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Constrained Probabilistic Pareto Dominance for Expensive Constrained Multiobjective Optimization Problems

IEEE Transactions on Evolutionary computation 2024年 1-1页

作者： Zhang, Zhiyao Wang, Yong Sun, Guangyong Pang, Tong Tang, Ke School of Automation Central South University Changsha China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha China Guangdong Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering and the Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China

This paper proposes a new parameterless constraint-handling technique, named constrained probabilistic Pareto dominance (CPPD), for expensive constrained multiobjective optimization problems (CMOPs). In CPPD, when comparing two solutions, in terms of each original objective, we design a new objective for each solution, which is the negative product of two probabilities calculated based on the predicted fitness mean values and the uncertainty information provided by Kriging models: 1) the probability that this solution satisfies all constraints, denoted as PoF, and 2) the probability that this solution is better than the other on the original objective, denoted as PoB. It is evident that for each solution, PoF and PoB indicate its feasibility and its optimality on the corresponding original objective, respectively. Then, Pareto dominance based on new objectives is executed. As a result, both competitive feasible solutions and promising infeasible solutions with good diversity can be preserved by CPPD. These two kinds of solutions can help the population to exploit the located feasible parts and to explore new feasible parts, respectively. Further, based on CPPD, we develop a Pareto-based Kriging-assisted constrained multiobjective evolutionary algorithm (called PEA) to deal with expensive CMOPs with two or three objectives. Finally, PEA is generalized to solve expensive constrained many-objective optimization problems, named PEA+. The effectiveness of CPPD, PEA, and PEA+ is verified by comprehensive experiments. IEEE

关键词： Evolutionary algorithms

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Surface Uptake of Exogenous Volatile Organic Compounds Enhances the NO2-to-HONO Conversion on Soot

ACS ES&T Air

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ACS ES&T Air 2025年第6期2卷 1107-1114页

作者： Xinyuan Zhao Qiang Wang Peng Zhang Yonghong Wang Shuying Li Zhanyu Su Jun Liu Biwu Chu Qingxin Ma Yujing Mu Hong He College of Environmental Science and Engineering Beijing Forestry University Beijing 100083 China；State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China College of Environmental Science and Engineering Beijing Forestry University Beijing 100083 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China；Institute of Urban Environment Chinese Academy of Sciences Xiamen 361021 China；State Key Laboratory of Advanced Environmental Technology Institute of Urban Environment Xiamen 361021 China

Heterogeneous reduction of nitrogen dioxides (NO2) on soot has been suggested to be a source of nitrous oxide (HONO) in the atmosphere. However, conventional wisdom says that the contribution of NO2reduction on soot to HONO formation is limited due to the rapid deactivation of surface reductive sites in the atmosphere. On the contrary, we show that adsorbed anthropogenic and biogenic volatile organic compounds (VOCs), collectively called exogenous VOCs (EVOCs), can persistently promote the heterogeneous conversion of NO2to HONO on soot. The surface uptake of NO2driven by H2O, coupled with the hydrogen reduction of NO2supported by EVOCs on elemental carbon (EC), is proposed to be the key pathway causing the persistent production of HONO. Furthermore, field observation conducted during biomass burning seasons in the North China Plain also showed that the presence of EVOCs promotes HONO production significantly. Our results imply that the continuous adsorption and conversion of EVOCs on soot surfaces may have a remarkable enhancing impact on the persistent conversion of NO2to HONO in the atmosphere.

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Experimental Study on the Relationship Between Performance and Structural Parameters of Metal Fiber 29

Experimental Study on the Relationship Between Performance a...

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2022 29th International Conference on Nuclear engineering, ICONE 2022

作者： Li, Lintai Zhou, Yanmin Li, Yuanyuan Sun, Zhongning Wang, Yin Gu, Haifeng Ma, Song Heilongjiang Provincial Key Laboratory of Nuclear Power System & Equipment Harbin Engineering University Harbin150001 China Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150001 China China Nuclear Power Engineering Co. Ltd Beijing100005 China

ISBN: (纸本)9780791886502

As a new filter material, metal fiber has good high-temperature resistance, moisture resistance, and radiation resistance. To explore the influence of the fiber's primary structural parameters on the fiber's performance, this paper experimentally studied the relationship between the flow resistance, filtration efficiency, and dust holding capacity of the metal fiber filter material and the thickness and solid volume fraction (SVF). Under the condition of ensuring uniform deposition of NaCl aerosol, we found that the deposition law of NaCl polydisperse aerosol is the same as that of monodisperse aerosol. The results show that for the same fiber diameter, increasing the fiber's thickness and SVF will increase the flow resistance of the fiber under the same dust holding capacity;that is, reducing the dust holding capacity of the fiber. In the depth filtration, the efficiency increases rapidly due to the aerosol deposition in the fiber, while the efficiency changes gently when the filter cake is covered on the filtration surface. At the same time, for each high filtration efficiency fiber, the variation characteristics of resistance with dust holding capacity in the deep filtration stage are the same. After the filter cake is completely covered on the filter surface, the growth trend of resistance is the same, independent of the fiber's structural parameters. © 2022 by ASME.

