Search · four archives
Search · four archives
19 papers · ranked by Valyu relevance
Umesh Uttamrao Shinde, Ravikumar Bandaru
The error correction model’s main purpose in heavy hexagonal quantum codes is to improve their reliability for quantum computing applications. Existing challenges include finding the optimal decoder for quantum error correction in heavy hexagonal codes. This research propels the frontier of quantum error correction…
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…
Zikai Wang, Xueyu Huang, Donglin Zhu
The swarm intelligence algorithm is a new technology proposed by researchers inspired by the biological behavior of nature, which has been practically applied in various fields. As a kind of swarm intelligence algorithm, the newly proposed sparrow search algorithm has attracted extensive attention due to its strong…
Shaoqiang Yan, Ping Yang, Donglin Zhu, Wanli Zheng + 1 more
This paper solves the shortcomings of sparrow search algorithm in poor utilization to the current individual and lack of effective search, improves its search performance, achieves good results on 23 basic benchmark functions and CEC 2017, and effectively improves the problem that the algorithm falls into local optimal…
Ping Yang, Shaoqiang Yan, Donglin Zhu, Jiangpeng Wang + 3 more
'Zhe Yan' 'Song Yan'] In order to overcome the defect that sparrow search algorithm converges very fast but is easy to fall into the trap of local optimization, based on the original mechanism of sparrow algorithm, this paper proposes game predatory mechanism and suicide mechanism, which makes sparrow algorithm more in…
Chengtian Ouyang, Donglin Zhu, Fengqi Wang
This paper solves the drawbacks of traditional intelligent optimization algorithms relying on 0 and has good results on CEC 2017 and benchmark functions, which effectively improve the problem of algorithms falling into local optimality. The sparrow search algorithm (SSA) has significant optimization performance, but…
Peng Wang, Yu Zhang, Hongwan Yang
With the deepening of the power market reform on the retail side, it is of great significance to study the economic optimization of the microgrid cluster system. Aiming at the economics of the microgrid cluster, comprehensively considering the degradation cost of energy storage battery, the compensation cost of…
Qinwen Yang, Yuelin Gao, Yanjie Song
The "Curse of Dimensionality" induced by the rapid development of information science, might have a negative impact when dealing with big datasets. In this paper, we propose a variant of the sparrow search algorithm (SSA), called Tent Lévy flying sparrow search algorithm (TFSSA), and use it to select the best subset of…
Yuan-Jie Chen, Ting Zhou
ultra-high-pressure water-jet nozzle using approximation method Authors: ['Yuan-Jie Chen' 'Ting Zhou'] Since the geometry structure of ultra-high-pressure (UHP) water-jet nozzle is a critical factor to enhance its hydrodynamic performance, it is critical to obtain a suitable geometry for a UHP water jet nozzle. In this…
Jeroen Gardeyn, Greet Vanden Berghe, Tony Wauters
2D nesting problems rank among the most challenging cutting and packing problems. Yet, despite their practical relevance, research over the past decade has seen remarkably little progress. One reasonable explanation could be that nesting problems are already solved to near optimality, leaving little room for…
Jie Wen, Chenyu Jia, Guangshu Xia
Aiming at the state of health (SOH) prediction of lithium-ion batteries (LiBs) for electric vehicles (EVs), this paper proposes a fusion model of a dual-module bidirectional gated recurrent unit (BiGRU) and sparrow search algorithm (SSA) with full parameter domain optimization. With the help of Spearman correlation…
Edouard R. Dufour, Pascal Fua
Black-box optimization is a fundamental science and engineering tool that makes it possible to optimize objectives without gradient information. Unfortunately, as it often requires many function evaluations, it can be challenging when each one is costly. This is especially true when the evaluation function is noisy or…
Lei He, Arthur Guijt, Mathijs de Weerdt, Lining Xing + 1 more
'Neil Yorke‐Smith'] The Order Acceptance and Scheduling (OAS) problem describes a class of real-world problems such as in smart manufacturing and satellite scheduling. This problem consists of simultaneously selecting a subset of orders to be processed as well as determining the associated schedule. A common…
Maria Ximena Bastidas-Rodriguez, Ana Melisa Fernandes, María José Espejo Uribe, Diana Abaunza + 7 more
Wingbeat frequency estimation is an important aspect for the study of avian flight, energetics, and behavioral patterns, among others. Hummingbirds, in particular, are ideal subjects to test a method for this estimation due to their fast wing motions and unique aerodynamics, which results from their ecological…
Marco Klein Heerenbrink, Lydia A. France, Graham K. Taylor
Flight is the most energetically costly activity that animals perform, making its optimisation crucial to evolutionary fitness. Steady flight behaviours like migration and commuting are adapted to minimise cost-of-transport or time-of-flight^1^, but the optimisation of unsteady flight behaviours is largely…
Clementine Bodin, Jasmin C.M. Wong, Shane Windsor, Sarah C. Woolley
Birds are capable of performing elaborate flight maneuvers in variable environmental conditions. While flight is an adaptable and skilled motor behavior, we know surprisingly little about how birds master this ability. Across species, skilled motor behaviors show practice-related changes or improvements in performance…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
Sonali Shinde, Ankur Patwardhan, Milind Watve
Among the classical models of optimization, some models maximize the ratio of returns per investment, others maximize the difference between returns and investment. However, the question under what conditions use of the ratio model is appropriate and under what conditions a difference model should be used remained…
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…