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Institution

Northeastern University (China)

EducationShenyang, China
About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).


Papers
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Journal ArticleDOI
TL;DR: The experimental results demonstrate that the proposed G-MFEA works more efficiently for multitasking optimization and successfully accelerates the convergence of expensive optimization problems compared to single-task optimization.
Abstract: Conventional evolutionary algorithms (EAs) are not well suited for solving expensive optimization problems due to the fact that they often require a large number of fitness evaluations to obtain acceptable solutions. To alleviate the difficulty, this paper presents a multitasking evolutionary optimization framework for solving computationally expensive problems. In the framework, knowledge is transferred from a number of computationally cheap optimization problems to help the solution of the expensive problem on the basis of the recently proposed multifactorial EA (MFEA), leading to a faster convergence of the expensive problem. However, existing MFEAs do not work well in solving multitasking problems whose optimums do not lie in the same location or when the dimensions of the decision space are not the same. To address the above issues, the existing MFEA is generalized by proposing two strategies, one for decision variable translation and the other for decision variable shuffling, to facilitate knowledge transfer between optimization problems having different locations of the optimums and different numbers of decision variables. To assess the effectiveness of the generalized MFEA (G-MFEA), empirical studies have been conducted on eight multitasking instances and eight test problems for expensive optimization. The experimental results demonstrate that the proposed G-MFEA works more efficiently for multitasking optimization and successfully accelerates the convergence of expensive optimization problems compared to single-task optimization.

182 citations

Journal ArticleDOI
TL;DR: In this article, annealing in air or oxygen in the range 350-450/sup 0/C produced material which analyzed as 6.94 (2) and 6.15-6.60, respectively.
Abstract: On the basis of iodometric determinations of the oxidation state of Cu in YBa/sub 2/Cu/sub 3/O/sub 7-x/, TGA experiments, and equilibrium reactions, the highest oxygen content of 6.96 (2) is achieved when annealing in O/sub 2/ at about 440/sup 0/C. Annealing in air or oxygen in the range 350-450/sup 0/C produced material which analyzed as 6.94 (2). The orthorhombic phase exists over the composition range O/sub 6.96/-O/sub 6.60/. The tetragonal composition YBa/sub 2/Cu/sub 3/O/sub 6/ is prepared by heating the mixture in an inert atmosphere, Ar or N/sub 2/, at temperatures in excess of 700/sup 0/C. The oxygen solution range for this phase ranges from O/sub 6.0/ to O/sub 6.15/. Compositions with nominal oxygen contents of 6.15-6.60 may be mixtures of the tetragonal and orthorhombic phases.

181 citations

Journal ArticleDOI
TL;DR: Several choices of Lyapunov equations over various graph topologies are presented, which play an important role in controller design and stability analysis of multi-agent systems.

181 citations

Journal ArticleDOI
TL;DR: Extraordinarily high reversible capacity of lithium-ion battery anodes is realized from SnO(2)/α-MoO(3) core-shell nanobelts that makes extra Li(2)O reversibly convert to Li(+).

181 citations

Journal ArticleDOI
TL;DR: This work proposes dynamic Bloom filters to represent dynamic sets, as well as static sets and design necessary item insertion, membership query, item deletion, and filter union algorithms.
Abstract: A Bloom filter is an effective, space-efficient data structure for concisely representing a set, and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a sufficiently low level. By investigating mainstream applications based on the Bloom filter, we reveal that dynamic data sets are more common and important than static sets. However, existing variants of the Bloom filter cannot support dynamic data sets well. To address this issue, we propose dynamic Bloom filters to represent dynamic sets, as well as static sets and design necessary item insertion, membership query, item deletion, and filter union algorithms. The dynamic Bloom filter can control the false positive probability at a low level by expanding its capacity as the set cardinality increases. Through comprehensive mathematical analysis, we show that the dynamic Bloom filter uses less expected memory than the Bloom filter when representing dynamic sets with an upper bound on set cardinality, and also that the dynamic Bloom filter is more stable than the Bloom filter due to infrequent reconstruction when addressing dynamic sets without an upper bound on set cardinality. Moreover, the analysis results hold in stand-alone applications, as well as distributed applications.

181 citations


Authors

Showing all 36436 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Hui-Ming Cheng147880111921
Yonggang Huang13679769290
Yang Liu1292506122380
Tao Zhang123277283866
J. R. Dahn12083266025
Terence G. Langdon117115861603
Frank L. Lewis114104560497
Xin Li114277871389
Peng Wang108167254529
David J. Hill107136457746
Jian Zhang107306469715
Xuemin Shen106122144959
Yi Zhang102181753417
Tao Li102248360947
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023166
2022906
20214,689
20204,118
20193,653
20182,878