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Fuzzy Logic

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ReLU-FCM trained by quasi-oppositional bare bone imperialist competition algorithm for predicting employment rate.

PloS one
Fuzzy cognitive maps (FCMs) are a powerful tool for system modeling, which can be used for static and dynamic analysis. However, traditional FCMs are usually learned by gradient-based methods, and the adopted sigmoid nonlinear activation function fre...

Deep learning fuzzy immersion and invariance control for type-I diabetes.

Computers in biology and medicine
In this study, a novel approach is proposed for glucose regulation in type-I diabetes patients. Unlike most studies, the glucose-insulin metabolism is considered to be uncertain. A new approach on the basis of the Immersion and Invariance (I&I) theor...

A Fast Weighted Fuzzy C-Medoids Clustering for Time Series Data Based on P-Splines.

Sensors (Basel, Switzerland)
The rapid growth of digital information has produced massive amounts of time series data on rich features and most time series data are noisy and contain some outlier samples, which leads to a decline in the clustering effect. To efficiently discover...

Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models.

Sensors (Basel, Switzerland)
To improve the monitoring of the electrical power grid, it is necessary to evaluate the influence of contamination in relation to leakage current and its progression to a disruptive discharge. In this paper, insulators were tested in a saline chamber...

Multi-Kernel Fuzzy Clustering-Based Sporting Consumption Behavior Study.

Computational intelligence and neuroscience
Cluster analysis plays a very important role in the field of unsupervised learning. The multikernel function is used to transform the low-dimensional nonlinear relationship of the influencing factors of consumption behavior into a high-dimensional li...

Risk assessment of interstate pipelines using a fuzzy-clustering approach.

Scientific reports
Interstate pipelines are the most efficient and feasible mean of transport for crude oil and gas within boarders. Assessing the risks of these pipelines is challenging despite the evolution of computational fuzzy inference systems (FIS). The computat...

Distance and similarity measures for normal wiggly dual hesitant fuzzy sets and their application in medical diagnosis.

Scientific reports
The normal wiggly dual hesitant fuzzy set (NWDHFS) is a modern mathematical tool that can be used to express the deep ideas of membership and non-membership information hidden in the thought-level of decision-makers (DMs). To enhance and expand the a...

A reservoir bubble point pressure prediction model using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique with trend analysis.

PloS one
The bubble point pressure (Pb) could be obtained from pressure-volume-temperature (PVT) measurements; nonetheless, these measurements have drawbacks such as time, cost, and difficulties associated with conducting experiments at high-pressure-high-tem...

Coordinated Control of Intelligent Fuzzy Traffic Signal Based on Edge Computing Distribution.

Sensors (Basel, Switzerland)
With the development of Internet of Things infrastructures and intelligent traffic systems, the traffic congestion that results from the continuous complexity of urban road networks and traffic saturation has a new solution. In this research, we prop...

Hesitant 2-tuple fuzzy linguistic multi-criteria decision-making method based on correlation measures.

PloS one
Correlation is considered the most important factor in analyzing the data in statistics. It is used to measure the movement of two different variables linearly. The concept of correlation is well-known and used in different fields to measure the asso...