关键词： Fibers

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When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions 24

When Federated Recommendation Meets Cold-Start Problem: Sepa...

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33rd ACM Web Conference, WWW 2024

作者： Zhang, Chunxu Long, Guodong Zhou, Tianyi Zhang, Zijian Yan, Peng Yang, Bo College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Australian Artificial Intelligence Institute FEIT University of Technology Sydney Sydney Australia Computer Science and Umiacs University of Maryland MD United States College of Computer Science and Technology Jilin University City University of Hong Kong Hong Kong City University of Hong Kong Hong Kong

ISBN: (纸本)9798400701719

Federated recommendation system usually trains a global model on the server without direct access to users' private data on their own devices. However, this separation of the recommendation model and users' private data poses a challenge in providing quality service, particularly when it comes to new items, namely cold-start recommendations in federated settings. This paper introduces a novel method called Item-aligned Federated Aggregation (IFedRec) to address this challenge. It is the first research work in federated recommendation to specifically study the cold-start scenario. The proposed method learns two sets of item representations by leveraging item attributes and interaction records simultaneously. Additionally, an item representation alignment mechanism is designed to align two item representations and learn the meta attribute network at the server within a federated learning framework. Experiments on four benchmark datasets demonstrate IFedRec's superior performance for cold-start scenarios. Furthermore, we also verify IFedRec owns good robustness when the system faces limited client participation and noise injection, which brings promising practical application potential in privacy-protection enhanced federated recommendation systems. The implementation code is available © 2024 ACM.

关键词： Recommender systems

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Combating air pollution significantly reduced air mercury concentrations in China

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National science Review 2024年第9期11卷 202-212页

作者： Xinbin Feng Xuewu Fu Hui Zhang Xun Wang Longyu Jia Leiming Zhang Che-Jen Lin Jen-How Huang Kaiyun Liu Shuxiao Wang State Key Laboratory of Environmental Geochemistry Institute of GeochemistryChinese Academy of Sciences University of Chinese Academy of Sciences Air Quality Research Division Science and Technology BranchEnvironment and Climate Change Canada Center for Advances in Water and Air Quality Lamar University State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University College of Environmental Science and Engineering North China Electric Power University

In the past decade, China has motivated proactive emission control measures that have successfully reduced emissions of many air pollutants. For atmospheric mercury, which is a globally transported neurotoxin,much less is known about the long-term changes in its concentrations and anthropogenic emissions in China. In this study, over a decade of continuous observations at four Chinese sites show that gaseous elemental mercury（GEM） concentrations continuously increased until the early 2010s, followed by significant declines at rates of 1.8%–6.1% yr-1until 2022. The GEM decline from 2013 to 2022（by38.6% ± 12.7%） coincided with the decreasing concentrations of criteria air pollutants in China and were larger than those observed elsewhere in the northern hemisphere（5.7%–14.2%）. The co-benefits of emission control measures contributed to the reduced anthropogenic Hg emissions and led to the GEM decline in China. We estimated that anthropogenic GEM emissions in China were reduced by 38%–50%（116–151 tons） from 2013 to 2022 using the machine-learning and relationship models.

关键词： atmospheric mercury long-term trend anthropogenic emission reductions co-benefits of clean air action

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Multiobjective Optimization with Fuzzy Classification-Assisted Environmental Selection 11th

Multiobjective Optimization with Fuzzy Classification-Assist...

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11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021

作者： Zhang, Jinyuan Ishibuchi, Hisao Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783030720612

Most environmental selection strategies in multiobjective evolutionary algorithms (MOEAs) select solutions based on their objective function values. However, the objective evaluations of many real-world problems are very time-consuming. The use of a large number of objective evaluations will inevitably reduce the efficiency of MOEAs. This paper proposes a fuzzy classification-assisted environmental selection (FAES) scheme to reduce the number of objective evaluations of MOEAs. The proposed method uses a fuzzy classifier to choose promising solutions in environmental selection. In the proposed method, first, solutions in the previous generations are classified into two classes using the Pareto dominance relation. The non-dominated solutions are positive class, and the dominated solutions are negative class. Next, the classified solutions are used to build a fuzzy classifier. Then, the built classifier is used to predict the membership degree of each of the current and offspring solutions. Only the offspring solutions, whose membership degrees to the positive class are larger than their parents’, are evaluated. The offspring solutions with smaller membership degrees are discarded with no objective evaluations. Therefore, the number of objective evaluations can be reduced. Finally, the evaluated offspring solutions are used in the environmental selection together with the current solutions. The proposed FAES strategy is integrated into an MOEA in computational experiments. Experimental results show the efficiency of the proposed FAES on reducing the number of objective evaluations. © 2021, Springer Nature Switzerland AG.

