modeling for Nonlinear Distributed Parameter Systems Using Simultaneous Perturbation Stochastic Approximation

Sign Up to like & get
recommendations!
Published in 2024 at "Applied Sciences"

DOI: 10.3390/app14177860

Abstract: Many systems in the manufacturing industry have spatial distribution characteristics, which correlate with both time and space. Such systems are known as distributed parameter systems (DPSs). Due to the spatiotemporal coupling characteristics, the modeling of… read more here.

Keywords: parameter systems; fuzzy modeling; dimensional fuzzy; three dimensional ... See more keywords

A Spatiotemporal Fuzzy Modeling Approach Combining Automatic Clustering and Hierarchical Extreme Learning Machines for Distributed Parameter Systems

Sign Up to like & get
recommendations!
Published in 2025 at "Mathematics"

DOI: 10.3390/math13030364

Abstract: Modeling distributed parameter systems (DPSs) is challenging due to their strong nonlinearity and spatiotemporal coupling. In this study, a three-dimensional fuzzy modeling method combining genetic algorithm (GA)-based automatic clustering and hierarchical extreme learning machine (HELM)… read more here.

Keywords: parameter systems; clustering hierarchical; fuzzy modeling; automatic clustering ... See more keywords