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A novel hybrid estimation of distribution algorithm for solving hybrid flowshop scheduling problem with unrelated parallel machine 被引量:9
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作者 孙泽文 顾幸生 《Journal of Central South University》 SCIE EI CAS CSCD 2017年第8期1779-1788,共10页
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor... The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms. 展开更多
关键词 hybrid estimation of distribution algorithm teaching learning based optimization strategy hybrid flow shop unrelated parallel machine scheduling
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Estimation Method of State-of-Charge For Lithium-ion Battery Used in Hybrid Electric Vehicles Based on Variable Structure Extended Kalman Filter 被引量:18
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作者 SUN Yong MA Zilin +2 位作者 TANG Gongyou CHEN Zheng ZHANG Nong 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2016年第4期717-726,共10页
Since the main power source of hybrid electric vehicle(HEV) is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge(SOC) estimation has attracted great attention ... Since the main power source of hybrid electric vehicle(HEV) is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge(SOC) estimation has attracted great attention in the area of HEV.However,the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected.A variable structure extended kalman filter(VSEKF)-based estimation method,which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition,is presented.First,the general lower-order battery equivalent circuit model(GLM),which includes column accumulation model,open circuit voltage model and the SOC output model,is established,and the off-line and online model parameters are calculated with hybrid pulse power characteristics(HPPC) test data.Next,a VSEKF estimation method of SOC,which integrates the ampere-hour(Ah) integration method and the extended Kalman filter(EKF) method,is executed with different adaptive weighting coefficients,which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes.According to the experimental analysis,the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV.The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method.In Summary,the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system,which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method.The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions. 展开更多
关键词 state of charge estimation hybrid electric vehicle general lower-order model variable structure EKF
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E-Bayesian estimation for competing risk model under progressively hybrid censoring 被引量:3
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作者 Min Wu Yimin Shi Yan Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第4期936-944,共9页
This paper considers the Bayesian and expected Bayesian(E-Bayesian) estimations of the parameter and reliability function for competing risk model from Gompertz distribution under Type-I progressively hybrid censori... This paper considers the Bayesian and expected Bayesian(E-Bayesian) estimations of the parameter and reliability function for competing risk model from Gompertz distribution under Type-I progressively hybrid censoring scheme(PHCS). The estimations are obtained based on Gamma conjugate prior for the parameter under squared error(SE) and Linex loss functions. The simulation results are provided for the comparison purpose and one data set is analyzed. 展开更多
关键词 Bayesian estimation expected Bayesian(E-Bayesian) estimation Gompertz distribution Type-I progressively hybrid censoring
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A NEW HYBRID FORECASTING ALGORITHM AND ITS APPLICATION IN ECONOMIC ANALYSIS
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作者 Li Shejiao Lv Bing Wen Chuanbo 《Journal of Electronics(China)》 2007年第5期705-709,共5页
There exists a great deal of periodic non-stationary processes in natural,social and eco- nomical phenomenon.It is very important to realize the dynamic analysis and real-time forecast within a period.In this letter,a... There exists a great deal of periodic non-stationary processes in natural,social and eco- nomical phenomenon.It is very important to realize the dynamic analysis and real-time forecast within a period.In this letter,a wavelet-Kalman hybrid estimation and forecasting algorithm based on step-by-step filtering with the real-time and recursion property is put forward.It combines the advantages of Kalman filter and wavelet transform.Utilizing the information provided by multi- sensor effectively,this algorithm can realize not only real-time tracking and dynamic multi-step fore- casting within a period,but also the dynamic forecasting between periods,and it has a great value to the system decision-making.Simulation results show that this algorithm is valuable. 展开更多
关键词 Wavelet-Kalman hybrid estimation and forecasting MULTI-SENSOR
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Local Hybrid Linear State Estimation for Electric Power Systems Using Stream Processing
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作者 Kang Sun Manyun Huang +2 位作者 Zhinong Wei Yuzhang Lin Guoqiang Sun 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2024年第3期1259-1268,共10页
The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note tha... The increasing penetration of renewable energy resources with highly fluctuating outputs has placed increasing concern on the accuracy and timeliness of electric power system state estimation(SE).Meanwhile,we note that only a fraction of system states fluctuate at the millisecond level and require to be updated.As such,refreshing only those states with significant variation would enhance the computational efficiency of SE and make fast-continuous update of states possible.However,this is difficult to achieve with conventional SE methods,which generally refresh states of the entire system every 4–5 s.In this context,we propose a local hybrid linear SE framework using stream processing,in which synchronized measurements received from phasor measurement units(PMUs),and trigger/timingmode measurements received from remote terminal units(RTUs)are used to update the associated local states.Moreover,the measurement update process efficiency and timeliness are enhanced by proposing a trigger measurement-based fast dynamic partitioning algorithm for determining the areas of the system with states requiring recalculation.In particular,non-iterative hybrid linear formulations with both RTUs and PMUs are employed to solve the local SE problem.The timeliness,accuracy,and computational efficiency of the proposed method are demonstrated by extensive simulations based on IEEE 118-,300-,and 2383-bus systems. 展开更多
