Václav Snåšel
YOU?
Author Swipe
View article: Multiscale SPD manifold learning for rehabilitation exercise evaluation
Multiscale SPD manifold learning for rehabilitation exercise evaluation Open
Rehabilitation exercise assessment plays a crucial role in patient recovery, particularly for individuals recovering from injuries, surgeries, or illnesses affecting mobility. In this paper, we propose a novel approach for the assessment o…
View article: LLM-Enhanced metaheuristics with single-shot and few-shot learning for multi-robot exploration tasks
LLM-Enhanced metaheuristics with single-shot and few-shot learning for multi-robot exploration tasks Open
Multi-robot exploration in unknown environments is a challenging optimization task. Although many optimization algorithms exist, there has been limited exploration of Large Language Models (LLMs) in the literature to enhance these methods.…
View article: Forecasting Power Quality Parameters Using Decision Tree and KNN Algorithms in a Small-Scale Off-Grid Platform
Forecasting Power Quality Parameters Using Decision Tree and KNN Algorithms in a Small-Scale Off-Grid Platform Open
This article presents the results of a performance comparison of four forecasting methods for prediction of electric power quality parameters (PQPs) in small-scale off-grid environments. Forecasting PQPs is crucial in supporting smart grid…
View article: MAAPO: an innovative membrane algorithm based on artificial protozoa optimizer for multilevel threshold image segmentation
MAAPO: an innovative membrane algorithm based on artificial protozoa optimizer for multilevel threshold image segmentation Open
This paper proposes a novel membrane algorithm based on artificial protozoa optimizer (MAAPO) for global optimization problems. The artificial protozoa optimizer (APO) is adopted as the base meta-heuristic algorithm due to its novelty and …
View article: EPICS: error-preserved and interpolation-corrected surrogate-assisted particle swarm optimization for complex optimization
EPICS: error-preserved and interpolation-corrected surrogate-assisted particle swarm optimization for complex optimization Open
Surrogate-assisted particle swarm optimization (SAPSO) has been proven to be efficient in solving high-dimension problems. However, the error originating from the surrogate model tends to mislead search direction and frequently traps in a …
View article: Optimization Strategies for Variational Quantum Algorithms in Noisy Landscapes
Optimization Strategies for Variational Quantum Algorithms in Noisy Landscapes Open
Variational Quantum Algorithms (VQAs) are a leading approach for near-term quantum computing but face major optimization challenges from noise, barren plateaus, and complex energy landscapes. We benchmarked more than fifty metaheuristic al…
View article: A goal programming-based algorithm for solving multi objective optimization problems
A goal programming-based algorithm for solving multi objective optimization problems Open
In multiobjective optimization scenarios, the challenge lies in balancing several conflicting objectives; classic optimization methods, which focus on a single measurable criterion, do not adequately address this issue. The existing approa…
View article: Master–Slave Architecture Enhanced and Improved <scp>GBO</scp> Tuned Cascaded <scp>PI</scp>‐<scp>PDN</scp> Controller for Speed Regulation of <scp>DC</scp> Motors
Master–Slave Architecture Enhanced and Improved <span>GBO</span> Tuned Cascaded <span>PI</span>‐<span>PDN</span> Controller for Speed Regulation of <span>DC</span> Motors Open
This study introduces a novel master–slave architecture featuring an improved gradient‐based optimizer (ImGBO) to effectively tune a cascaded proportional‐integral (PI) and proportional‐derivative with filter (PDN) controller specifically …
View article: A comprehensive DEA-based framework for evaluating sustainability and efficiency of vehicle types: Integrating undesirable inputs and social-environmental indicators
A comprehensive DEA-based framework for evaluating sustainability and efficiency of vehicle types: Integrating undesirable inputs and social-environmental indicators Open
The sustainability and efficiency of different vehicle types play a crucial role in reducing environmental impacts. As governments and industries move towards greener transportation, choosing an appropriate evaluation method remains a chal…
View article: Enhanced aquila optimizer for global optimization and data clustering
Enhanced aquila optimizer for global optimization and data clustering Open
The Aquila Optimizer (AO) is a newly proposed, highly capable metaheuristic algorithm based on the hunting and search behavior of the Aquila bird. However, the AO faces some challenges when dealing with high-dimensional optimization proble…
View article: Analysis of deep learning under adversarial attacks in hierarchical federated learning
Analysis of deep learning under adversarial attacks in hierarchical federated learning Open
Hierarchical Federated Learning (HFL) extends traditional Federated Learning (FL) by introducing multi-level aggregation in which model updates pass through clients, edge servers, and a global server. While this hierarchical structure enha…
View article: A Hybrid PSO-GCRA Framework for Optimizing Control Systems Performance
A Hybrid PSO-GCRA Framework for Optimizing Control Systems Performance Open
Optimization is essential for improving the performance of control systems, particularly in scenarios that involve complex, non-linear, and dynamic behaviors. This paper introduces a new hybrid optimization framework that merges Particle S…
View article: Optimizing Intrusion Detection in Wireless Sensor Networks via the Improved Chameleon Swarm Algorithm for Feature Selection
Optimizing Intrusion Detection in Wireless Sensor Networks via the Improved Chameleon Swarm Algorithm for Feature Selection Open
In this paper, the improved chameleon swarm algorithm (ICSA) enhances the exploration–exploitation balance while optimizing feature subset selection. The integration of Lévy flight‐based exploration refines ICSA's search strategy, compleme…
View article: A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction
A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction Open
A brain tumor, one of the deadliest disorders, is characterized by the abnormal growth of synapses in the brain. Early detection can improve brain tumor diagnosis, and accurate diagnosis is essential for effective treatment. Researchers ha…