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IEEE 35th International Conference on Data Engineering (ICDE)

作者： Wei, Ziheng Link, Sebastian Univ Auckland Dept Comp Sci Auckland New Zealand

ISBN: (纸本)9781538674741

Computing the functional dependencies that hold on a given data set is one of the most important problems in data profiling. Utilizing new data structures and original techniques for the dynamic computation of stripped partitions, we devise a new hybridization strategy that outperforms the best algorithms in terms of efficiency, column-, and row-scalability. This is demonstrated on real-world benchmark data. We further propose the number of redundant data values for ranking the output of discovery algorithms. Our ranking assesses the relevance of functional dependencies for the given data set.

关键词： algorithm data-profiling discovery functional dependency hybrid memory-consumption missing-data ranking redundancy runtime-efficiency

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Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode

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Frontiers in Energy 2019年第1期13卷 131-148页

作者： Alireza REZVANI Ali ESMAEILY Hasan ETAATI Mohammad MOHAMMADINODOUSHAN Department of Electrical Engineering Saveh BranchIslamic Azad UniversitySaveh ***Iran Water and Power Resources Development Company(IWPCO)Iran Department of Electrical Engineering Karaj BranchIslamic Azad UniversityKaraj ***Iran Iran Water and Power Resources Development Company(IWPCO) Iran Department of Electrical Engineering Science and Research BranchIslamic Azad UniversityTehran ***Iran

Photovoltaic(PV)generation is growing increasingly fast as a renewable energy ***,the drawback of the PV system is intermittent because of depending on weather ***,the wind power can be considered to assist for a stable and reliable output from the PV generation system for loads and improve the dynamic performance of the whole generation system in the grid connected *** this paper,a novel topology of an intelligent hybrid generation system with PV and wind turbine is *** order to capture the maximum power,a hybrid fuzzy-neural maximum power point tracking(MPPT)method is applied in the PV *** average tracking efficiency of the hybrid fuzzy-neural is incremented by approximately two percentage points in comparison with the conventional *** pitch angle of the wind turbine is controlled by radial basis function network-sliding mode(RBFNSM).Different conditions are represented in simulation results that compare the real power values with those of the presented *** obtained results verify the effectiveness and superiority of the proposed method which has the advantages of robustness,fast response and good *** mathematical model and a control approach of a three-phase grid-connected intelligent hybrid system have been proposed using Matlab/Simulink.

关键词： photovoltaic wind turbine hybrid system fuzzy logic controller genetic algorithm RBFNSM

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Optimal Sizing of Solar/Wind hybrid Off-Grid Microgrids Using an Enhanced Genetic algorithm

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Journal of Power and Energy Engineering 2018年第5期6卷 64-77页

作者： Abdrahamane Traoré Hatem Elgothamy Mohamed A. Zohdy Department of Electrical and Computer Engineering Oakland University Rochester MI USA

This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.

关键词： Optimization Off-Grid Microgrid Renewable Energy Energy Storage Systems (ESS) Solar Photovoltaic (PV) Wind Battery hybrid Genetic algorithm (GA)

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hybrid algorithm performance with varying population size for multi-objective optimisation of in-situ bioremediation of groundwater

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2013年第3期5卷 164-174页

作者： Kumar, Deepak Ch, Sudheer Mathur, Shashi Panigrahi, B. K. IIT Delhi Dept Civil Engn New Delhi 110016 India IIT Delhi Dept Elect Engn New Delhi 110016 India

In-situ bioremediation of groundwater is one of the remediation technique applied for cleaning groundwater at its site. Cost of remediation and remaining concentration of contaminant are the main conflicting objectives to be decided during remediation period of groundwater. Multi objective optimisation is one of the best techniques to obtain Paretos for the conflicting objectives. In this study metaheuristic hybrid algorithm has been used to obtain Paretos for in-situ bioremediation of groundwater. Further, the performance of Paretos obtained with varying population size has been evaluated. The results indicate that too small or too large population size does not give well spaced Paretos. Only the population size in specific range shows better performance in the present study for groundwater remediation. The cost analysis of in-situ bioremediation based on the Paretos obtained from proposed hybrid algorithm shows that percentage increase in cost increases as the clean up standard of groundwater increases.

