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Quantifying multiple social relationships based on a multiplex stochastic block model Science Letter
Mincheng Wu, Zhen Li, Cunqi Shao, Shibo He,s18he@zju.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 11, Pages 1458-1462 doi: 10.1631/FITEE.2000617
Keywords： 社交网络；多重网络；随机块模型
The Model on Maximum Entropy of Knowledge Creating Stochastic Process
Chen Xin,He Jinsheng,Dong Liping
Strategic Study of CAE 2004, Volume 6, Issue 12, Pages 43-46
On the basis of the hypothesis that the existing relevant knowledge influences the formation of the new knowledge, this thesis sets up the maximum entropy fundamental model of the stochastic prosess of knowledge innovation by applying the probability & statistics theory, the optimization theory and the maximum entropy principle comprehensively, and puts forward the conditional probability P(y|x) of the new knowledge y∈Y which is restrained by the existing knowledge x∈X. This model posesses such character that the randomness and the causality are unity of opposites
Keywords： maximum entropy knowledge innovation conditional entropy stochastic process
Fully stochastic analysis method for structural time-independent reliability
Du Bin,Xiang Tianyu,Zhao Renda
Strategic Study of CAE 2010, Volume 12, Issue 3, Pages 108-112
In order to effectively evaluate existed bridges' reliability, the effect of bridge service time on bridge reliability was considered. To extend the so-called semi-stochastic process model for specified in the design code in analysis reliability for existing structure, assuming that the structural resistances and the action effects are independent, based on the characteristics of the resistance and action effects variation with time, considering the resistance is an independent increment process and calculating the self-revelation coefficient of resistance, an approximate algorithm of failure probability was developed. And a fully stochastic process model was developed to analysis time-dependent reliability. Through the example,this method is simple and convenient and can supply a basis for structural assessment and service life prediction.
Keywords： existing structure stochastic process time-dependent reliability action effects resistance deterioration
Analysis on the principle-agent model in construction project supply chain
Wu Yuhua,Zhang Qingmin
Strategic Study of CAE 2008, Volume 10, Issue 5, Pages 75-78
General form of principle-agent model in integrated supply chain has been discussed from principle-agent Theories. Based on the above model, construction project supply chain one-period principle-agent model and multi-period construction project supply chain reputation model have been built with the characters of principle and agent of construction project integrated supply chain.
Keywords： principle- agent model incentive compatibility reputation model random walk
Bulk Glassy Alloys: Historical Development and Current Research Review
Akihisa Inoue
Engineering 2015, Volume 1, Issue 2, Pages 185-191 doi: 10.15302/J-ENG-2015038
This paper reviews the development of current research in bulk glassy alloys by focusing on the trigger point for the synthesis of the first bulk glassy alloys by the conventional mold casting method. This review covers the background, discovery, characteristics, and applications of bulk glassy alloys, as well as recent topics regarding them. Applications of bulk glassy alloys have been expanding, particularly for Fe-based bulk glassy alloys, due to their unique properties, high glass-forming ability, and low cost. In the near future, the engineering importance of bulk glassy alloys is expected to increase steadily, and continuous interest in these novel metallic materials for basic science research is anticipated.
Keywords： bulk glassy alloys mold casting metallic materials structural relaxation
Matrix-valued distributed stochastic optimization with constraints
夏子聪,刘洋,卢文联,桂卫华
Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9, Pages 1239-1252 doi: 10.1631/FITEE.2200381
Keywords： Distributed optimization Matrix-valued optimization Stochastic optimization Penalty method Gossip model
Man-machine verification of mouse trajectory based on the random forestmodel Research Articles
Zhen-yi XU, Yu KANG, Yang CAO, Yu-xiao YANG
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 7, Pages 925-929 doi: 10.1631/FITEE.1700442
Identifying code has been widely used in man-machine verification to maintain network security. The challenge in engaging man-machine verification involves the correct classification of man and machine tracks. In this study, we propose a random forest (RF) model for man-machine verification based on the mouse movement trajectory dataset. We also compare the RF model with the baseline models (logistic regression and support vector machine) based on performance metrics such as precision, recall, false positive rates, false negative rates, F-measure, and weighted accuracy. The performance metrics of the RF model exceed those of the baseline models.
