AIMC Topic: Fuzzy Logic

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Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Physical and engineering sciences in medicine
Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convolutional neural networks (CNNs) hold promise in accurately identifying tumor locations and boundarie...

A fuzzy interval dynamic optimization model for surface and groundwater resources allocation under water shortage conditions, the case of West Azerbaijan Province, Iran.

Environmental science and pollution research international
The allocation of water in areas which face shortage of water especially during hot dry seasons is of utmost importance. This is normally affected by various factors, the management of which takes a lot of time and energy with efforts falling inferti...

A fuzzy interval optimization approach for p-hub median problem under uncertain information.

PloS one
Stochastic and robust optimization approaches often result in sub-optimal solutions for the uncertain p-hub median problem when continuous design parameters are discretized to form different environmental scenarios. To solve this problem, this paper ...

Q-learning and fuzzy logic multi-tier multi-access edge clustering for 5g v2x communication.

Network (Bristol, England)
The 5th generation (5 G) network is required to meet the growing demand for fast data speeds and the expanding number of customers. Apart from offering higher speeds, 5 G will be employed in other industries such as the Internet of Things, broadcast ...

An intelligent interval forecasting system based on fuzzy time series and error distribution characteristics for air quality index.

Environmental research
Due to the emergency environment pollution problems, it is imperative to understand the air quality and take effective measures for environmental governance. As a representative measure, the air quality index (AQI) is a single conceptual index value ...

Intrinsic growth rate and evolution of the Premnotrypes Vorax population using fuzzy information.

Bio Systems
The white potato worm (Premnotrypes Vorax (Hustache)) is one of the pests that causes the greatest damage to the potato crop and the greatest economic losses to the grower; therefore, knowing its life cycle and estimating its intrinsic growth rate is...

Machine learning methods for the modelling and optimisation of biogas production from anaerobic digestion: a review.

Environmental science and pollution research international
Biogas plant operators often face huge challenges in the monitoring, controlling and optimisation of the anaerobic digestion (AD) process, as it is very sensitive to surrounding changes, which often leads to process failure and adversely affects biog...

Comprehensive evaluation of green mine construction level considering fuzzy factors using intuitionistic fuzzy TOPSIS with kernel distance.

Environmental science and pollution research international
With increasing concerns about climate change and resource-environmental limitations, the green development of the mining industry has become mainstream and gained much support. Driven by the concept of sustainable and green development, China has ma...

An Optimized Stimulation Control System for Upper Limb Exoskeleton Robot-Assisted Rehabilitation Using a Fuzzy Logic-Based Pain Detection Approach.

Sensors (Basel, Switzerland)
The utilization of robotic systems in upper limb rehabilitation has shown promising results in aiding individuals with motor impairments. This research introduces an innovative approach to enhance the efficiency and adaptability of upper limb exoskel...

Robust face recognition using quaternion interval type II fuzzy logic-based feature extraction on colour images.

Medical & biological engineering & computing
In this paper, we propose a new robust and fast learning technique by investigating the effect of integration of quaternion and interval type II fuzzy logic along with non-iterative, parameter free deterministic learning machine (DLM) pertaining to f...