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Found 24 papers, 3 papers with code
Gradient-based Fuzzy System Optimisation via Automatic Differentiation -- FuzzyR as a Use Case
Since their introduction, fuzzy sets and systems have become an important area of research known for its versatility in modelling, knowledge representation and reasoning, and increasingly its potential within the context explainable AI.
The Energy Prediction Smart-Meter Dataset: Analysis of Previous Competitions and Beyond
These competitions focus on accurate energy consumption forecasting and the importance of interpretability in understanding the underlying factors.
The Joint Weighted Average (JWA) Operator
Information aggregation is a vital tool for human and machine decision making, especially in the presence of noise and uncertainty.
Quantification of Robotic Surgeries with Vision-Based Deep Learning
We believe this is a prerequisite for the provision of surgical feedback and modulation of surgeon performance in pursuit of improved patient outcomes.
Image Augmentation Using a Task Guided Generative Adversarial Network for Age Estimation on Brain MRI
The proposed method was evaluated on a public brain MRI data set for age estimation.
Towards Handling Uncertainty-at-Source in AI -- A Review and Next Steps for Interval Regression
Increasingly, however, research is focusing upon uncertainty arising at the level of individual measurements (i. e., within- or intra-source), such as for a given sensor output or human response.
Vortical flow structures induced by red blood cells in capillaries
We conduct an experimental study on the flow field around red blood cells in capillary flow that are complemented by simulations of vortical flow between red blood cells.
Biological Physics Fluid Dynamics Cell Behavior
Disaster Resilience and Asset Prices
This paper investigates whether security markets price the effect of social distancing on firms' operations.
A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation
To address this problem, we propose a generic semi-supervised learning framework for image segmentation based on a deep convolutional neural network (DCNN).
Autonomous robotic nanofabrication with reinforcement learning
Here, we present a strategy to work around both obstacles, and demonstrate autonomous robotic nanofabrication by manipulating single molecules.
Measuring Inter-group Agreement on zSlice Based General Type-2 Fuzzy Sets
While previously, the Agreement Ratio was proposed to measure the strength of agreement in fuzzy set based models of interval data, said measure has only been applicable to type-1 fuzzy sets.
Measuring Player's Behaviour Change over Time in Public Goods Game
External clustering indices were originally used to measure the difference between suggested clusters in terms of clustering algorithms and ground truth labels for items provided by experts.
Modelling Cyber-Security Experts' Decision Making Processes using Aggregation Operators
An important role carried out by cyber-security experts is the assessment of proposed computer systems, during their design stage.
Exploring Differences in Interpretation of Words Essential in Medical Expert-Patient Communication
As the results of these questionnaires are often used to assess patient progress and to determine future treatment options, it is important to establish that the words used are interpreted in the same way by both patients and medical professionals.
Applying Interval Type-2 Fuzzy Rule Based Classifiers Through a Cluster-Based Class Representation
Fuzzy Rule-Based Classification Systems (FRBCSs) have the potential to provide so-called interpretable classifiers, i. e. classifiers which can be introspective, understood, validated and augmented by human experts by relying on fuzzy-set based rules.
Optimising Rule-Based Classification in Temporal Data
Based on these initial classifications, the optimisation process tries to find an improved classifier which produces the best possible compact classes of objects (players) for every time point in the temporal data.
Precision measurement of the local bias of dark matter halos
We present accurate measurements of the linear, quadratic, and cubic local bias of dark matter halos, using curved "separate universe" N-body simulations which effectively incorporate an infinite-wavelength overdensity.
Cosmology and Nongalactic Astrophysics
Separate Universe Simulations
The large-scale statistics of observables such as the galaxy density are chiefly determined by their dependence on the local coarse-grained matter density.
Cosmology and Nongalactic Astrophysics
Analysing Fuzzy Sets Through Combining Measures of Similarity and Distance
This is especially true where a large number of fuzzy sets are being compared as part of a reasoning system.
A Fuzzy Directional Distance Measure
The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory, however, distance measures currently within the literature use a crisp value to represent the distance between fuzzy sets.
Multiobjective Optimization and Comparisonof Nonsingleton Type-1 and Singleton IntervalType-2 Fuzzy Logic Systems
We will also present a multiobjective evolution-ary algorithm (MOEA) for the optimization of singleton type-1, nonsingleton type-1, and singleton interval type-2 fuzzy systems forfunction approximation problems.
Measuring the Directional Distance Between Fuzzy Sets
The measure of distance between two fuzzy sets is a fundamental tool within fuzzy set theory.
Extending Similarity Measures of Interval Type-2 Fuzzy Sets to General Type-2 Fuzzy Sets
Similarity measures provide one of the core tools that enable reasoning about fuzzy sets.
Creating Personalised Energy Plans. From Groups to Individuals using Fuzzy C Means Clustering
Changes in the UK electricity market mean that domestic users will be required to modify their usage behaviour in order that supplies can be maintained.