Keywords： Man-machine verification Random forest Support vector machine Logistic regression Performance metrics
The Model for Loan Portfolio With Safety-first Criterion
Tang Wansheng,Yan Weizhen,Ning Yufu
Strategic Study of CAE 2007, Volume 9, Issue 11, Pages 137-141
This paper proposes the model for loan portfolio under probability criterion, and designs the hybrid optimization algorithm based on random simulation to solve the model. The algorithm can solve the models with the return rates with any probability distributions, and is not subject to the assumption that the return rates have normal distributions. The feasibility of the algorithm is verified by two examples.
Keywords： loan portfolio safety-first criterion random simulation genetic algorithm(GA) simultaneousperturbation stochastic approximation(SPSA)
Improved Matching Algorithms for Linear Face Class Model
Fu Yun,Zheng Nanning
Strategic Study of CAE 2005, Volume 7, Issue 2, Pages 47-56
An advanced matching technique for linear face class model is proposed, which can solve the problem of detailed controlling and robust iteration for the realistic facial modeling. A new method——Dynamic Gaussian Pyramid Analysis (DGPA), which combines Non-Uniform Sampling (NUS) method and Multi-Resolution Analysis, is presented. Integrating the PS Sampling and the Cluster Random Sampling, the distribution of the sampled points in each level images of the Gaussian pyramid is adjusted dynamically. In coarse-to-fine scheme, the minimization algorithm is used to compute the near global optimal solution that may fit to yield accurate model matching. Dynamic adjusting the boundary of the sampling cluster area and the resampling ratio, the detailed representations are effectively controlled, and the model creation is quite robust. An improved Stochastic Gradient Descent (SGD) algorithm based on the Correlative Disturbance (CD) and Adaptive Learning Rate (ALR) is exploited to accelerate iteration convergence and compute valid model parameters. With the examples of MPI Caucasian Face and AI&R Asian Face databases, experimental results in subjective evaluation and objective evaluation demonstrate the advanced model matching technique.
Keywords： facial modeling model matching stochastic gradient descent non-uniform sampling multiresolution analysis
Ting-ting JIN, Xiao-qiang SHE, Xiao-lan QIU, Bin LEI
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2, Pages 253-264 doi: 10.1631/FITEE.1700462
Classification of intertidal area in synthetic aperture radar (SAR) images is an important yet challenging issue when considering the complicatedly and dramatically changing features of tidal fluctuation. The difficulty of intertidal area classification is compounded because a high proportion of this area is frequently flooded by water, making statistical modeling methods with spatial contextual information often ineffective. Because polarimetric entropy and anisotropy play significant roles in characterizing intertidal areas, in this paper we propose a novel unsupervised contextual classification algorithm. The key point of the method is to combine the generalized extreme value (GEV) statistical model of the polarization features and the Markov random field (MRF) for contextual smoothing. A goodness-of-fit test is added to determine the significance of the components of the statistical model. The final classification results are obtained by effectively combining the results of polarimetric entropy and anisotropy. Experimental results of the polarimetric data obtained by the Chinese Gaofen-3 SAR satellite demonstrate the feasibility and superiority of the proposed classification algorithm.
Keywords： Intertidal classification Polarimetric synthetic aperture radar Finite mixture model Markov random field Generalized extreme value model
A robust optimization model considering probability distribution
Ding Ran,Li Qiqiang,Zhang Yuanpeng
Strategic Study of CAE 2008, Volume 10, Issue 9, Pages 70-73
Robust optimization is a method to process optimization problem under uncertainty. The current robust optimization methods have some deficiencies in application conditions and probability utilization. Based on the chance constraints programming, two kinds of robust constraints according to two different kinds of probability distribution of the stochastic parameters are proposed, and a novel robust optimization model is proposed. The feasible solutions of this model can be controlled to satisfy the robust index. This model can be used in the situations that both sides of the constraints contain stochastic parameters, and can be easily extended to non-liner models. The simulation results illustrate the validity of the model.