关键词： in-situ bioremediation multi-objective Paretos population size groundwater optimisation metaheuristic hybrid remediation performance algorithm

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Aircraft Engine Gas Path Fault Diagnosis Based on hybrid PSO-TWSVM

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第2期35卷 334-342页

作者： Du Yanbin Xiao Lingfei Chen Yusheng Ding Runze Jiangsu Province Key Laboratory of Aerospace Power Systems College of Energy and Power EngineeringNanjing University of Aeronautics and Astronautics

Twin support vector machine(TWSVM)is a new development of support vector machine(SVM)*** has the smaller computation scale and the stronger ability to cope with unbalanced *** this paper,TWSVM is introduced into aircraft engine gas path fault *** generalization capacity of Gauss kernel function usually used in TWSVM is relatively *** a mixed kernel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good learning *** results prove that the cross validation training accuracy of TWSVM using the mixed kernel function averagely increases 2%.Grid search is usually applied in parameter optimization of TWSVM,but it heavily depends on ***,the hybrid particle swarm algorithm is *** can intelligently and rapidly find the global *** prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.

关键词： aircraft engines fault diagnosis twin support vector machine (TWSVM) hybrid particle swarm optimization (HPSO) algorithm mixed kernel function

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hybrid Optimization of a Valveless Diaphragm Micropump Using the Cut-Cell Method

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Journal of Mechanics Engineering and Automation 2019年第4期9卷 120-127页

作者： kapsoulis K.Samouchos X.Trompoukis K.Giannakoglou Parallel CFD&Optimization Unit School Mech.Eng.National Technical University of AthensAthens 15780Greece

This paper presents the optimization of 3D valveless diaphragm micropump for medical *** pump comprises an inlet and outlet diffuser connected to the main chamber equipped with a periodically moving diaphragm that generates the unsteady flow within the *** optimization,which is related exclusively to the diaphragm motion,aims at maximizing the net flowrate and minimizing the backflow at the outlet *** CFD analyses are performed using an in-house cut-cell method,based on the finite volume approach,on a many-processor *** reduce the optimization turn-around time,two optimization methods,a gradient-free evolutionary algorithm enhanced by surrogate evaluation models and a gradient-based(GB)method are synergistically *** support the GB optimization,the continuous adjoint method that computes the gradient of the objectives with respect to the design variables has been developed and *** the hybrid optimization method,the Pareto front of non-dominated solutions,in the two-objective space,is ***,a couple of optimal solutions selected from the computed Pareto front are re-evaluated by considering uncertainties in the operating conditions;these are quantified using the polynomial chaos expansion method.

关键词： Diaphragm micropump cut-cell method hybrid optimization adjoint method evolutionary algorithm uncertaintyquantification

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Collaborative Optimization of Berth Allocation and Yard Storage in Container Terminals

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Journal of Traffic and Transportation Engineering 2019年第2期7卷 56-70页

作者： Wenwen Guo Mingjun Ji Huiling Zhu Dalian Maritime University Transportation Engineering College Dalian 116026LiaoningChina

Considering the interaction between the berth and the yard,this paper studies the collaborative optimization problem of berth allocation and yard storage from the point of the ships over a certain planning *** collaborative optimization problem is formulated as the integer programming,which aims at minimizing the total truck travel *** decision variables are the berthing positions for visiting ships and the storage positions for export ***,this paper demonstrates the complexity of the problem in *** the hybrid tabu genetic algorithm is designed to solve the problem to obtain the optimal berth allocation position and export container storage *** this algorithm,the rule is applied to generate the initial feasible solutions,and the crossover and mutation operation are simultaneously applied to optimize the initial ***,this paper discusses two different scenes:the same berth scene and the same ship *** influence of two different scenes on truck travel distance is analyzed by different numerical *** examples’results show that the collaborative optimization of berth allocation and yard storage can effectively shorten the truck travel distance and improve the efficiency of terminal operation,which provides the decision support for terminal operators.

