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Adaptive sampling immune algorithm solving joint chance-constrained programming

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控制理论与应用（英文版） 2013年第2期11卷 237-246页

作者： Zhuhong ZHANG Lei WANG Min LIAO Institute of system Science & information Technology College of Science Guizhou University

This work investigates one immune optimization algorithm in uncertain environments, solving linear or nonlinear joint chance-constrained programming with a general distribution of the random vector. In this algorithm, an a priori lower bound estimate is developed to deal with one joint chance constraint, while the scheme of adaptive sampling is designed to make empirically better antibodies in the current population acquire larger sample sizes in terms of our sample-allocation rule. Relying upon several simplified immune metaphors in the immune system, we design two immune operators of dynamic proliferation and adaptive mutation. The first picks up those diverse antibodies to achieve proliferation according to a dynamical suppression radius index, which can ensure empirically potential antibodies more clones, and reduce noisy influence to the optimized quality, and the second is a module of genetic diversity, which exploits those valuable regions and finds those diverse and excellent antibodies. Theoretically, the proposed approach is demonstrated to be convergent. Experimentally, the statistical results show that the approach can obtain satisfactory performances including the optimized quality, noisy suppression and efficiency.

关键词： Joint chance-constrained programming Immune optimization Adaptive sampling Reliability domi-nance Noisy attenuation

Machine Learning-based Stable P2P IPTV Overlay

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Computers, Materials & Continua 2022年第6期71卷 5381-5397页

作者： Muhammad Javid Iqbal Ihsan Ullah Muhammad Ali Atiq Ahmed Waheed Noor Abdul Basit directorate of information Technology Sardar Bahadur Khan Women’s UniversityQuettaPakistan Department of Computer Science and information Technology University of BalochistanQuettaPakistan

Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service *** Internet was not designed for such services during its inception,such a service poses some serious challenges including cost and ***-to-Peer(P2P)Internet Protocol Television(IPTV)is an application-level distributed paradigm to offer live video *** terms of ease of deployment,it has emerged as a serious alternative to client server,Content Delivery Network(CDN)and IP multicast ***,P2P approach has struggled to provide the desired streaming quality due to a number of *** of peers in a network is one of themajor issues among *** of the existing approaches address this issue through older-stable *** paper first extensively investigates the older-stable principle to observe its validity in different *** is observed that the older-stable principle does not hold in several of ***,it utilizes machine learning approach to predict the stability of *** work evaluates the accuracy of severalmachine learning algorithms over the prediction of stability,where the Gradient Boosting Regressor(GBR)out-performs other ***,this work presents a proof-of-concept simulation to compare the effectiveness of older-stable rule and machine learning-based predictions for the stabilization of the *** results indicate that machine learning-based stability estimation significantly improves the system.

关键词： P2P IPTV live video streaming user behavior overlay networks stable peers machine learning

Source enumeration method by combining diagonal loading and constructing second-order statistics

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The Journal of China Universities of Posts and Telecommunications 2023年第1期30卷 47-55页

作者： Wang Chuanchuan Zeng Yonghu Wang Liandong Li Zhipeng State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and information system Luoyang 471003China

A source enumeration method based on diagonal loading of eigenvalues and constructing second-order statistics is proposed,for the case that the antenna array observed signals are overlapped with spatial colored noise,and the number of antennas compared with the number of snapshots meet the requirement of general asymptotic ***,the sample covariance matrix of the observed signals is obtained,the eigenvalues of the sample covariance matrix can be acquired by eigenvalue decomposition,and the eigenvalues are diagonally loaded,and a new formula for calculating the diagonal loading is *** on the diagonal loaded eigenvalues,the difference values are calculated for the adjacent eigenvalues after diagonal loading,and the statistical variance of the difference values is *** this basis,the second-order statistics of the difference values are constructed,and when the second-order statistics are minimized,the corresponding number of sources is *** proposed method has wide applicability,which is suitable for both general asymptotic regime and classical asymptotic system,and is suitable for both white Gaussian noise environment and colored noise *** method makes up for the lack of source enumeration methods in the case of general asymptotic system and colored noise.

