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Fuzzy Logic

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A deep learning approach for ovarian cancer detection and classification based on fuzzy deep learning.

Scientific reports
Different oncologists make their own decisions about the detection and classification of the type of ovarian cancer from histopathological whole slide images. However, it is necessary to have an automated system that is more accurate and standardized...

Unsupervised learning for real-time and continuous gait phase detection.

PloS one
Individuals with lower limb impairment after a stroke or spinal cord injury require rehabilitation, but traditional methods can be challenging for both patients and therapists. Robotic systems have been developed to help; however, they currently cann...

The hazard analysis of passenger-cargo ferries: a revised risk matrix model based on fuzzy best-worst method.

Environmental science and pollution research international
Improving hazards in maritime transport is essential to maintain the reliability and sustainability of the industry, ensure safety and security, and support global trade and economic growth. This paper is aimed at analyzing the hazards of passenger-c...

Research on anti-swing control system of slewing crane based on fuzzy PID.

PloS one
BACKGROUND: The slewing crane is easily affected by the wind and the manipulation level of the operator when it is working, which in turn impacts its swing angle, affects the working efficiency and safety of the crane.

A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine.

PloS one
BACKGROUND: In Persian medicine, early diagnosis and treatment of stomach dystemperament is crucial for preventing other diseases. However, traditional medicine diagnosis often involves ambiguous and less structured information making it challenging ...

Research on technology innovation path of Intelligent Manufacturing enterprises-Based on qualitative comparative analysis of fuzzy sets under TOE framework.

PloS one
Intelligent manufacturing enterprises play a crucial role in the modern industrial system and are key to high-quality economic development. However, most current research on intelligent manufacturing technology innovation focuses on single variables,...

Dual-hesitant fermatean fuzzy Hamacher aggregation operators and TOPSIS with their application to multi-criteria decision-making.

PloS one
The concept of the Dual-hesitant fermatean fuzzy set (DHFFS) represents a significant advancement in practical implementation, combining Fermatean fuzzy sets and Dual-hesitant sets. This new structure uses membership and non-membership hesitancy and ...

A novel approach to decision making in rice quality management using interval-valued Pythagorean fuzzy Schweizer and Sklar power aggregation operators.

PloS one
The Pythagorean fuzzy set and interval-valued intuitionistic fuzzy set are the basis of the interval-valued Pythagorean fuzzy set (IVPFS) which offers an effective approach to addressing the complex uncertainty in decision-analysis processes, making ...

The dynamics and behavior of logarithmic type fuzzy difference equation of order two.

PloS one
Fuzzy difference equations are becoming increasingly popular in fields like engineering, ecology, and social science. Difference equations find numerous applications in real-life problems. Our study demonstrates that the logarithmic-type fuzzy differ...

Deep fuzzy physics-informed neural networks for forward and inverse PDE problems.

Neural networks : the official journal of the International Neural Network Society
As a grid-independent approach for solving partial differential equations (PDEs), Physics-Informed Neural Networks (PINNs) have garnered significant attention due to their unique capability to simultaneously learn from both data and the governing phy...