关键词： Export containers berth allocation yard storage collaborative optimization hybrid tabu genetic algorithm

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Abdominopelvic trauma: from anatomical to anatomo-physiological classification

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WORLD JOURNAL OF EMERGENCY SURGERY 2018年第1期13卷 1-4页

作者： Coccolini, Federico Catena, Fausto Kluger, Yoram Sartelli, Massimo Baiocchi, Gianluca Ansaloni, Luca Moore, Ernest Eugene Bufalini Hosp Gen Emergency & Trauma Surg Dept Viale Ghirotti 268 I-47521 Cesena Italy Parma Maggiore Hosp Emergency Surg Dept Parma Italy Rambam Hlth Care Campus Haifa Div Gen Surg Haifa Israel Macerata Hosp Dept Gen Surg Macerata Italy Univ Brescia Dept Clin & Expt Sci Brescia Italy Denver Hlth Trauma Surg Denver CO USA

Abdominopelvic trauma has been for decades classified with the AAST-OIS (American Association for the Surgery of Trauma-Organ Injury Scale) classification. It has represented a milestone. At present, the medical evolutions in trauma management allowed an incredible progress in trauma decision-making and treatment. Non-operative trauma management has been widely applied. The interventional radiological procedures and the modern conception of hybrid and Endovascular Trauma and Bleeding Management (EVTM) led to good results in increasing the rate of patients managed non-operatively, opening new scenarios and options. Even severe anatomical lesions in hemodynamically stable patients can be safely managed non-operatively. The driving issue in deciding for the best treatment is anatomy, as well as physiology, for the patient physiological derangement grade is even more important. The emergency general surgeon must be prepared in those pathophysiological issues that play the pivotal role in the team management of trauma patients. Moreover, the classification of trauma patients cannot only remain anchored to anatomical lesions. The necessity to follow the modern possibilities of treatment imposes addressing trauma using a classification based on anatomical lesions and on the physiological status of the patient.

关键词： Trauma Classification Physiology Stratification Decision Flow-chart algorithm Guidelines Spleen Liver Pelvis Kidney Polytrauma hybrid Endovascular Bleeding Management Emergency general surgery

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An Optimization Method for a Single Machine Multi-family Scheduling Problem with Qualification Run Constraints

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Journal of Harbin Institute of Technology(New Series) 2018年第2期25卷 24-32页

作者： Binghai Zhou Jiaying Gu School of Mechanical Engineering Tongji University

The qualification run(qual-run) as a technique to avoid possible quality problems of products inevitably leads to much longer cycle time. To effectively balance the trade-off between the qual-run and setup times,a scheduling model of a single machine with multiple families was developed and an adaptive differential evolution algorithm based on catastrophe with depth neighborhood search was applied to resolve the problem. First,a scheduling problem domain was described,and a mathematical programming model was set up with an objective of minimizing makespan. Further,several theorems were developed to construct feasible solutions. On the basis of differential evolution,the depth neighborhood search operator was adopted to search a wide range of solutions. In addition,the adaptive process and catastrophe theory were combined to improve the performance of the algorithm. Finally,simulation experiments were carried out and the results indicated that the proposed algorithm was effective and efficient.

关键词： setup qual-run multi-family scheduling hybrid differential evolution algorithm

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A hybrid finite-element and integral-equation method for forward modeling of 3D controlled-source electromagnetic induction

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Applied Geophysics 2018年第3期15卷 536-544页

作者： Zhou Feng Tang Jing-Tian Ren Zheng-Yong Zhang Zhi-Yong Chen Huang Huang Xiang-Yu Zhong Yi-Yuan School of Geosciences and Infophysics of Central South University Changsha 410083China School of Geophysics and Measurement-control Technology East China Institute of TechnologyNanchang 330013China

We have developed a hybrid solver that combines the finite-element and integralequation method for 3D CSEM modeling based on unstructured meshes. To avoid the source singularity, the secondary field is used in the modeling framework. The primary electromagnetic field from an electric dipole source in a layered medium is calculated based on the magnetic vector potential method. The inhomogeneities of the computational region are discretized by a vector-based finite-element mesh with boundaries at finite distance from the inhomogeneities by using the dyadic Green's function, reducing the truncation boundary effect and the solution region. The electric and magnetic Green's function is used in data postprocessing to reduce the numerical errors owing to inaccurate gradients because of unstructured meshes; thus, the electromagnetic field is more accurately calculated. Finally, the proposed algorithm is applied to a block and a disc model, and we assess the topography effect on the field components.

关键词： CSEM FEM IE hybrid algorithm mesh

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