Fuzzy information processing 2023 / Kelly Cohen, Nicholas Ernest, Barnabas Bede, Vladik Kreinovich, editors.
Cohen, Kelly, editor.; Ernest, Nicholas, editor.; Bede, Barnabas, editor.; Kreinovich, Vladik, editor.; North American Fuzzy Information Processing Society. Annual Meeting (2023 : Cincinnati, Ohio); Workshop on Constraint Programming and Decision Making (2023 : Cincinnati, Ohio) ; jointly held conference.
2023
QA248 .N67 2023eb
Available Online

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks

Details

Title
Fuzzy information processing 2023 / Kelly Cohen, Nicholas Ernest, Barnabas Bede, Vladik Kreinovich, editors.
ISBN
9783031467783 (electronic bk.)
3031467787 (electronic bk.)
9783031467776
3031467779
DOI
https://doi.org/10.1007/978-3-031-46778-3
Published
Cham : Springer, 2023.
Language
English
Description
1 online resource (x, 358 pages) : illustrations (some color).
Item Number
10.1007/978-3-031-46778-3 doi
Call Number
QA248 .N67 2023eb
Dewey Decimal Classification
006.3/3
Summary
This book is an overview of latest successes and applications of fuzzy techniques -- techniques that use expert knowledge formulated by natural-language words like "small". Engineering applications deal with aerospace (control of spacecrafts and unmanned aerial vehicles, air traffic control, airport passenger flow predictions), materials (designing gold nano-structures for medicine, catalysis, and sensors), and robot navigation and manipulation. Other application areas include cosmology, demographics, finances, wine production, medicine (diagnostics, epidemics control), and predicting human behavior. In many cases, fuzzy techniques are combined with machine learning AI. Due to natural-language origin of fuzzy techniques, such combination adds explainability (X) to AI. This book is recommended to students and practitioners interested in the state-of-the-art fuzzy-related XAI and to researchers willing to take on numerous remaining challenges.
Note
Includes author index.
Bibliography, etc. Note
References -- Genetic Fuzzy Threat Assessment for Asteroids 2600 Derived Game -- 1 Introduction -- 2 Methodology -- 2.1 Fuzzy Targeting -- 2.2 Aiming -- 2.3 Genetic Algorithm -- 3 Results -- 4 Discussion -- 5 Conclusion -- References -- Calibration Error Estimation Using Fuzzy Binning -- 1 Introduction -- 2 Background -- 2.1 Neural Network Calibration -- 2.2 Expected Calibration Error -- 3 Fuzzy Calibration Error -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Developing System Requirements for Trustworthy AI Enabled Refueling Spacecraft
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed December 4, 2023).
Added Author
Cohen, Kelly, editor.
Ernest, Nicholas, editor.
Bede, Barnabas, editor.
Kreinovich, Vladik, editor.
Added Corporate Author
North American Fuzzy Information Processing Society. Annual Meeting (2023 : Cincinnati, Ohio)
Added Meeting Name
Workshop on Constraint Programming and Decision Making (2023 : Cincinnati, Ohio) ; jointly held conference.
Series
Lecture notes in networks and systems ; v. 751. 2367-3389
Available in Other Form
Fuzzy Information Processing 2023
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
Forcing the Network to use Human Explanations in its Inference Process
Fuzzy Inference System-based Collision Avoidance of Unmanned Aerial Vehicles Optimized using Genetic Algorithm
Fuzzy Logic-aided Inverse Kinematics Control for Redundant Manipulators
Growth Kinetics of Gold Nanoparticles via p-fuzzy systems
Optimization of Artificial Potential Field using Genetic Algorithm for Human-aware Navigation of Autonomous Mobile Robots
Genetic Fuzzy Threat Assessment for Asteroids 2600 Derived Game
Deep Learning ANFIS Architectures
A Fuzzy Inference System for an Optimal Spacecraft Attitude State Trajectory
Faster Algorithms for Estimating the Mean of a Quadratic Expression under Uncertainty
People Prefer More Information About Uncertainty, But Perform Worse When Given This Information: An Explanation of the Paradoxical Phenomenon.

Browse Subjects

Show more subjects...

Statistics

from
to
Export