关键词 Fast dynamic partitioning local hybrid linear state estimation phasor measurement units stream processing TIMELINESS trigger/timing-mode measurements
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Intent Inference Based Trajectory Prediction and Smooth for UAS in Low-Altitude Airspace with Geofence 被引量:3
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作者 Qixi Fu Xiaolong Liang +1 位作者 Jiaqiang Zhang Xiangyu Fan 《Computers, Materials & Continua》 SCIE EI 2020年第4期417-444,共28页
In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System(UAS)in Unmanned Aircraft System Traffic Management(UTM),an Intent Based Trajectory Prediction and Smooth Based on ... In order to meet the higher accuracy requirement of trajectory prediction for Unmanned Aircraft System(UAS)in Unmanned Aircraft System Traffic Management(UTM),an Intent Based Trajectory Prediction and Smooth Based on Constrained State-dependent-transition Hybrid Estimation(CSDTHE-IBTPS)algorithm is proposed.Firstly,an intent inference method of UAS is constructed based on the information of ADS-B and geofence system.Moreover,a geofence layering algorithm is proposed.Secondly,the Flight Mode Change Points(FMCP)are used to define the relevant mode transition parameters and design the guard conditions,so as to generate the mode transition probability matrix and establish the continuous state-dependent-transition model.After that,the constrained Kalman filter(CKF)is applied to improve State-dependent-transition Hybrid Estimation(SDTHE)algorithm by applying equality constraint to the velocity of UAS in the straight phase and turning phase,respectively,and thus the constrained state-dependent-transition hybrid estimation(CSDTHE)algorithm is constructed.Finally,the results of intent inference and hybrid estimation are used to make trajectory prediction.Furthermore,each flight segment of trajectory is smoothed respectively by Rauch-Tung-Striebel(RTS)backward smooth method using the proposed CSDTHE-RTS algorithm,so as to obtain more accurate trajectory prediction results.The simulation shows that the proposed algorithm can reduce the errors of trajectory prediction and the time delay of intent inference. 展开更多
关键词 Trajectory prediction unmanned aircraft system geofence intent inference hybrid estimation Rauch-Tung-Striebel(RTS)backward smooth
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Fault Diagnosis of Nonlinear Systems Using Structured Augmented State Models
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作者 Jochen Aβfalg Frank Allgwer 《International Journal of Automation and computing》 EI 2007年第2期141-148,共8页
This paper presents an internal model approach for modeling and diagnostic functionality design for nonlinear systems operating subject to single- and multiple-faults. We therefore provide the framework of structured ... This paper presents an internal model approach for modeling and diagnostic functionality design for nonlinear systems operating subject to single- and multiple-faults. We therefore provide the framework of structured augmented state models. Fault characteristics are considered to be generated by dynamical exosystems that are switched via equality constraints to overcome the augmented state observability limiting the number of diagnosable faults. Based on the proposed model, the fault diagnosis problem is specified as an optimal hybrid augmented state estimation problem. Sub-optimal solutions are motivated and exemplified for the fault diagnosis of the well-known three-tank benchmark. As the considered class of fault diagnosis problems is large, the suggested approach is not only of theoretical interest but also of high practical relevance. 展开更多
关键词 Fault diagnosis nonlinear systems hybrid estimation.
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THE CONVERGENCE FOR NODAL EXPANSION METHOD
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作者 黄艾香 张波 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 1993年第2期135-149,共15页
In this paper, we prove the convergence of the nodal expansion method, a new numerical method for partial differential equations and provide the error estimates of approximation solution.
关键词 Nodal Expansion Method CONVERGENCE Error Estimate. Primal hybrid Finite Element Method.
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Superconvergence and recovery type a posteriori error estimation for hybrid stress finite element method 被引量:1
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作者 BAI YanHong WU YongKe XIE XiaoPing 《Science China Mathematics》 SCIE CSCD 2016年第9期1835-1850,共16页
Superconvergence and recovery type a posteriori error estimators are analyzed for Pian and Sumihara's 4-node hybrid stress quadrilateral finite element method for linear elasticity problems. Superconvergence of or... Superconvergence and recovery type a posteriori error estimators are analyzed for Pian and Sumihara's 4-node hybrid stress quadrilateral finite element method for linear elasticity problems. Superconvergence of order O(h^(1+min){α,1}) is established for both the displacement approximation in H^1-norm and the stress approximation in L^2-norm under a mesh assumption, where α > 0 is a parameter characterizing the distortion of meshes from parallelograms to quadrilaterals. Recovery type approximations for the displacement gradients and the stress tensor are constructed, and a posteriori error estimators based on the recovered quantities are shown to be asymptotically exact. Numerical experiments confirm the theoretical results. 展开更多
关键词 linear elasticity hybrid stress finite element superconvergence recovery a posteriori error estimator
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