Presented Hybrid Model Research Articles

Sparse and hybrid modelling of relative humidity: the Krško basin case study

This study describes an application of hybrid modelling for an atmospheric variable in the Krsko basin. The hybrid model is a combination of a physics-based and data-driven model and has some properties of both modelling approaches. In the authors’ case, it is used for the modelling of an atmospheric variable, namely relative humidity in a particular location for the purpose of using the predictions of the model as an input to the air-pollution-dispersion model for radiation exposure. The presented hybrid model is a combination of a physics-based atmospherical model and a Gaussian-process (GP) regression model. The GP model is a probabilistic kernel method that also enables evaluation of prediction confidence. The problem of poor scalability of GP modelling was solved using sparse GP modelling; in particular, the fully independent training conditional method was used. Two different approaches to dataset selection for empirical model training were used and multiple-step-ahead predictions for different horizons were assessed. It is shown in this study that the accuracy of the predicted relative humidity in the Krsko basin improved when using hybrid models over using the physics-based model alone and that predictions for a considerable length of horizon can be used.

Modeling and Control of a Mini Hybrid Hydro Matrix / Wind in Micro Grid Applications

The performance of controlled hybrid renewable hydro matrix wheels/ wind in micro grid application during the variations of water speed and load is described and investigated. This hybrid contained three wheels and three wind turbines modeled in MATLAB Simulink. This presented hybrid model consists of a water wheel and a generator in the main channel, wind turbine drives an induction generator, battery, variable static load, DC link, and control unit. Appropriate controllers are used to maintain the DC-link voltage constant at its desired value with variations of load, water and wind speed. The obtained simulated result shows that the studied hybrid system with the proposed controller and the storage system have a better performance of load voltage and current waveform compared with the case of not using an energy storage unit and the case of without a controller under the water, wind speed and load variations.

An innovative hybrid model based on outlier detection and correction algorithm and heuristic intelligent optimization algorithm for daily air quality index forecasting

Air pollution forecasting plays an important role in helping reduce air pollutant emission and guiding people's daily activities and warning the public in advance. Nevertheless, previous articles still have many shortcomings, such as ignoring the importance of outlier point detection and correction of original time series, and random initial parameters of models, and so on. A new hybrid model using outlier detection and correction algorithm and heuristic intelligent optimization algorithm is proposed in this study to address the above mentioned problems. First, data preprocessing algorithms are conducted to detect and correct outliers, excavate the main characteristics of the original time series; second, a widely used heuristic intelligent optimization algorithm is adopted to optimize the parameters of extreme learning machine to obtain the forecasting results of each subseries with improvement in accuracy; finally, experimental results and analysis show that the presented hybrid model provides accurate prediction, outperforming other comparison models, which emphasize the importance of outlier point detection and correction and optimization parameters of models, it also give a new feasible method for air pollution prediction, and contribute to make effective plans for air pollutant emissions.

Microscopic analysis of quasielastic scattering and breakup reactions of the neutron-rich nuclei Be12,14

A microscopic analysis of the optical potentials (OPs) and cross sections of quasielastic scattering of $^{12,14}$Be on $^{12}$C at 56 MeV/nucleon and on protons at energy near 700 MeV is carried out. For lower energy scattering the real part of the OP is calculated by using of double-folding procedure accounting for the anti-symmetrization effects, while the imaginary part is obtained on the base of the high-energy approximation (HEA). The HEA is also applied to the calculations of both real and imaginary OPs when solving the relativistic equation for the high-energy proton-nucleus elastic scattering. The neutron and proton density distributions computed in different microscopic models for $^{12}$Be and $^{14}$Be are used. In the present hybrid model of the optical potential the only free parameters are the depths of the real and imaginary parts of OP obtained by fitting the experimental data. The role of the inelastic scattering channel to the first excited $2^{+}$ and $3^{-}$ states in $^{12}$C when calculating the quasielastic cross sections, as well as the modified density of the $^{12}$C target accounting for the surface effects are studied. In addition, the cluster model, in which $^{14}$Be consists of a $2n$-halo and the $^{12}$Be core, is applied to calculate the cross sections of diffraction breakup and stripping reactions in $^{14}$Be+$^{12}$C scattering and longitudinal momentum distributions of $^{12}$Be fragments at energy of 56 MeV/nucleon. A good agreement of the theoretical results with the available experimental data of both quasielstic scattering and breakup processes is obtained.

Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes

The notion of hesitant fuzzy linguistic term sets (HFLTSs), which enables experts to utilize a few possible linguistic terms to evaluate varieties of common qualitative information, plays a significant role in handling situations in cases where these experts are hesitant in offering linguistic expressions. For addressing the challenges of information analysis and information fusion in hesitant fuzzy linguistic (HFL) group decision making, in accordance with the multi-granularity three-way decisions paradigm, the primary purpose of this study is to develop the notion of multigranulation decision-theoretic rough sets (MG-DTRSs) into the HFL background within the two-universe framework. Having revisited the relevant literature, we first propose a hybrid model named adjustable HFL MG-DTRSs over two universes by introducing an adjustable parameter for the expected risk appetite of experts, in which both optimistic and pessimistic versions of HFL MG-DTRSs over two universes are special cases of the adjustable version. Second, some of the fundamental properties of the proposed model are discussed. Then, on the basis of the presented hybrid model, a group decision making approach within the HFL context is further constructed. Finally, a practical example, a comparative analysis, and a validity test concerning person-job fit problems are explored to reveal the rationality and practicability of the constructed decision making rule.

A zonal hybrid approach coupling FNPT with OpenFOAM for modelling wave-structure interactions with action of current

This paper presents a hybrid numerical approach, which combines a two-phase Navier- Stokes model (NS) and the fully nonlinear potential theory (FNPT), for modelling wave-structure interaction. The former governs the computational domain near the structure, where the viscous and turbulent effects are significant, and is solved by OpenFOAM/InterDyMFoam which utilising the finite volume method (FVM) with a Volume of Fluid (VOF) for the phase identification. The latter covers the rest of the domain, where the fluid may be considered as incompressible, inviscid and irrotational, and solved by using the Quasi Arbitrary Lagrangian- Eulerian finite element method (QALE-FEM). These two models are weakly coupled using a zonal (spatially hierarchical) approach. Considering the inconsistence of the solutions at the boundaries between two different sub-domains governed by two fundamentally different models, a relaxation (transitional) zone is introduced, where the velocity, pressure and surface elevations are taken as the weighted summation of the solutions by two models. In order to tackle the challenges associated and maximise the computational efficiency, further developments of the QALE-FEM have been made. These include the derivation of an arbitrary Lagrangian- Eulerian FNPT and application of a robust gradient calculation scheme for estimating the velocity. The present hybrid model is applied to the numerical simulation of a fixed horizontal cylinder subjected to a unidirectional wave with or without following current. The convergence property, the optimisation of the relaxation zone, the accuracy and the computational efficiency are discussed. Although the idea of the weakly coupling using the zonal approach is not new, the present hybrid model is the first one to couple the QALE-FEM with OpenFOAM solver and/or to be applied to numerical simulate the wave-structure interaction with presence of current.

Study on the Brexit’s background and causes

Motivation: The results of the in-out referendum on the United Kingdom’s membership in the European Union has shown that the European project, understood as a process of political integration within the EU is not stable. The economic crisis as well as the migration crisis has started new discussion on the European project and its weaknesses. The British decision to leave the European Union significantly influences the conditions of the EU functioning and future. There is no doubt that the present situation is the most serious crisis in the history of the European integration. Aim: The aim of the paper is to analyze the hybrid model of integration and its influence on the United Kingdom’s decision to exit from the European Union and to broaden our understanding of the factors influencing that decision. The specific position of the United Kingdom in the EU will be analyzed. The history of the UK membership in the EU and the fundamental tension in the Member States’ debates concerning the model of integration will be discussed. The current situation represents a trade-off between two rival, federal and confederal, models of integration. The weaknesses of the present model of integration and its influence on the current state of the EU will be discussed. Results: From the very beginning the UK membership in the EU has been marked by many tensions. One of the most important problem was the discussion on the future model of the integration. The paper demonstrates that the present European integration hybrid model is the main reason for the EU crisis and the United Kingdom’s decision to leave the European Union.

