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This study aims to analyze students' learning participation in the blended teaching model based on swarm intelligence and multi-platform integration. Through a questionnaire survey, data from 666 college students were collected and analyzed using the ...

Force myography (FMG) is increasingly gaining importance in gesture recognition because of it’s ability to achieve high classification accuracy without having a direct contact with the skin. In this study, we investigate the performance of a ...

• Collect FMG signal using a bracelet with 6 FSR sensors.
• Investigate the performance of BGWOPSO as a feature selection and an optimizer for the ELM classifier and test it on real FMG data.
• Comapre the classification of 37 gestures ...

The Traveling Salesman Problem (TSP) has long been a challenging optimization puzzle, prompting the development of various methodologies to seek efficient solutions. In this paper, we propose an improved method utilizing a Swarm Intelligence-based ...

Swarm intelligence optimization algorithms have been widely used in the fields of machine learning, process control and engineering prediction, among which common algorithms include ant colony algorithm (ACO), artificial bee colony algorithm (ABC) and ...

Particle Swarm Optimization (PSO) is one of the most famous swarm-based algorithms used for solving optimization problems. PSO has received growing attention within many fields of the research community. Since its inception, some prominent ...

This paper presents a pioneering approach to personalized English oral education through the integration of deep learning and swarm intelligence algorithms. Leveraging deep learning techniques, our system offers precise evaluation of various aspects of ...

We propose a method based on particle swarm optimization (PSO) for the multi-agent pattern formation problem (MAPFP), which allows agents to form formation patterns with a high completion rate without overlaps. MAPFP is a problem in which a large ...

The progression in quantum computing and the rapid development of quantum computation hardware has raised expectations for its application to commercially relevant use cases in the future. However, the need for high-level quantum programming ...

Generative adversarial networks (GANs) have seen significant research interest over the past decade, yet core issues of training instability and mode collapse persist. This work proposes SwarmGAN, a novel GAN framework incorporating swarm intelligence ...

Swarm intelligence (SI) algorithms have become popular due to their self-learning characteristics and adaptability to external changes. They can find reasonable solutions to complex problems without in-depth knowledge. Much of the success of these ...

Mathematical modeling is crucial for analyzing how intensively a disease spreads across a population so that an adequate counterstrategy can be prepared. In this paper, we employ agent-based modeling (ABM) to analyze the SIR model (susceptible – ...

Fire hawk Optimizer (FHO) is a relatively new intake in the family of evolutionary algorithms for a distinct type of optimization problem. Initialization of the population plays a significant role in solving classical optimization issues. ...

Swarm Intelligence draws inspiration from the collective intelligent behavior of animals such as birds, fish, and bees. It refers to the collective behavior of decentralized, self-organized systems composed of many simple agents that interact with ...

The range of applications of swarm optimization algorithms is very vast. However, high dimensions and more number of decision variables make these optimization problems more complex. Particle Swarm Optimization (PSO) is the most popular optimizer ...

• A new Global Best-Worst Particle Swarm Optimization algorithm has been proposed to increase parallelism.
• The proposed algorithm uses concepts of the particle swarm optimization and Jaya algorithm.
• Systematic analysis of run time ...

In the past ten years, due to the rapid growth of the Internet, a huge number of cyber-crimes have been committed on the Internet. One of the crucial obstacles’ user’s encounters is the phishing website's threat, especially for login credentials ...

Campus basketball culture is gradually affecting students’ sports spirit and sports accomplishment. As for the evaluation of basketball teaching achievements, the method of specified items is generally used for testing, which is highly subjective. ...

• Hybrid global and local path planning for smart assistive navigation systems.
• Hybrid ACO with chaotic maps and Fuzzy Logic for multiobjective path planning.
• Bug-based algorithm with Fuzzy Logic for obstacle avoidance of static ...

Given the increased interest in smart assistive technologies and autonomous robot vehicles, path planning has emerged as one of the most researched and challenging topics in navigation. Moving to partially known or unknown environment, an ...

Due to its features regarding immutability, transparency and traceability, blockchain has emerged as a promising solution in various application domains. However, despite its advantages, blockchain suffers from major drawbacks in terms of scalability ...

In the past few years mobile Adhoc network(MANET) has been widely applied in a range of fields like road safety, sensors for the environment, home, health, disaster rescue operations, defense, weapons, robots, IOT applications etc. In this era of ...

Image classification is a fundamental and pervasive task in the field of computer vision, with profound implications across a wide array of applications. From the autonomous vehicles navigating complex urban environments to the critical diagnosis ...