关键词： Efficiency

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Multiscale study of the dynamic friction coefficient due to asperity plowing

引用

Friction 2021年第4期9卷 822-839页

作者： Jianqiao HU Hengxu SONG Stefan SANDFELD Xiaoming LIU Yueguang WEI State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100049China Institute for Advanced Simulation IAS-9:Materials Data Science and Informatics Forschungszentrum Juelich GmbHJuelich 52425Germany Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China

A macroscopically nominal flat surface is rough at the nanoscale level and consists of ***,the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity contact pairs under *** this work,we first used molecular dynamics simulations to study the non-adhesive shear between single contact ***,to estimate the friction coefficient of rough surfaces,we implemented the frictional behavior of a single contact pair into a Greenwood-Williamson-type statistical *** employing the present multiscale approach,we used the size,rate,and orientation effects,which originated from nanoscale dislocation plasticity,to determine the dependence of the macroscale friction coefficient on system parameters,such as the surface roughness,separation,loading velocity,and *** model predicts an unconventional dependence of the friction coefficient on the normal contact load,which has been observed in nanoscale frictional ***,this model represents one step toward understanding some of the relevant macroscopic phenomena of surface friction at the nanoscale level.

关键词： multiscale friction asperity plowing dislocation plasticity size/velocity effect crystal orientation statistical model

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AWEQ: Post-Training Quantization with Activation-Weight Equalization for Large Language Models

arXiv

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arXiv 2023年

作者： Li, Baisong Wang, Xingwang Xu, Haixiao School of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China

Large language models(LLMs) excellent performance across a variety of tasks, but they come with significant computational and storage costs. Quantizing these models is an effective way to alleviate this issue. However, existing methods struggle to strike a balance between model accuracy and hardware efficiency. This is where we introduce AWEQ, a post-training method that requires no additional training overhead. AWEQ excels in both ultra-low-bit quantization and 8-bit weight and activation (W8A8) quantization. There is an observation that weight quantization is less challenging than activation quantization. AWEQ transfers the difficulty of activation quantization to weights using channel equalization, achieving a balance between the quantization difficulties of both, and thereby maximizing performance. We have further refined the equalization method to mitigate quantization bias error, ensuring the robustness of the model. Extensive experiments on popular models such as LLaMA and OPT demonstrate that AWEQ outperforms all existing post-training quantization methods for large models. Copyright © 2023, The Authors. All rights reserved.

关键词： Chemical activation

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Affine Invariant Feature Based on Local Color

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Chinese Journal of Electronics 2023年第3期22卷 511-516页

作者： LIU Pingping ZHOU Qiuzhan ZHAO Hongwci School of Computer Science and Technology Jilin University Changchun China Ministry of Education Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Changchun China School of Communication Engineering Jilin University Changchun China

Image localization using local features has attracted a lot of attention in recent mobile robots research. A novel, fast local invariant feature in affine transformation is proposed in this article, called AIFLC (Affine invariant feature based on local color). We adopt affine moment invariants to build affine invariant descriptors. Moreover, we use color gradient based center moment instead of original pixel values in order to enhance discriminative power and robustness of descriptor in photometric transformations. simulation results show that the run time of AIFLC using optimal selection parameters is about 1/3 of classical SIFT algorithm. Using the standard evaluation images and the ones taken by mobile robots, we experimentally demonstrate that the AIFLC outperforms the state-of-art approaches such as SIFT and SURF in terms of image scaling, rotation, viewpoint changing, and blur transformations.

关键词： Location awareness Image color analysis Navigation simulation Lighting Real-time systems Robustness

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Population Sizing of Evolutionary Large-Scale Multiobjective Optimization 11th

Population Sizing of Evolutionary Large-Scale Multiobjective...

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11th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2021

作者： He, Cheng Cheng, Ran Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783030720612

Large-scale multiobjective optimization problems (LSMOPs) are emerging and widely existed in real-world applications, which involve a large number of decision variables and multiple conflicting objectives. Evolutionary algorithms (EAs) are naturally suitable for multiobjective optimization due to their population-based property, allowing the search of optima simultaneously. Nevertheless, LSMOPs are challenging for conventional EAs, mainly due to the huge volume of search space in LSMOPs. Thus, it is important to explore the impact of the population sizing on the performance of conventional multiobjective EAs (MOEAs) in solving LSMOPs. In this work, we compare several representative MOEAs with different settings of population sizes on some transformer ratio error estimation (TREE) problems in the power system. These test cases are defined on combinations of three population sizes, three TREE problems, and five MOEAs. Our results indicate that the performances of conventional MOEAs with different population sizes in solving LSMOPs are different. The impact of population sizing is most significant for differential evolution based and particle swarm based MOEAs. © 2021, Springer Nature Switzerland AG.

关键词： Multiobjective optimization

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