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Constraints on neutrino mass in the scenario of vacuum energy interacting with cold dark matter after Planck 2018

Communications in Theoretical Physics 2020年第12期72卷 152-162页

作者： Hai-Li Li Jing-Fei Zhang Xin Zhang College of Sciences&Ministry of Education’s Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern UniversityShenyang 110819China Center for High Energy Physics Peking UniversityBeijing 100080China Center for Gravitation and Cosmology Yangzhou UniversityYangzhou 225009China

In this work,we investigate the constraints on the total neutrino mass in the scenario of vacuum energy interacting with cold dark matter(abbreviated as IACDM)by using the latest cosmological *** consider four typical interaction forms,i.e.Q=βHρde,Q=βHρc,Q=βH0ρde,and Q=βH0ρc,in the IACDM *** avoid the large-scale instability problem in interacting dark energy models,we employ the extended parameterized post-Friedmann method for interacting dark energy to calculate the perturbation evolution of dark energy in these *** observational data used in this work include the cosmic microwave background(CMB)measurements from the Planck 2018 data release,the baryon acoustic oscillation(BAO)data,the type Ia supernovae(SN)observation(Pantheon compilation),and the 2019 local distance ladder measurement of the Hubble constant H0 from the Hubble Space *** find that,compared with those in the ACDM+∑mv model,the constrains on∑mv are looser in the four IACDM+∑mv *** considering the three mass hierarchies of neutrinos,the constraints on∑mv are tightest in the degenerate hierarchy case and loosest in the inverted hierarchy *** addition,in the four IACDM+∑mv models,the values of coupling parameterβare larger using the CMB+BAO+SN+H0 data combination than that using the CMB+BAO+SN data combination,andβ>0 is favored at more than 1σlevel when using CMB+BAO+SN+H0 data *** issue of the H0 tension is also discussed in this *** find that,compared with the ACDM+∑mv model,the H0 tension can be alleviated in the IACDM+∑mv model to some extent.

关键词： total neutrino mass neutrino mass hierarchies interacting dark energy Hubble tension cosmological observations

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Energy decision making of steel company based on energy management system

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IFAC-PapersOnLine 2020年第5期53卷 608-613页

作者： Yunqi Ban Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education China

With the promotion of the concept of smart city, every industry in the city needs to become more intelligent. As a pillar industry of economic development, the energy-intensive steel plant has brought challenges to the city environment. Factories in cities also need to be more intelligent. The application of artificial intelligence and data technology has become one of the important meaning to improve the management level of steel plant and to improve the city environment. As a modern management tool, energy management system provides a new way of intelligent management for iron and steel companies. The energy management system can be used to monitor the energy consumption in real time, master the energy consumption of the company and allocate the energy consumption of the company. So we can get better production plan, reduce the energy consumption of the company, and improve the competitiveness of the company. Two functions, energy allocation and energy consumption prediction, are developed in the energy management system. According to the formula of iron balance and the relationship between iron and energy consumption in each production unit, the mathematical model of energy allocation is established and applied in the energy management system. Another one of the functions of the energy management system is to predict the energy consumption of steel companies with maximum prediction error is about 5%, which provides the basis for the auxiliary decision-making of energy management. The forecasted results can be used to better understand the trend of energy consumption of the whole company, so as to do a good decision of energy reserve and reduce unnecessary waste.

关键词： energy management system energy prediction energy consumption decision making

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Prospects for weighing neutrinos in interacting dark energy models using joint observations of gravitational waves andγ-ray bursts

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Chinese Physics C 2024年第9期48卷 225-233页

作者： Lu Feng Tao Han Jing-Fei Zhang Xin Zhang College of Physical Science and Technology Shenyang Normal UniversityShenyang 110034China Key Laboratory of Cosmology and Astrophysics(Liaoning Province)&Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern UniversityShenyang 110819China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China

Cosmological observations can be used to weigh neutrinos,but this method is model-dependent,with results relying on the cosmological model *** we consider interactions between dark energy and dark matter,the neutrino mass constraints differ from those derived under the standard *** the contrary,gravitational wave(GW)standard siren observations can measure absolute cosmological distances,helping to break parameter degeneracies inherent in traditional cosmological observations,thereby improving constraints on neutrino *** paper examines the constraints on neutrino mass within interacting dark energy(IDE)models and explores how future GW standard siren observations could enhance these *** multi-messenger GW observations,we consider the joint observations of binary neutron star mergers by third-generation ground-based GW detectors and shortγ-ray burst observations by missions similar to the THESEUS satellite *** current cosmological observations(CMB+BAO+SN),we obtain an upper limit on the neutrino mass in the IDE models of 0.15(or 0.16)*** the inclusion of GW data,the upper limit on the neutrino mass improves to 0.14 *** indicates that in the context of IDE models,the improvement in neutrino mass constraints from GW observations is relatively ***,GW observations significantly enhance the constraints on other cosmological parameters,such as matter density parameter,the Hubble constant,and coupling strength between dark energy and dark matter.