Keywords： uncertainty robust optimization stochastic programming chance constraints
Reinforcement design of anchor blocks for external tendons
Hong Hao,Tong Yuqiang ,He Zhiqi,Liu Zhao
Strategic Study of CAE 2013, Volume 15, Issue 8, Pages 95-98
Reinforced blocks are common anchorage forms for external tendons. However, there was no mature design method. Through finite element analysis, the paper revealed that the tensile stress concentration was caused by three typical local actions. On this basis, three equations for calculating resultant forces of these local actions were formulated. Thus a quantitative reinforcement design method of anchor blocks was proposed. Finally, an anchor block of the Fourth Nanjing Yangtze River Bridge was presented as a design example to demonstrate the effectiveness and convenience of the proposed method.
Keywords： anchor block external prestressing reinforcement design bursting force cantilever action tie-back
An Enhanced Physically Based Scour Model for Considering Jet Air Entrainment
Rafael Duarte,António Pinheiro,Anton J. Schleiss
Engineering 2016, Volume 2, Issue 3, Pages 294-301 doi: 10.1016/J.ENG.2016.03.003
Based on systematic experiments on the influence of air entrainment on rock block stability in plunge pools impacted by high-velocity jets, this study presents adaptations of a physically based scour model. The modifications regarding jet aeration are implemented in the Comprehensive Scour Model (CSM), allowing it to reproduce the physical-mechanical processes involved in scour formation concerning the three phases; namely, water, rock, and air. The enhanced method considers the reduction of momentum of an aerated jet as well as the decrease of energy dissipation in the jet diffusive shear layer, both resulting from the entrainment of air bubbles. Block ejection from the rock mass depends on a combination of the aerated time-averaged pressure coefficient and the modified maximum dynamic impulsion coefficient, which was found to be a constant value of 0.2 for high-velocity jets in deep pools. The modified model is applied to the case of the observed scour hole at the Kariba Dam, with good agreement.
Keywords： Air entrainment Uplift Rock scour Dam safety High-velocity jets Block stability Scour assessment
Wei Liang, Jiancheng Li, Xinyu Xu, Shengjun Zhang, Yongqi Zhao
Engineering 2020, Volume 6, Issue 8, Pages 860-878 doi: 10.1016/j.eng.2020.05.008
This paper focuses on estimating a new high-resolution Earth’s gravity field model named SGG-UGM-2 from satellite gravimetry, satellite altimetry, and Earth Gravitational Model 2008 (EGM2008)-derived gravity data based on the theory of the ellipsoidal harmonic analysis and coefficient transformation (EHA-CT). We first derive the related formulas of the EHA-CT method, which is used for computing the spherical harmonic coefficients from grid area-mean and point gravity anomalies on the ellipsoid. The derived formulas are successfully evaluated based on numerical experiments. Then, based on the derived least-squares formulas of the EHA-CT method, we develop the new model SGG-UGM-2 up to degree 2190 and order 2159 by combining the observations of the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE), the normal equation of the Gravity Recovery and Climate Experiment (GRACE), marine gravity data derived from satellite altimetry data, and EGM2008-derived continental gravity data. The coefficients of degrees 251–2159 are estimated by solving the block-diagonal form normal equations of surface gravity anomalies (including the marine gravity data). The coefficients of degrees 2–250 are determined by combining the normal equations of satellite observations and surface gravity anomalies. The variance component estimation technique is used to estimate the relative weights of different observations. Finally, global positioning system (GPS)/leveling data in the mainland of China and the United States are used to validate SGG-UGM-2 together with other models, such as European improved gravity model of the earth by new techniques (EIGEN)-6C4, GECO, EGM2008, and SGG-UGM-1 (the predecessor of SGG-UGM-2). Compared to other models, the model SGG-UGM-2 shows a promising performance in the GPS/leveling validation. All GOCE-related models have similar performances both in the mainland of China and the United States, and better performances than that of EGM2008 in the mainland of China. Due to the contribution of GRACE data and the new marine gravity anomalies, SGG-UGM-2 is slightly better than SGG-UGM-1 both in the mainland of China and the United States.
