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Search · four archives
25 papers · ranked by Valyu relevance
Mohd Nadhir Ab Wahab, Samia Nefti-Meziani, Adham Atyabi, Catalin Buiu
'Catalin Buiu'] Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known…
Minghai Xu, Li Cao, Dongwan Lu, Zhongyi Hu + 2 more
'Heming Jia'] Image processing technology has always been a hot and difficult topic in the field of artificial intelligence. With the rise and development of machine learning and deep learning methods, swarm intelligence algorithms have become a hot research direction, and combining image processing technology with…
Zoran Jakšić, Swagata Devi, Olga Jakšić, Koushik Guha + 3 more
The application of artificial intelligence in everyday life is becoming all-pervasive and unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired algorithms for multiparameter optimization, which find their use in a large number of areas. Novel methods and advances are being published at…
Deqi Li
Table tennis is China 's national game and the proudest sport in China's sports field. During the research and technology service work of the Chinese table tennis team for many years, it has accumulated a large amount of valuable data on the analysis of skills and tactics of training and matches, match video, training…
Thounaojam Chinglemba, Soujanyo Biswas, Debashish Malakar, Vivek Meena + 2 more
'Vivek Meena' 'Debojyoti Sarkar' 'Anupam Biswas'] > Abstract. With the rapid upliftment of technology, there has emerged a dire need to 'fine-tune' or 'optimize' certain processes, software, models or structures, with utmost accuracy and efficiency. Optimization algorithms are preferred over other methods of…
Xin‐She Yang, Suash Deb, Yuxin Zhao, Simon Fong + 1 more
Many optimization problems in science and engineering are challenging to solve, and the current trend is to use swarm intelligence (SI) and SI-based algorithms to tackle such challenging problems. Some significant developments have been made in recent years, though there are still many open problems in this area. This…
Joanna Kwiecień
Swarm intelligence draws its inspiration from the collective behaviour of many individual agents interacting with both one another and their environment. This paper presents a possibility to apply a swarm-based algorithm, modelled after the behaviour of individuals operating within a group where individuals move around…
Jiangnan Zhang, Kewen Xia, Ziping He, Shurui Fan
Bird swarm algorithm is one of the swarm intelligence algorithms proposed recently. However, the original bird swarm algorithm has some drawbacks, such as easy to fall into local optimum and slow convergence speed. To overcome these short-comings, a dynamic multi-swarm differential learning quantum bird swarm algorithm…
Sachan Rohit Kumar, Kushwaha Dharmender Singh
Nature-inspired algorithms are commonly used for solving the various optimization problems. In past few decades, various researchers have proposed a large number of nature-inspired algorithms. Some of these algorithms have proved to be very efficient as compared to other classical optimization methods. A young…
Shahira Shaaban Azab, Hesham A. Hefny
— This Paper represents a literature review of Swarm intelligence algorithm in the area of semi-supervised classification. There are many research papers for applying swarm intelligence algorithms in the area of machine learning. Some algorithms of SI are applied in the area of ML either solely or hybrid with other ML…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Iztok Fister, Iztok Fister
Numerical Association Rule Mining is a popular variant of Association Rule Mining, where numerical attributes are handled without discretization. This means that the algorithms for dealing with this problem can operate directly, not only with categorical, but also with numerical attributes. Until recently, a big…
Authors not listed
Swarm intelligence-based algorithms have proven successful in exploring a potential energy surfaces (PESs) of chemical systems. One of the major limitations to recent implementations of these algorithms is that they have been implemented serially. To overcome this limitation we present our asynchronously parallel…
David L. Krongauz, Teddy Lazebnik
Collective motion (CM) takes many forms in nature; schools of fish, flocks of birds, and swarms of locusts to name a few. Commonly, during CM the individuals of the group avoid collisions. These CM and collision avoidance (CA) behaviors are based on input from the environment such as smell, air pressure, and vision…
Charly Empereur-mot, Luca Pesce, Davide Bochicchio, Claudio Perego + 1 more
We present Swarm-CG, a versatile software for the automatic parametrization of bonded parameters incoarse-grained (CG) models. By coupling state-of-the-art metaheuristics to Boltzmann inversion, Swarm-CG performs accurate parametrization of bonded terms in CG models composed of up to 200 pseudoatomswithin 4h-24h on…
Marcos Oliveira, Diego Pinheiro, Mariana Macedo, Carmelo J. A. Bastos-Filho + 1 more
'Carmelo J. A. Bastos-Filho' 'Ronaldo Menezes'] Swarm intelligence is the collective behavior emerging in systems with locally interacting components. Because of their self-organization capabilities, swarm-based systems show essential properties for handling real-world problems such as robustness, scalability, and…
Utku Köse, Ahmet Arslan
In this paper, the idea of a new artificial intelligence based optimization algorithm, which is inspired from the nature of vortex, has been provided briefly. As also a bio-inspired computation algorithm, the idea is generally focused on a typical vortex flow / behavior in nature and inspires from some dynamics that…
Charly Empereur-mot, Luca Pesce, Davide Bochicchio, Claudio Perego + 1 more
We present Swarm-CG, a versatile software for the automatic parametrization of bonded parameters in coarse-grained (CG) models. By coupling state-of-the-art metaheuristics to Boltzmann inversion, Swarm-CG performs accurate parametrization of bonded terms in CG models composed of up to 200 pseudoatoms within 4h-24h on…
Ryusuke Fujisawa, Genki Ichinose, Shigeto Dobata
The evolution of complexity is one of the prime features of life on Earth. Although well accepted as the product of adaptation, the dynamics underlying the evolutionary build-up of complex adaptive systems remains poorly resolved. Using simulated robot swarms that exhibit ant-like group foraging with trail pheromones…
Qing Li, Lingwei Zhang, Yongnan Jia, Tianzhao Lu
Models of collective behaviour have been proved helpful in revealing what mechanism may underlie characteristics of a flock of birds, a school of fish, and a swarm of herds. Recently, the metric-free model gradually occupies a dominant position in the research field of collective intelligence. Most of these models…
Authors not listed
With the ever-increasing demand for atomistic structures representative of real-life systems as well as the ad-vent of exascale computers, it has now become necessary and possible to use advanced global optimization (GO) techniques to intelligently sample the potential energy surface (PES). Given the previous studies…
Kyanoush Seyed Yahosseini, Mehdi Moussaïd
Groups can be very successful problem-solvers. This collective achievement crucially depends on how the group is structured, that is, how information flows between members and how individual contributions are merged. Numerous methods have been proposed, which can be divided into two major categories: those that involve…
Ishriak Ahmed, Md. Saiful Islam, Imraan A. Faruque
Collective motions in biological organisms such as honey bees, midges, and birds exhibit remarkable coordination and adaptability, emerging from local interactions among individuals, including those with tight constraints on neural material. Understanding the underlying mechanisms behind the collective behavior of…
Daniel Gaissmaier, Matthias van den Borg, Donato Fantauzzi, Timo Jacob
In this work, we demonstrate the superior exploration capabilities of the population-based methods over the sequential one-parameter parabolic interpolation (SOPPI) approach to optimise ReaxFF force field parameters. Evolutionary algorithms (EAs) are heuristic-based approaches using a population of concurrent models in…
Olena Doroshenko
Pathfinding in complex topographies poses a challenge with applications extending from urban planning to autonomous navigation. While numerous algorithms offer potential solutions, their comparative efficiency and reliability when confronted with nonlinear terrains remain to be systematically evaluated. This study…