A discrete phase hybrid continuum-atomistic model for electrokinetics in nanofluidics

The ever-growing field of micro- and nanotechnology has a great deal of interest in simulating dynamic phenomena of multiscale systems. Hybrid approaches that produce a trade-off between accuracy and computational costs play a key role in this area. In this study, an improved hybrid continuum-atomistic model is proposed for the simulation of electroosmotic flows in nanochannels. The aqueous solvent phase is modeled by the continuum four-way coupled Navier-Stokes equations, while a Lagrangian approach is used for the ion transport. Different forces, including the drag, buoyancy, Brownian, electrostatic, and ion-ion/wall-ion collision, and torques, including the drag and collision, govern the motion of ion particles. The ion-ion/wall-ion collision is taken into account by a discrete phase model, and the electric field is derived by the Poisson-Boltzmann closure. Results of the model, such as the change in bulk velocity with surface electric charge density, are validated by several molecular dynamics simulations and experimental observations available in the literature. It is shown that the present hybrid model is capable of predicting the main features of the problem. Moreover, the significance of different forces and the other alternative for modeling the external electric field, i.e., the discrete Coulomb’s approach with the modified particle mesh Ewald boundary treatment, are also examined. The proposed model would be extremely useful for future studies on the electrokinetics in nanochannels, especially in more complex geometries where the molecular dynamics approaches are limited due to the computational costs.

Discrete-Time Hybrid Control in Borel Spaces

A discrete-time hybrid control model with Borel state and action spaces is introduced. In this type of models, the dynamic of the system is composed by two sub-dynamics affecting the evolution of the state; one is of a standard-type that runs almost every time and another is of a special-type that is active under special circumstances. The controller is able to use two different type of actions, each of them is applied to each of the two sub-dynamics, and the activations of these sub-dynamics are possible according to an activation rule that can be handled by the controller. The aim for the controller is to find a control policy, containing a mix of actions (of either standard- or special-type), with the purpose of minimizing an infinite-horizon discounted cost criterion whose discount factor is dependent on the state-action history and may be equal to one at some stages. Two different sets of conditions are proposed to guarantee (i) the finiteness of the cost criterion, (ii) the characterization of the optimal value function and (iii) the existence of optimal control policies; to do so, we employ the dynamic programming approach. A useful characterization that signalizes the accurate times between changes of sub-dynamics in terms of the so-named contact set is also provided. Finally, we introduce two examples that illustrate our results and also show that control models such as discrete-time impulse control models and discrete-time switching control models become special cases of our present hybrid model.

Toward a hybrid model of ship performance in ice suitable for route planning purpose

Practical knowledge about the performance of a ship while navigating in ice is crucial for the selection of safe and efficient route for a ship. Existing route finding tools estimate ship performance in ice adopting numerous approaches, ranging from model tests and engineering models to experts-based guidelines. Therein ship performance is usually understood as attainable ship speed or the average speed in given ice conditions; rarely the probability of besetting in ice is taken into account. Those models despite being fairly accurate in the theory share the same shortcoming in practice. The latter encompasses three main issues: (1) inaccurate information about prevailing ice conditions, (2) presence of ice conditions that goes beyond the scope of the models, and (3) the effect of operational patterns and traffic organization on the performance of an individual ship. To approach those issues, we propose a hybrid model of ship performance in ice-covered waters. The hybrid model combines two other sub-models: engineering and data-driven. The former determines ship speed and besetting probability in ridged ice field with ice concentration close to 100%. The latter sub-model provides information on ship’s speed in the actual ice conditions, where the speed is affected also by operational restrictions and icebreaker assistance. It is based on an extensive dataset combining ship data from automatic identification system and ice data from ice charts and ice forecast models. The presented hybrid model is valid for a specific ship type, which is ice going bulk carrier (IA Super ice class), operating within the Northern Baltic Sea winter navigation system. The obtained results reveal that the hybrid model in principle is capable of providing reliable information about the performance of a ship in a wide range of conditions accounting for environmental variability and existing operational conditions. The model is suitable for the purpose of safe route planning in ice for a single ship or group of similar ships, accounting for the economy and safety of a voyage.

Universal freezeout condition for charged hadrons in a hybrid approach

Hadronic freezeout during the evolution of the medium created in heavy-ion collisions is an important phenomena. It is quite useful to find a universal freezeout condition for each and every nuclear collisions. In this article, we have constructed a hybrid model to calculate the ratio of transverse energy to total mean multiplicity $E_{T} /N_{ch}$, since this ratio can possibly act as a freezeout condition in heavy-ion collision experiments. Present hybrid model blends two approaches : Tsallis statistics and wounded quark approach. Recently, Tsallis statistics has been reliably used to obtain the transverse momentum distribution of charged hadrons produced in relativistic ion collisions. On the other side it has been shown that the pseudorapidity distribution of charged hadrons can be calculated satisfactorily using the wounded quark model (WQM). We have used this hybrid model to calculate the transverse energy density distributions, $dE_{T}/d\eta$ at midrapidity using charged particle pseudorapidity distributions, $dN_{ch}/d\eta$ and mean transverse momentum $\langle p_{T} \rangle$ in various type of nuclear collisions. We found that present hybrid model satisfactorily explains the experimental data whether other models fail to reproduce the data at central and at peripheral collisions simultaneously. Finally, ratio of transverse energy to total mean multiplicity, $E_{T} /N_{ch}$ has been computed within hybrid model and compared with the available experimental data at RHIC and LHC energies. We observed no explicit dependence of $E_{T} /N_{ch}$ on energy as well as centrality and thus it can definitely act as a freezeout criteria.

