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基于Gaussian、ECOSAR模型的紫外/次氯酸体系降解含卤阻燃剂的产物预测与毒性评估

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环境化学 2024年第1期43卷 82-91页

作者：卢志磊范勇杰陈洁洁杨婧吴春山孙启元福建师范大学环境科学与工程学院福州350007 福建省污染控制与资源循环利用重点实验室福州350007 福建省高校城市废物资源化技术与管理工程研究中心福州350007

含卤阻燃剂广泛应用于各类电子产品的生产,难降解且具有生物毒性.在生产和使用过程中,部分含卤阻燃剂会残留在水体并排放到水环境造成累积污染,威胁水环境安全,亟需探寻有效的降解去毒方法.本研究通过Gaussian与ECOSAR模型预测了四氯双... 详细信息

含卤阻燃剂广泛应用于各类电子产品的生产,难降解且具有生物毒性.在生产和使用过程中,部分含卤阻燃剂会残留在水体并排放到水环境造成累积污染,威胁水环境安全,亟需探寻有效的降解去毒方法.本研究通过Gaussian与ECOSAR模型预测了四氯双酚A(TCBPA)、四溴双酚A(TBBPA)、十溴二苯乙烷(DBDPE)等3种典型含卤阻燃剂在紫外/次氯酸(UV/Cl)体系中的光催氧化降解路径与产物毒性.结果表明,UV/Cl体系中的含氯自由基(RCS)与羟基自由基(·OH)易攻击阻燃剂分子结构上键能较低、Fukui指数较高的位点,促使C—Cl键、C—Br键、C—C键等因为受到攻击而断裂,进而降解阻燃剂.同时,利用ECOSAR模型评估发现降解产物的急性毒性LC_(50)-96 h均低于100 mg·L^(-1),佐证了UV/Cl体系对含卤阻燃剂降解的有效性,并降低其环境危害.因此,采用Gaussian计算、ECOSAR模型相结合的分析方法,能够更加便捷地预测阻燃剂降解路径与产物毒性特征,为深入揭示UV/Cl体系光催氧化降解含卤阻燃剂机理提供新思路.

关键词： Gaussian Fukui指数 ECOSAR模型含卤阻燃剂紫外/次氯酸生物毒性

Long-term Traffic Volume Prediction Based on K-means Gaussian Interval Type-2 Fuzzy Sets

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IEEE/CAA Journal of Automatica Sinica 2019年第6期6卷 1344-1351页

作者： Runmei Li Yinfeng Huang Jian Wang the School of Electronic and Information Engineer ing Beijing Jiaotong University

This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this paper to get 5 minutes traffic volume variation as input data for the Gaussian interval type-2 fuzzy sets which can reflect the distribution of historical traffic volume in one statistical period. Moreover, the cluster with the largest collection of data obtained by K-means clustering method is calculated to get the key parameters of type-2 fuzzy sets, mean and standard deviation of the Gaussian membership function.Using the range of data as the input of Gaussian interval type-2 fuzzy sets leads to the range of traffic volume forecasting output with the ability of describing the possible range of the traffic volume as well as the traffic volume prediction data with high accuracy. The simulation results show that the average relative error is reduced to 8% based on the combined K-means Gaussian interval type-2 fuzzy sets forecasting method. The fluctuation range in terms of an upper and a lower forecasting traffic volume completely envelopes the actual traffic volume and reproduces the fluctuation range of traffic flow.

关键词： Gaussian interval type-2 fuzzy sets K-means clustering long-term prediction traffic volume traffic volume fluctuation range

Experimental Gaussian Boson sampling

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Science Bulletin 2019年第8期64卷 511-515页

作者： Han-Sen Zhong Li-Chao Peng Yuan Li Yi Hu Wei Li Jian Qin Dian Wu Weijun Zhang Hao Li Lu Zhang Zhen Wang Lixing You Xiao Jiang Li Li Nai-Le Liu Jonathan P.Dowling Chao-Yang Lu Jian-Wei Pan Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of China CAS Centre for Excellence and Synergetic Innovation Centre in Quantum Information and Quantum Physics University of Science and Technology of China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology (SIMIT) Chinese Academy of Sciences Hearne Institute for Theoretical Physics and Department of Physics and Astronomy Louisiana State University NYU-ECNU Institute of Physics at NYU Shanghai

Gaussian Boson sampling(GBS) provides a highly efficient approach to make use of squeezed states from parametric down-conversion to solve a classically hard-to-solve sampling problem. The GBS protocol not only significantly enhances the photon generation probability, compared to standard Boson sampling with single photon Fock states, but also links to potential applications such as dense subgraph problems and molecular vibronic spectra. Here, we report the first experimental demonstration of GBS using squeezed-state sources with simultaneously high photon indistinguishability and collection efficiency.We implement and validate 3-, 4- and 5-photon GBS with high sampling rates of 832, 163 and 23 kHz,respectively, which is more than 4.4, 12.0, and 29.5 times faster than the previous experiments.Further, we observe a quantum speed-up on a NP-hard optimization problem when comparing with simulated thermal sampler and uniform sampler.