Keywords： Gravity field model GOCE GRACE Satellite altimetry Block-diagonal least-squares
Data-Driven Model Falsification and Uncertainty Quantification for Fractured Reservoirs Article
Junling Fang, Bin Gong, Jef Caers
Engineering 2022, Volume 18, Issue 11, Pages 116-128 doi: 10.1016/j.eng.2022.04.015
Many properties of natural fractures are uncertain, such as their spatial distribution, petrophysical properties, and fluid flow performance. Bayesian theorem provides a framework to quantify the uncertainty in geological modeling and flow simulation, and hence to support reservoir performance predictions. The application of Bayesian methods to fractured reservoirs has mostly been limited to synthetic cases. In field applications, however, one of the main problems is that the Bayesian prior is falsified, because it fails to predict past reservoir production data. In this paper, we show how a global sensitivity analysis (GSA) can be used to identify why the prior is falsified. We then employ an approximate Bayesian computation (ABC) method combined with a tree-based surrogate model to match the production history. We apply these two approaches to a complex fractured oil and gas reservoir where all uncertainties are jointly considered, including the petrophysical properties, rock physics properties, fluid properties, discrete fracture parameters, and dynamics of pressure and transmissibility. We successfully identify several reasons for the falsification. The results show that the methods we propose are effective in quantifying uncertainty in the modeling and flow simulation of a fractured reservoir. The uncertainties of key parameters, such as fracture aperture and fault conductivity, are reduced.
Keywords： Bayesian evidential learning Falsification Fractured reservoir Random forest Approximate Bayesian computation
Title Author Date Type Operation
Quantifying multiple social relationships based on a multiplex stochastic block model
Mincheng Wu, Zhen Li, Cunqi Shao, Shibo He,s18he@zju.edu.cn
Journal Article
The Model on Maximum Entropy of Knowledge Creating Stochastic Process
Chen Xin,He Jinsheng,Dong Liping
Journal Article
Fully stochastic analysis method for structural time-independent reliability
Du Bin,Xiang Tianyu,Zhao Renda
Journal Article
Analysis on the principle-agent model in construction project supply chain
Wu Yuhua,Zhang Qingmin
Journal Article
Man-machine verification of mouse trajectory based on the random forestmodel
Zhen-yi XU, Yu KANG, Yang CAO, Yu-xiao YANG
Journal Article
The Model for Loan Portfolio With Safety-first Criterion
Tang Wansheng,Yan Weizhen,Ning Yufu
Journal Article
Intertidal area classification with generalized extreme value distribution and Markov random field in quad-polarimetric synthetic aperture radar imagery
Ting-ting JIN, Xiao-qiang SHE, Xiao-lan QIU, Bin LEI
Journal Article
A robust optimization model considering probability distribution
Ding Ran,Li Qiqiang,Zhang Yuanpeng
Journal Article
Reinforcement design of anchor blocks for external tendons
Hong Hao,Tong Yuqiang ,He Zhiqi,Liu Zhao
Journal Article
An Enhanced Physically Based Scour Model for Considering Jet Air Entrainment
Rafael Duarte,António Pinheiro,Anton J. Schleiss
Journal Article
A High-Resolution Earth’s Gravity Field Model SGG-UGM-2 from GOCE, GRACE, Satellite Altimetry, and EGM2008
Wei Liang, Jiancheng Li, Xinyu Xu, Shengjun Zhang, Yongqi Zhao
Journal Article
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