Verified propagation of imprecise probabilities in non-linear ODEs
We combine reachability analysis and probability bounds analysis, which allow for imprecisely known random variables (multivariate intervals or p-boxes) to be specified as the initial states of a dynamical system. In combination, the methods ...
GFDC: A granule fusion density-based clustering with evidential reasoning
Density-based clustering algorithms are known for their ability to detect irregular clusters, but they have limitations when it comes to dealing with clusters of varying densities. In this paper, we propose a new clustering algorithm called ...
A novel approach to discretizing information systems associated with neighborhood rough sets
By effectively capturing the similarity relationship between objects, neighborhood rough set models offer a highly advantageous approach to analyzing numerical data. However, it is computationally demanding to construct granular structures by ...
An efficient method of renewing object-induced three-way concept lattices involving decreasing attribute-granularity levels
In three-way concept analysis, changing (decreasing or increasing) attribute-granularity levels is needed to seek desirable information. Reconstructing three-way concept lattices often requires huge computation and long elapsed time when ...
A direct approach to representing algebraic domains by formal contexts
This paper is to establish closer links between domain theory and Formal Concept Analysis (FCA). We propose the notion of an optimised concept for a formal context, which has some properties similar to an intent. With the tool of optimised ...
Outlier detection for partially labeled categorical data based on conditional information entropy
Labeling a large amount of data is exceptionally costly and practically infeasible, and thus available data may have missing labels. In this article, we investigate outlier detection for partially labeled categorical data based on conditional ...
Three-way decisions with evaluative linguistic expressions
The theory of three-way decisions (3WD) requires dividing a finite, non-empty universe into three disjoint sets called positive, negative, and boundary regions. Three types of decisions are then made on the objects in each region: acceptance, ...
Change in quantitative bipolar argumentation: Sufficient, necessary, and counterfactual explanations
This paper presents a formal approach to explaining change of inference in Quantitative Bipolar Argumentation Frameworks (QBAFs). When drawing conclusions from a QBAF and updating the QBAF to then again draw conclusions (and so on), our approach ...
Construction methods of fuzzy implications on bounded posets
The fuzzy implication on bounded lattices was introduced by Palmeira et al., and the method of extending fuzzy implications on bounded lattices by using retraction was provided. However, we find that the extension of fuzzy implications on bounded ...
ω A -IvE methodology: Admissible interleaving entropy methods applied to video streaming traffic classification
This work focuses on the width-based interval fuzzy entropy notion, considering the interval data diameter as a measure of the lack of knowledge and uncertainty related to the precise membership degrees of elements in an interval-valued fuzzy ...
Improvements proposed to noisy-OR derivatives for multi-causal analysis: A case study of simultaneous electromagnetic disturbances
- Lokesh Devaraj,
- Qazi Mashaal Khan,
- Alastair R. Ruddle,
- Alistair P. Duffy,
- Richard Perdriau,
- Mohsen Koohestani
In multi-causal analysis, the independence of causal influence (ICI) assumed by the noisy-OR (NOR) model can be used to predict the probability of the effect when several causes are present simultaneously, and to identify (when it fails) inter-...
Changing behaviour under unfairness: An evolutionary model of the Ultimatum Game
Experimental results on the Ultimatum Game indicate that receivers may reject non-zero offers, even though that seems irrational. The explanation is that, when players are treated unfairly, they can act against strict rationality. This paper ...
Some general fusion and transformation frames for merging basic uncertain information
The Basic Uncertain Information (BUI) is a recently introduced type of uncertain data that has rapidly undergone development and practical application. The existing aggregation operators designed for BUI solely encompass the weighted mean and ...
A novel information fusion method using improved entropy measure in multi-source incomplete interval-valued datasets
Multi-source data is a comprehensive data type that combines multiple sources of information or datasets. Compared to point-valued data, interval-valued data provides a more accurate representation of the uncertainty and variability associated ...
How to choose a completion method for pairwise comparison matrices with missing entries: An axiomatic result
Since there exist several completion methods to estimate the missing entries of pairwise comparison matrices, practitioners face a difficult task in choosing the best technique. Our paper contributes to this issue: we consider a special set of ...
Classical iterative proportional scaling of log-linear models with rational maximum likelihood estimator
In this work we investigate multipartition models, the subset of log-linear models for which one can perform the classical iterative proportional scaling (IPS) algorithm to numerically compute the maximum likelihood estimate (MLE). Multipartition ...
Inversion of Bayesian networks
Variational autoencoders and Helmholtz machines use a recognition network (encoder) to approximate the posterior distribution of a generative model (decoder). In this paper we establish some necessary and some sufficient properties of a ...
Concepts of neighbors and their application to instance-based learning on relational data
Knowledge graphs and other forms of relational data have become a widespread kind of data, and powerful methods to analyze and learn from them are needed. Formal Concept Analysis (FCA) is a mathematical framework for the analysis of symbolic ...
Polyadic relational concept analysis
Formal concept analysis is a mathematical framework based on lattice theory that aims at representing the information contained in binary object-attribute datasets (called formal contexts) in the form of a lattice of so-called formal concepts. ...
A preferential interpretation of MultiLayer Perceptrons in a conditional logic with typicality
In this paper we investigate the relationships between a multipreferential semantics for defeasible reasoning in knowledge representation and a multilayer neural network model. Weighted knowledge bases for a simple description logic with ...