关键词： Quantum information Boson sampling Gaussian Boson sampling Squeezed state Quantum advantage Quantum approximate optimization

Gaussian processes non-linear inverse reinforcement learning

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IET Cyber-Systems and Robotics 2021年第2期3卷 150-163页

作者： Qifeng Qiao Xiaomin Lin Netflix Inc.Los GatosCaliforniaUSA Massachusetts Mutual Life Insurance Co BostonMassachusettsUSA

The authors analyse a Bayesian framework for posing and solving inverse reinforcement learning(IRL)problems that arise in decision-making and optimisation settings.The authors propose a non-parametric Bayesian model using Gaussian process(GP)and preference graphs,which offer an effective and computationally efficient method for illposed IRL problems in large or infinite state space.This approach only requires a finite number of demonstrations that is much less than the amount required for approximating the feature expectation or value functions in previous IRL methods.The proposed learning framework is expressive as it relies on a Bayesian structure in which assumptions are explicit and changeable.It is also robust in that it formalises on convex optimisation,which retains the promise of computationally manageable implementations for practical problems.To deal with more realistic IRL problems where the dynamics is also unknown,the GP model can be easily combined with the method to learn the dynamics at the same time.Experimental results prove the superiority of the authors method to current prevailing IRL algorithms with fewer numbers of demonstrations in both discrete and continuous state space.

关键词： space. inverse Gaussian

Using a Gaussian mathematical model to define eruptive stages of young volcanic rocks in Tengchong based on laser 40Ar/39Ar dating

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Science China Earth Sciences 2020年第5期63卷 662-673页

作者： Xinwei ZHAO Jing ZHOU Fang MA Jianqing JI Alan DEINO School of Earth Sciences and Resources China University of GeosciencesBeijing 100083China Key Laboratory of Orogenic Belts and Crustal Evolution School of Earth and Space SciencesPeking UniversityBeijing 100871China Berkeley Geochronology Center Berkeley CA94709USA

Reconstruction of Quaternary environments,late Cenozoic geodynamics and evaluation of volcanic hazards,all depend on the precise delineation of eruptive stages.In recent years,laser 40Ar/39Ar dating methods have been widely used for dating young volcanic rocks,given their stable automated testing process,very low background level and high sensitivity,which meet the requirements for precise dating of young samples.This paper applied high-precision laser 40Ar/39Ar dating to the main volcanic units in the Tengchong area and obtained ages in the range of 0.025–5.1 Ma using conventional data processing methods.However,conventional dating highlighted issues related to very low radiogenic 40Ar content,accidental errors and poor data stability,which led to huge age deviations.Moreover,lacking a unified timescale,conventional methods were unable to strictly define the stages of the Tengchong volcanic eruptions,leading to ongoing controversy.In this study,we applied a Gaussian mathematical model to deal with all 378 original ages from 13 samples.An apparent age-probability diagram,consisting of three independent waveforms,have been obtained.The corresponding isochron ages of these three waveforms suggest there were three volcanic eruptive stages,namely during the Pliocene(3.78±0.04 Ma),early Middle Pleistocene(0.63±0.03 Ma)and late Middle Pleistocene to early Late Pleistocene(0.139±0.005 Ma).These results accurately define eruptive stages in the Tengchong area.

