Kiyohiko Uehara

According to our database1, Kiyohiko Uehara authored at least 23 papers between 1993 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2021
A Fast Method for Fuzzy Rules Learning with Derivative-Free Optimization by Formulating Independent Evaluations of Each Fuzzy Rule.
J. Adv. Comput. Intell. Intell. Informatics, 2021

2019
Noise Reduction with Fuzzy Inference Based on Generalized Mean and Singleton Input-Output Rules: Toward Fuzzy Rule Learning in a Unified Inference Platform.
J. Adv. Comput. Intell. Intell. Informatics, 2019

2018
Noise Reduction with Inference Based on Fuzzy Rule Interpolation at an Infinite Number of Activating Points: Toward Fuzzy Rule Learning in a Unified Inference Platform.
J. Adv. Comput. Intell. Intell. Informatics, 2018

2017
Fuzzy Inference Based on α-Cuts and Generalized Mean: Relations Between the Methods in its Family and their Unified Platform.
J. Adv. Comput. Intell. Intell. Informatics, 2017

Multi-Level Control of Fuzzy-Constraint Propagation in Inference with Fuzzy Rule Interpolation at an Infinite Number of Activating Points.
J. Adv. Comput. Intell. Intell. Informatics, 2017

Fuzzy Inference: Its Past and Prospects.
J. Adv. Comput. Intell. Intell. Informatics, 2017

2016
Multi-Level Control of Fuzzy-Constraint Propagation via Evaluations with Linguistic Truth Values in Generalized-Mean-Based Inference.
J. Adv. Comput. Intell. Intell. Informatics, 2016

2015
Inference with Fuzzy Rule Interpolation at an Infinite Number of Activating Points.
J. Adv. Comput. Intell. Intell. Informatics, 2015

2013
Multi-Level Control of Fuzzy-Constraint Propagation in Inference Based on α-Cuts and Generalized Mean.
J. Adv. Comput. Intell. Intell. Informatics, 2013

Multi-Level Interpolation for Inference with Sparse Fuzzy Rules: An Extended Way of Generating Multi-Level Points.
J. Adv. Comput. Intell. Intell. Informatics, 2013

Infinite-Level Interpolation for Inference with Sparse Fuzzy Rules: Fundamental Analysis Toward Practical Use.
J. Adv. Comput. Intell. Intell. Informatics, 2013

2011
Inference for Nonlinear Mapping with Sparse Fuzzy Rules Based on Multi-Level Interpolation.
J. Adv. Comput. Intell. Intell. Informatics, 2011

2010
Inference Based on ά-Cut and Generalized Mean in Representing Fuzzy-Valued Functions.
J. Adv. Comput. Intell. Intell. Informatics, 2010

Suppression Effect of alpha-Cut Based Inference on Consequence Deviations.
J. Adv. Comput. Intell. Intell. Informatics, 2010

Inference Based on alpha-Cut and Generalized Mean with Fuzzy Tautological Rules.
J. Adv. Comput. Intell. Intell. Informatics, 2010

2009
Inference with Governing Schemes for Propagation of Fuzzy Convex Constraints Based on alpha-Cuts.
J. Adv. Comput. Intell. Intell. Informatics, 2009

Fuzzy Inference with Schemes for Guaranteeing Convexity and Symmetricity in Consequences Based on alpha-Cuts.
J. Adv. Comput. Intell. Intell. Informatics, 2009

1998
Parallel and Multistage Fuzzy Inference Based on Families of alpha-level sets.
Inf. Sci., 1998

1997
Fuzzy Connection Admission Control for ATM Networks Based on Possibility Distribution of Cell Loss Ratio.
IEEE J. Sel. Areas Commun., 1997

Fuzzy Inference Based Connection Admission Control in ATM Networks.
J. Adv. Comput. Intell. Intell. Informatics, 1997

Parallel Fuzzy Inference Based on alpha-Level Sets and Generalized Means.
Inf. Sci., 1997

1993
Multistage fuzzy inference formulated as linguistic-truth-value propagation and its learning algorithm based on back-propagating error information.
IEEE Trans. Fuzzy Syst., 1993

Fuzzy inference based on families of α-level sets.
IEEE Trans. Fuzzy Syst., 1993


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