关键词： interacting dark energy neutrino mass gravitational wave standard siren cosmology

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Prediction of Blast Furnace Temperature Based on Evolutionary optimization 11th

Prediction of Blast Furnace Temperature Based on Evolutionar...

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

作者： Hu, Tenghui Wang, Xianpeng Wang, Yao Dong, Zhiming Zhuang, Xinyu Liaoning Key Laboratory of Manufacturing System and Logistics Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China Ltd. Beijing100085 China

ISBN: (纸本)9783030720612

Blast furnace temperature, generally characterized by silicon content, is an important indicator to characterize the stability of furnace conditions in the blast furnace ironmaking process. To achieve its accurate prediction, a prediction model based on multi-objective evolutionary optimization and non-linear ensemble learning is proposed in this paper. First, the input features of each sub-learner are optimized through a modified discrete multi-objective evolutionary algorithm to obtain a set of highly accurate and diverse sub-learners. Subsequently, a nonlinear ensemble method based on extreme learning machine is employed to ensemble the obtained sub-learners to further improve the accuracy and robustness of the prediction model. Furthermore, the effectiveness of the proposed prediction method is verified by experiments based on actual production data. © 2021, Springer Nature Switzerland AG.

关键词： Forecasting

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A decision space variable topology feature visualization and clustering method for Dynamic Multi-objective optimization

A decision space variable topology feature visualization and...

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2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Chen, Min Zhang, Yanyan National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shen Yang China

ISBN: (纸本)9798400704956

We propose a dynamic multi-objective optimization algorithm for visualizing and clustering topological features of decision space variables. It maps all the obtained historical optimal solutions to the two-dimensional space through t-SNE, clusters the points, and selects a corresponding proportion of individuals from different clusters to form a new population. Throughout the search process, the topological characteristics of the reduced historical optimal solutions can be visually displayed. We conducted a preliminary experimental analysis on the standard test function to verify the effectiveness of the proposed method. © 2024 Copyright held by the owner/author(s).

关键词： Topology

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Symmetry Parallel Search Strategy For Permutation-related optimization Problems

Symmetry Parallel Search Strategy For Permutation-related Op...

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2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Li, Tianyang Meng, Ying Tang, Lixin Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China

ISBN: (纸本)9798400704956

In this paper, we propose a symmetry parallel search strategy that can be applied to permutation-related combinatorial optimization problems. The proposed symmetry parallel search strategy considers the parity of the permutations and decomposes the solution space into two independent regions, i.e., even and odd permutations. Then, we analyze the relations between the parity of permutations and two representative neighborhood search operators. This allows trajectory-based metaheuristics to keep searching on even or odd permutations without breaking the utility of search operators. For experiments, we take the quadratic assignment problem and two classical trajectory-based metaheuristics as a case study. Experimental results show that the trajectory-based metaheuristics embedded with the symmetry parallel search strategy can achieve a competitive performance. © 2024 held by the owner/author(s).

关键词： Combinatorial optimization

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Synergy between CSST galaxy survey and gravitational-wave observation: Inferring the Hubble constant from dark standard sirens

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Science China(Physics,Mechanics & Astronomy) 2024年第3期67卷 7-19页

作者： Ji-Yu Song Ling-Feng Wang Yichao Li Ze-Wei Zhao Jing-Fei Zhang Wen Zhao Xin Zhang Key Laboratory of Cosmology and Astrophysics(Liaoning)&College of Sciences Northeastern UniversityShenyang 110819China CAS Key Laboratory for Researches in Galaxies and Cosmology Department of AstronomyUniversity of Science and Technology of ChinaChinese Academy of SciencesHefei 230026China School of Astronomy and Space Sciences University of Science and Technology of ChinaHefei 230026China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern UniversityShenyang 110819China Key Laboratory of Data Analytics and Optimization for Smart Industry(Ministry of Education) Northeastern Universty Shenyang 110819China

Gravitational waves(GWs) from compact binary coalescences encode the absolute luminosity distances of GW sources. Once the redshifts of GW sources are known, one can use the distance-redshift relation to constrain cosmological parameters. One way to obtain the redshifts is to localize GW sources by GW observations and then use galaxy catalogs to determine redshifts from a statistical analysis of redshift information of the potential host galaxies, commonly referred to as the dark siren method. The third-generation(3G) GW detectors are planned to work in the 2030s and will observe numerous compact binary *** these GW events as dark sirens requires high-quality galaxy catalogs from future sky survey projects. The China Space Station Telescope(CSST) will be launched in 2024 and will observe billions of galaxies within a 17500 deg^(2) survey area with redshift up to z ~ 4, providing photometric and spectroscopic galaxy catalogs. In this work, we simulate the CSST galaxy catalogs and the 5-year GW data from the 3G GW detectors and combine them to infer the Hubble constant(H_(0)). Our results show that the measurement precision of H0could reach the sub-percent level, meeting the standard of precision cosmology. We conclude that the synergy between CSST and the 3G GW detectors is of great significance in measuring the Hubble constant.