关键词： Laser 40Ar/39Ar dating Gaussian mathematical model Eruptive stages Apparent age-probability diagram Age deviations Isochron age

Convergence Rate Analysis of Gaussian Belief Propagation for Markov Networks

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 668-673页

作者： Zhaorong Zhang Minyue Fu School of Electrical Engineering and Computer Science The University of Newcastle.University DriveNSW 2308Australia IEEE School of Automation Guangdong University of Technologyand Guangdong Key Laboratory of Intelligent Decision and Cooperative ControlGuangzhou 510006China

Gaussian belief propagation algorithm(GaBP) is one of the most important distributed algorithms in signal processing and statistical learning involving Markov networks. It is well known that the algorithm correctly computes marginal density functions from a high dimensional joint density function over a Markov network in a finite number of iterations when the underlying Gaussian graph is acyclic. It is also known more recently that the algorithm produces correct marginal means asymptotically for cyclic Gaussian graphs under the condition of walk summability(or generalised diagonal dominance). This paper extends this convergence result further by showing that the convergence is exponential under the generalised diagonal dominance condition,and provides a simple bound for the convergence rate. Our results are derived by combining the known walk summability approach for asymptotic convergence analysis with the control systems approach for stability analysis.

关键词： Belief propagation distributed algorithm distributed estimation Gaussian belief propagation Markov networks

Oversampling Method Based on Gaussian Distribution and K-Means Clustering

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Computers, Materials & Continua 2021年第10期69卷 451-469页

作者： Masoud Muhammed Hassan Adel Sabry Eesa Ahmed Jameel Mohammed Wahab Kh.Arabo Department of Computer Science University of ZakhoDuhok42001Kurdistan RegionIraq Department of Information Technology Duhok Polytechnic UniversityDuhok42001Kurdistan RegionIraq

Learning from imbalanced data is one of the greatest challenging problems in binary classification,and this problem has gained more importance in recent years.When the class distribution is imbalanced,classical machine learning algorithms tend to move strongly towards the majority class and disregard the minority.Therefore,the accuracy may be high,but the model cannot recognize data instances in the minority class to classify them,leading to many misclassifications.Different methods have been proposed in the literature to handle the imbalance problem,but most are complicated and tend to simulate unnecessary noise.In this paper,we propose a simple oversampling method based on Multivariate Gaussian distribution and K-means clustering,called GK-Means.The new method aims to avoid generating noise and control imbalances between and within classes.Various experiments have been carried out with six classifiers and four oversampling methods.Experimental results on different imbalanced datasets show that the proposed GK-Means outperforms other oversampling methods and improves classification performance as measured by F1-score and Accuracy.

关键词： Class imbalance oversampling Gaussian multivariate distribution k-means clustering

基于高维Gaussian Copula函数的区域农田灌溉需水分析

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水利学报 2018年第3期49卷 323-331页

作者：杜奕良涂新军杜晓霞陈晓宏林凯荣吴海鸥中山大学水资源与环境系广东广州510275 广东省华南地区水安全调控工程技术研究中心广东广州510275

以广东省农田灌溉需水为例,构建了分区降水的8维联合分布模型,提出了给定全省降水频率的全省及分区农田灌溉需水分析思路,采用同频、典型年和最大权函数3种方法对区域需水、分区降水频率及需水进行了分析计算和对比。结果显示:Gaussian ... 详细信息

以广东省农田灌溉需水为例,构建了分区降水的8维联合分布模型,提出了给定全省降水频率的全省及分区农田灌溉需水分析思路,采用同频、典型年和最大权函数3种方法对区域需水、分区降水频率及需水进行了分析计算和对比。结果显示:Gaussian Copula函数能够很好地模拟广东省8个分区年降水联合分布,单变量最优分布主要为广义极值分布和广义正态分布。3种方法之间的全省农田灌溉需水相差甚小,但是各分区需水差别相对较大。典型年法推求的分区降水频率差异最明显,最大权函数法推求的大部分分区降水频率处于同频位置附近,其中分区Ⅷ的降水频率在特枯和特丰时明显偏离同频位置,而且其置信区间范围明显大于其它分区,表明分区Ⅷ不确定性更大。由于基于高维Copula函数联合分布模拟既考虑了分区降水的独立分布,又考虑了它们之间的相依性,而且能够给出分区需水的置信范围,因此认为最大权函数法推求区域农田灌溉需水更为合理。

关键词：灌溉需水降水频率高维联合分布 Gaussian Copula函数典型年法最大权函数

Silicon photonic Bessel-Gaussian beam generation unlocks new possibilities for long-range sensing

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Light(Science & Applications) 2023年第7期12卷 1178-1179页

作者： Sangsik Kim School of Electrical Engineering Korea Advanced Institute of Science and TechnologyDaejeon 34141Republic of Korea

Concentrically distributed silicon photonic grating arrays generate long-range Besse-Gaussian beams,enabling rotational and range measurements over obstacles.This compact and mass-producible chip unlocks new potential... 详细信息

关键词： Gaussian Bessel beam