关键词： source enumeration general asymptotic regime colored noise diagonal loading second-order statistics

FORECASTING THE MJO INDEX BASED ON SSA-AR

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Journal of Tropical Meteorology 2011年第4期17卷 317-325页

作者：江志红张勤朱红蕊吴立广 Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science & Technology Wyle information system CPC/NOAAUSA

Experiments of forecasting daily bi-variate index of the tropical atmospheric Madden-Julian Oscillation (MJO) are performed in the context of adaptive filtering prediction models by combining the singular spectrum analysis (SSA) with the autoregressive (AR) *** MJO index,a pair of empirical orthogonal function (EOF) time series,called RMM1 and RMM2,predicts by the combined statistical SSA and AR models:firstly,according to the index of historic observation decomposed by SSA and then reconstructed by selecting the first several components based on prominent variance contributions;after that,established an AR prediction model from the composite (scheme A) or built the forecast models for each of these selected reconstructed components,separately (Scheme B).Several experimental MJO index forecasts are performed based on the *** results show that both models have useful skills of the MJO index forecast beyond two *** some cases,the correlation coefficient between the observed and predicted index series stays above 0.5 in 20 leading *** SSA-AR model,based on the reconstructed composite series,has better performance on MJO forecast than the AR model,especially for the leading time longer than 5 ***,if we build a real-time forecast system by the SSA-AR model,it might provide an applicable tool for the operational prediction of the MJO index.

关键词： Madden-Julian Oscillation singular spectrum analysis autoregressive model

Enhanced piecewise regression based on deterministic annealing

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Science in China(Series F) 2008年第8期51卷 1025-1038页

作者： ZHANG JiangShe YANG YuQian CHEN XiaoWen ZHOU ChengHu Institute for information and system Sciences Faculty of Sciences Xi'an Jiaotong University Xi'an 710049 China State Key Laboratory of Resources & Environmental information system Institute of Geography Chinese Academy of Sciences Beijing 100101 China

Regression is one of the important problems in statistical learning theory. This paper proves the global convergence of the piecewise regression algorithm based on deterministic annealing and continuity of global minimum of free energy w.r.t temperature, and derives a new simplified formula to compute the initial critical temperature. A new enhanced plecewise regression algorithm by using ＂migration of prototypes＂ is proposed to eliminate ＂empty cell＂ in the annealing process. Numerical experiments on several benchmark datasets show that the new algorithm can remove redundancy and improve generalization of the piecewise regression model.

关键词： statistical regression piecewise regression deterministic annealing generalization

Phosphorus speciation in sediments of Lake Hongfeng, China

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Chinese Journal of Oceanology and Limnology 2011年第1期29卷 53-62页

作者：蒋翠红胡继伟黄先飞李存雄邓家军张杰刘峰 Guizhou Provincial Key Laboratory for information system of Mountainous Areas and Protection of Ecological Environment Guizhou Normal University

This study was conducted to evaluate the distribution characteristics of phosphorus and its species in 14 sediments samples collected from Lake Hongfeng based on sequential extraction. Lake Hongfeng, a major drinking-water source for Guiyang City in southwestern China, is one of the largest artificial reservoirs located in a typical karstic area of the Yunnan-Guizhou Plateau. The results of this study indicate that the average percentages of DP, Al-P, Fe-P, Ca-P and OP in the lake sediments were 0.52, 6.59, 6.09, 42.85 and 40.27, respectively. The concentrations of organic phosphorus (OP) were lower than those of inorganic phosphorus (IP), which consisted mainly of calcium-bound phosphorus (Ca-P). The high concentrations of Ca-P may temporarily control the release of phosphorus from the sediments because it is a relatively stable, inert, and non-bioavailable phosphorus fraction. However, a large number of phosphate solubilizing bacteria can transform insoluble phosphate into bioavailable forms. Moreover, the concentrations of total phosphorus (TP) in the lake sediments were high; thus, the potential for the release of phosphorus from the sediments to the water column and phosphorus bioavailability were still significant. Further statistical analyses of the results revealed significant correlations between phosphorus species in sediments from the lake with two extractable principal component species (PCs) and five selectable cluster levels allowing interpretation of possible origins of phosphorus loading and the release of phosphorus. Furthermore, available remediation measures were briefly assessed for the lake with consideration of its distinctive environmental features.