关键词： CSST galaxy survey galaxy catalogs gravitational waves dark sirens the Hubble constant

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Constraints on active and sterile neutrinos in an interacting dark energy cosmology

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Science China(Physics,Mechanics & Astronomy) 2020年第9期63卷 16-29页

作者： Lu Feng Dong-Ze He Hai-Li Li Jing-Fei Zhang Xin Zhang College of Physical Science and Technology Shenyang Normal UniversityShenyang110034China Department of Physics College of SciencesNortheastern UniversityShenyang 110819China Ministry of Education’s Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern UniversityShenyang 110819China Center for High Energy Physics Peking UniversityBeijing 100080China

We investigate the impacts of dark energy on constraining massive(active/sterile)neutrinos in interacting dark energy(IDE)models by using the current *** employ two typical IDE models,the interacting w cold dark matter(IwCDM)model and the interacting holographic dark energy(IHDE)model,to make an *** avoid large-scale instability,we use the parameterized post-Friedmann approach to calculate the cosmological perturbations in the IDE *** cosmological observational data used in this work include the Planck cosmic microwave background(CMB)anisotropies data,the baryon acoustic oscillation data,the type Ia supernovae data,the direct measurement of the Hubble constant,the weak lensing data,the redshift-space distortion data,and the CMB lensing *** find that the dark energy properties could influence the constraint limits of active neutrino mass and sterile neutrino parameters in the IDE *** also find that the dark energy properties could influence the constraints on the coupling strength parameterβ,and a positive coupling constant,β>0,can be detected at the 2.5σstatistical significance for the IHDE+νs model by using the all-data *** addition,we also discuss the"Hubble tension"issue in these *** find that the H0 tension can be effectively relieved by considering massive sterile neutrinos,and in particular in the IHDE+νsmodel the H0 tension can be reduced to be at the 1.28σlevel.

关键词： interacting dark energy neutrino mass active neutrinos sterile neutrinos Hubble tension

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Models of vacuum energy interacting with cold dark matter:Constraints and comparison

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Science China(Physics,Mechanics & Astronomy) 2019年第12期62卷 19-27页

作者： Hai-Li Li Lu Feng Jing-Fei Zhang Xin Zhang Department of Physics College of SciencesNortheastern UniversityShenyang 110819China College of Physical Science and Technology Shenyang Normal UniversityShenyang 110034China Ministry of Education Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern UniversityShenyang 110819China Center for High Energy Physics Peking UniversityBeijing 100080China

In this paper, we investigate the observational constraints on the scenario of vacuum energy interacting with cold dark *** consider eight typical interaction forms in such an interacting vacuum energy scenario. The observational data used in this work to constrain these models include the JLA sample of type Ia supernovae observation, the Planck 2015 distance priors data of cosmic microwave background anisotropies observation, the baryon acoustic oscillations data, and the Hubble constant direct measurement. We find that the current observational data almost equally favor these interacting vacuum energy models. We also find that for all these models of vacuum energy interacting with cold dark matter the case of no interaction is actually well consistent with the current observational data within 1σ range.

关键词： interacting dark energy interacting vacuum energy models cosmological observations cosmological constraints modelcomparison

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A real-time temperature prediction method based on CNN-LSTM with MODE in steelmaking process

A real-time temperature prediction method based on CNN-LSTM ...

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IISE Annual Conference and Expo 2024

作者： Wang, Dan Liu, Chang Tang, Lixin Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Shenyang110819 China Ministry of Education Shenyang110819 China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang110819 China

ISBN: (纸本)9781713877851

Prediction of molten steel quality is a key issue in the converter steelmaking process. Due to high temperature and physical-chemical reaction, it is difficult to predict the temperature of molten steel in real time through mechanism analysis. This is a challenging problem with black box characteristics. Here we propose a Convolutional neural networks (CNN) and long short-term memory (LSTM) networks model based on multi-objective differential evolution algorithm (MODE) for the real-time prediction problem in the steelmaking process. Specifically, the CNN is used to extract feature between multiple variables that affect the temperature of molten steel, and the LSTM is suitable for the time series model based on the irregular trends information. The multi-step output CNN-LSTM method is used to construct the temperature prediction model of molten steel, and a knee solution strategy is applied to MODE, which can balance the model accuracy and generalization ability. The experiments were conducted using real data collected from the converter steelmaking process. The results verify the effectiveness of the proposed model on multiple steel grades and outperform other artificial intelligence methods in multi-task prediction. © IISE Annual Conference and Expo *** rights reserved.

关键词： Convolutional neural networks

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