Iryna Pliss
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View article: Enhanced Input-Doubling Method Leveraging Response Surface Linearization to Improve Classification Accuracy in Small Medical Data Processing
Enhanced Input-Doubling Method Leveraging Response Surface Linearization to Improve Classification Accuracy in Small Medical Data Processing Open
Currently, the tasks of intelligent data analysis in medicine are becoming increasingly common. Existing artificial intelligence tools provide high effectiveness in solving these tasks when analyzing sufficiently large datasets. However, w…
View article: An Approach Towards Reducing Training Time of the Input Doubling Method via Clustering for Middle-Sized Data Analysis
An Approach Towards Reducing Training Time of the Input Doubling Method via Clustering for Middle-Sized Data Analysis Open
Intellectual analysis of small and middle-sized datasets through machine learning tools presents challenges in various application domains. Existing methods fail to provide sufficient accuracy, and their utilization is accompanied by a ran…
View article: Credibilistic Fuzzy Clustering Method Based on Evolutionary Approach of Crazy Wolfs in Online Mode
Credibilistic Fuzzy Clustering Method Based on Evolutionary Approach of Crazy Wolfs in Online Mode Open
The problem of big data credibilistic fuzzy clustering is considered.This task was interested, when data are fed in both batch and online modes and has a lot of the global extremums.To find the global extremum of the objective function of …
View article: Clusterization of vector and matrix data arrays using the combined evolutionary method of fish schools
Clusterization of vector and matrix data arrays using the combined evolutionary method of fish schools Open
The problem of clustering data arrays described in both vector and matrix forms and based on the optimization of data distribution density functions in these arrays is considered. For the optimization of these functions, the algorithm that…
View article: Modified generalized neo-fuzzy system with combined online fast learning in medical diagnostic task for situations of information deficit
Modified generalized neo-fuzzy system with combined online fast learning in medical diagnostic task for situations of information deficit Open
In the paper, we propose the modified generalized neo-fuzzy system. It is designed to solve the pattern-image recognition task by working with data that are fed to the system in the image form. The neo-fuzzy system can work with small tra…
View article: Adaptive Probabilistic Neuro-Fuzzy System and its Hybrid Learning in Medical Diagnostics Task
Adaptive Probabilistic Neuro-Fuzzy System and its Hybrid Learning in Medical Diagnostics Task Open
Background: The medical diagnostic task in conditions of the limited dataset and overlapping classes is considered. Such limitations happen quite often in real-world tasks. The lack of long training datasets during solving real tasks in th…
View article: Credibilistic fuzzy clustering based on evolutionary method of crazy cats
Credibilistic fuzzy clustering based on evolutionary method of crazy cats Open
The problem of fuzzy clustering of large datasets that are sent for processing in both batch and online modes, based on a credibilistic approach, is considered. To find the global extremum of the credibilistic fuzzy clustering goal functio…
View article: Adaptive Learning of Evolving Hyper Basis Function Neural Network
Adaptive Learning of Evolving Hyper Basis Function Neural Network Open
In the article architecture and learning method of the artificial evolving hyper basis neural network are proposed.The neural network under consideration tunes not only its synaptic weights, but automatically determines neurons number, coo…
View article: Fast Probabilistic Neuro-Fuzzy System for Pattern Classification Task
Fast Probabilistic Neuro-Fuzzy System for Pattern Classification Task Open
The probabilistic neuro-fuzzy system to solve the image classification-recognition task is proposed. The considered system is a “hybrid” of Specht’s probabilistic neural network and the neuro-fuzzy system of Takagi-Sugeno-Kang. It is desig…
View article: Multidimensional Neo-Fuzzy-Neuron for Solving Medical Diagnostics Tasks in Online-Mode
Multidimensional Neo-Fuzzy-Neuron for Solving Medical Diagnostics Tasks in Online-Mode Open
In this paper neuro-fuzzy approach for medical data processing is considered. Special capacities for methods and systems of Computational Intelligence were introduced for Medical Data Mining tasks, like transparency and interpretability of…
View article: Deep Evolving Stacking Convex Cascade Neo-Fuzzy Network and Its Rapid Learning
Deep Evolving Stacking Convex Cascade Neo-Fuzzy Network and Its Rapid Learning Open
A deep evolving stacking convex neo-fuzzy network is proposed.It is a feedforward cascade hybrid system, the layers-stacks of which are formed by generalized neo-fuzzy neurons that implement Wang-Mendel fuzzy reasoning.The optimal in the s…
View article: Deep Hybrid System of Computational Intelligence with Architecture Adaptation for Medical Fuzzy Diagnostics
Deep Hybrid System of Computational Intelligence with Architecture Adaptation for Medical Fuzzy Diagnostics Open
In the paper the deep hybrid system of computational intelligence with architecture adaptation for medical fuzzy diagnostics is proposed.This system allows to increase a quality of medical information processing under the condition of over…
View article: Neo-Fuzzy Encoder and Its Adaptive Learning for Big Data Processing
Neo-Fuzzy Encoder and Its Adaptive Learning for Big Data Processing Open
In the paper a two-layer encoder is proposed. The nodes of encoder under consideration are neo-fuzzy neurons, which are characterised by high speed of learning process and effective approximation properties. The proposed architecture of ne…
View article: Deep Evolving GMDH-SVM-Neural Network and its Learning for Data Mining Tasks
Deep Evolving GMDH-SVM-Neural Network and its Learning for Data Mining Tasks Open
In the paper, the deep evolving neural network and its learning algorithms (in batch and on-line mode) are proposed.The deep evolving neural network's architecture is developed based on GMDH approach (in J. Schmidhuber's opinion it is hist…