Ivan Izonin
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View article: Nature-inspired swarm optimization paradigms for securing semantic web frameworks against DDoS attacks: a computational approach
Nature-inspired swarm optimization paradigms for securing semantic web frameworks against DDoS attacks: a computational approach Open
The Semantic Web has transformed the way data is represented, shared, and integrated across multiple domains. However, as its size and interconnectedness continue to grow, it becomes increasingly exposed to cyber threats. Securing the Sema…
View article: Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case
Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case Open
In the field of transplantology, where medical decisions are heavily dependent on complex data analysis, the challenge of small data has become increasingly prominent. Transplantology, which focuses on the transplantation of organs and tis…
View article: An enhanced cascade ensemble method for big data analysis
An enhanced cascade ensemble method for big data analysis Open
In the digital age, the proliferation of data presents both challenges and opportunities, particularly in the realm of big data, which is characterized by its volume, velocity, and variety. Machine learning is a crucial technology for extr…
View article: Enhancing the FFT-LSTM Time-Series Forecasting Model via a Novel FFT-Based Feature Extraction–Extension Scheme
Enhancing the FFT-LSTM Time-Series Forecasting Model via a Novel FFT-Based Feature Extraction–Extension Scheme Open
The importance of enhancing the accuracy of time-series forecasting using artificial intelligence tools is increasingly critical in light of the rapid advancements in modern technologies, particularly deep learning and neural networks. The…
View article: Time Series Forecasting Model Based on the Adapted Transformer Neural Network and FFT-Based Features Extraction
Time Series Forecasting Model Based on the Adapted Transformer Neural Network and FFT-Based Features Extraction Open
In today’s data-driven world, where information is one of the most valuable resources, forecasting the behavior of time series, collected by modern sensor networks and IoT systems, is crucial across various fields, including finance, clima…
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: GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach
GRNN-based cascade ensemble model for non-destructive damage state identification: small data approach Open
Assessing the structural integrity of ageing structures that are affected by climate-induced stressors, challenges traditional engineering methods. The reason is that structural degradation often initiates and advances without any notable …
View article: An approach toward improvement of ensemble method’s accuracy for biomedical data classification
An approach toward improvement of ensemble method’s accuracy for biomedical data classification Open
Amidst rapid technological and healthcare advancements, biomedical data classification using machine learning (ML) is pivotal for revolutionizing medical diagnosis, treatment, and research by organizing vast healthcare-related data. Despit…
View article: A Method for Reducing Training Time of ML-Based Cascade Scheme for Large-Volume Data Analysis
A Method for Reducing Training Time of ML-Based Cascade Scheme for Large-Volume Data Analysis Open
We live in the era of large data analysis, where processing vast datasets has become essential for uncovering valuable insights across various domains of our lives. Machine learning (ML) algorithms offer powerful tools for processing and a…
View article: Improvement of the ANN-Based Prediction Technology for Extremely Small Biomedical Data Analysis
Improvement of the ANN-Based Prediction Technology for Extremely Small Biomedical Data Analysis Open
Today, the field of biomedical engineering spans numerous areas of scientific research that grapple with the challenges of intelligent analysis of small datasets. Analyzing such datasets with existing artificial intelligence tools is a com…
View article: Multi-Step Dynamic Ensemble Selection to Estimate Software Effort
Multi-Step Dynamic Ensemble Selection to Estimate Software Effort Open
Software Effort Estimation (SEE) is a foremost concern of software companies in order to successfully develop and deliver software products within a defined budget and time. Many software companies fail to deliver the product on time, eith…
View article: Advancements in AI-Based Information Technologies: Solutions for Quality and Security
Advancements in AI-Based Information Technologies: Solutions for Quality and Security Open
At the current stage of development and implementation of information technology in various areas of human activity, decisive changes are taking place, as there are powerful technical resources for the accumulation and processing of large …
View article: Quality and Security of Critical Infrastructure Systems
Quality and Security of Critical Infrastructure Systems Open
The amount of information is constantly growing, and thus, the issue of information security is becoming more acute [...]
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: AN UNSUPERVISED-SUPERVISED ENSEMBLE TECHNOLOGY WITH NON-ITERATIVE TRAINING ALGORITHM FOR SMALL BIOMEDICAL DATA ANALYSIS
AN UNSUPERVISED-SUPERVISED ENSEMBLE TECHNOLOGY WITH NON-ITERATIVE TRAINING ALGORITHM FOR SMALL BIOMEDICAL DATA ANALYSIS Open
Improving the accuracy of intelligent data analysis is an important task in various application areas. Existing machine learning methods do not always provide a sufficient level of classification accuracy for their use in practice. That is…
View article: An Ensemble Method for the Regression Model Parameter Adjustments: Direct Approach
An Ensemble Method for the Regression Model Parameter Adjustments: Direct Approach Open
Intelligence analysis of tabular datasets in the field of biomedical engineering is a complex task. This is explained both by the multidimensional datasets and the complex relationships between the components of the set, and by the high pr…
View article: A cascade ensemble-learning model for the deployment at the edge: case on missing IoT data recovery in environmental monitoring systems
A cascade ensemble-learning model for the deployment at the edge: case on missing IoT data recovery in environmental monitoring systems Open
In recent years, more and more applied industries have relied on data collection by IoT devices. Various IoT devices generate vast volumes of data that require efficient processing. Usually, the intellectual analysis of such data takes pla…
View article: An improved ANN-based global-local approximation for small medical data analysis
An improved ANN-based global-local approximation for small medical data analysis Open
INTRODUCTION: The task of approximation of complex nonlinear dependencies, especially in the case of short datasets, is important in various applied fields of medicine. Global approximation methods describe the generalized behavior of the …
View article: PREDICTION OF HARDNESS, FLEXURAL STRENGTH, AND FRACTURE TOUGHNESS OF ZRO2 BASED CERAMICS USING ENSEMBLE LEARNING ALGORITHMS
PREDICTION OF HARDNESS, FLEXURAL STRENGTH, AND FRACTURE TOUGHNESS OF ZRO2 BASED CERAMICS USING ENSEMBLE LEARNING ALGORITHMS Open
Flexural strength, hardness, and fracture toughness are the basic mechanical properties of ceramic materials. Manufacturers widely use this set of properties to ensure the durability of ceramic products. However, many factors, such as chem…
View article: Design and implementation of adaptive network stabilization based on artificial bees colony optimization for nature inspired cyber security
Design and implementation of adaptive network stabilization based on artificial bees colony optimization for nature inspired cyber security Open
Adaptive Defense has become an important factor in order to maintain device safety and security on the Internet. In 2021, there were more than 10 billion devices connected to the Internet which is estimated to exceed 25.4 billion by 2030. …
View article: Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks
Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks Open
This paper presents a parallel approach to the Levenberg-Marquardt algorithm (LM). The use of the Levenberg-Marquardt algorithm to train neural networks is associated with significant computational complexity, and thus computation time. As…