关键词： Eutrophication karstic environment lake sediments phosphorus speciation sequential extraction procedure

Knowledge-based neural network SPICE modeling for MOSFETs and its application on 2D material field-effect transistors

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Science China(information Sciences) 2023年第2期66卷 227-236页

作者： Guodong QI Xinyu CHEN Guangxi HU Peng ZHOU Wenzhong BAO Ye LU State Key Laboratory of ASIC and system School of Information Science and TechnologyFudan University State Key Laboratory of ASIC and system School of Microelectronics Fudan University Zhangjiang Fudan International Innovation Center Fudan University

As the traditional scaling of silicon metal-oxide-semiconductor field-effect transistors(MOSFETs) reaches its physical limit, research efforts on novel semiconductor devices are increasingly desired. To enable the joint optimization of early-stage circuit design and process of novel devices, the rapid creation of an accurate compact model of these devices with the capability to cover process variations is required. In this work, a knowledge-based neural network(KNN) modeling method is proposed. This method separates the geometrical variables from the other input variables of the device, where the geometrical variables are modeled with physics-based analytical equations, while the remaining part is modeled by an artificial neural network. The KNN model takes advantage of the automated numerical fitting capability of the neural network and the geometrical scalability from device physics. The created KNN model is first validated with silicon MOSFET data from the industry standard BSIM6 and shows more than 20% accuracy improvement as compared with the traditional neural network model. Furthermore, MoS2field-effect transistors and circuits,such as ring oscillators, standard cells, and logic functional circuits, are experimentally fabricated for model verification. The results show that the KNN model is capable of predicting the electrical characteristics of devices beyond the measurement geometry and facilitates the accurate simulations of statistical circuits with respect to experimental data. This work paves the way for future circuit designs and simulations of novel semiconductor devices.

关键词： knowledge-based neural network MOSFET 2D material FETs Monte Carlo simulations circuit benchmark

Comparative simulation study of effects of eddy-topography interaction in the East/Japan Sea deep circulation

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Acta Oceanologica Sinica 2015年第7期34卷 1-18页

作者： CHOI Youngjin Center for Earth information Science and Technology Japan Agency for Marine-Earth Science and Technology Geo system Research Corporation

In this study the structure and seasonal variations of deep mean circulation in the East/lapan Sea （E/S） were numerically simulated using a mid-resolution ocean general circulation model with two different parameterizations for the eddy-topography interaction （ETI）. The strong deep mean circulations observed in the EIS are well reproduced when using the ETI parameterizations. The seasonal variability in the EIS deep layer is shown by using ETI parameterization based on the potential vorticity approach, while it is not shown in the statistical dynamical parameterization. The driving mechanism of the strong deep mean currents in the E/S are discussed by investigating the effects of model grids and parameterizations. The deep mean circulation is more closely related to the baroclinic process and potential vorticity than it is to the wind driven circulation.

关键词： East/Iapan Sea deep mean current seasonal variability ocean general circulation model eddy- topography interaction

Byte-Level Function-Associated Method for Malware Detection

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Computer systems Science & Engineering 2023年第7期46卷 719-734页

作者： Jingwei Hao Senlin Luo Limin Pan information system&Security and Countermeasures Experiments Center Beijing Institute of TechnologyBeijing100081China

The byte stream is widely used in malware detection due to its independence of reverse ***,existing methods based on the byte stream implement an indiscriminate feature extraction strategy,which ignores the byte function difference in different segments and fails to achieve targeted feature extraction for various byte semantic representation modes,resulting in byte semantic *** address this issue,an enhanced adversarial byte function associated method for malware backdoor attack is proposed in this paper by categorizing various function bytes into three functions involving structure,code,and *** Minhash algorithm,grayscale mapping,and state transition probability statistics are then used to capture byte semantics from the perspectives of text signature,spatial structure,and statistical aspects,respectively,to increase the accuracy of byte semantic ***,the three-channel malware feature image is constructed based on different function byte semantics,and a convolutional neural network is applied for *** on multiple data sets from 2018 to 2021 show that the method can effectively combine byte functions to achieve targeted feature extraction,avoid byte semantic confusion,and improve the accuracy of malware detection.

关键词： Byte function malware backdoor attack semantic representation model visualization