An Innovative Hybrid Model Based on Data Pre-Processing and Modified Optimization Algorithm and Its Application in Wind Speed Forecasting

Wind speed forecasting has an unsuperseded function in the high-efficiency operation of wind farms, and is significant in wind-related engineering studies. Back-propagation (BP) algorithms have been comprehensively employed to forecast time series that are nonlinear, irregular, and unstable. However, the single model usually overlooks the importance of data pre-processing and parameter optimization of the model, which results in weak forecasting performance. In this paper, a more precise and robust model that combines data pre-processing, BP neural network, and a modified artificial intelligence optimization algorithm was proposed, which succeeded in avoiding the limitations of the individual algorithm. The novel model not only improves the forecasting accuracy but also retains the advantages of the firefly algorithm (FA) and overcomes the disadvantage of the FA while optimizing in the later stage. To verify the forecasting performance of the presented hybrid model, 10-min wind speed data from Penglai city, Shandong province, China, were analyzed in this study. The simulations revealed that the proposed hybrid model significantly outperforms other single metaheuristics.

Improvement of the simulation of fuel particles motion in a fluidized bed by considering wall friction

The mixing of fuel particles is a key issue on the performance of fluidized bed reactors. In this work, the motion of a non-reactive fuel particle in a pseudo-2D bubbling fluidized bed operated at ambient conditions is simulated employing a hybrid-model and introducing a new friction term that accounts for the effect of the bed vessel front and rear walls. The hybrid-model, implemented in the code MFIX, simulates the dense and gas phases using a Two-Fluid Model (TFM) whereas the fuel particles are modeled using a Discrete Element Method (DEM). The importance of the present hybrid-model is that the interaction of the continuum phases with the fuel particles behavior is fully coupled.To improve the accuracy of the simulated fuel particle motion in a bubbling fluidized bed, a model accounting for the effect of the bed front and rear walls on the continuum solid phase is combined with the hybrid-model. The rising and sinking velocity of the fuel particles, the circulation time and statistical parameters associated to the location of the fuel particle in the bed were obtained from the simulations and compared with experimental measurements. According to the results, the prediction of these parameters is clearly improved when the friction term is included in the simulation.

A hybrid PSO-SVM-based method for predicting the friction coefficient between aircraft tire and coating

A hybrid PSO-SVM-based model is proposed to predict the friction coefficient between aircraft tire and coating. The presented hybrid model combines a support vector machine (SVM) with particle swarm optimization (PSO) technique. SVM has been adopted to solve regression problems successfully. Its regression accuracy is greatly related to optimizing parameters such as the regularization constant , the parameter gamma corresponding to RBF kernel and the epsilon parameter in the SVM training procedure. However, the friction coefficient which is predicted based on SVM has yet to be explored between aircraft tire and coating. The experiment reveals that drop height and tire rotational speed are the factors affecting friction coefficient. Bearing in mind, the friction coefficient can been predicted using the hybrid PSO-SVM-based model by the measured friction coefficient between aircraft tire and coating. To compare regression accuracy, a grid search (GS) method and a genetic algorithm (GA) are used to optimize the relevant parameters (, and ), respectively. The regression accuracy could be reflected by the coefficient of determination (). The result shows that the hybrid PSO-RBF-SVM-based model has better accuracy compared with the GS-RBF-SVM- and GA-RBF-SVM-based models. The agreement of this model (PSO-RBF-SVM) with experiment data confirms its good performance.

Modeling and performance analysis of dynamic spectrum sharing between DSRC and Wi‐Fi systems

AbstractThe Notice of Proposed Rulemaking 13‐22 released by Federal Communications Commission unlocks the Dedicated Short Range Communication (DSRC) spectrum for Wi‐Fi availability, which undoubtedly brings unpredictable effects to the new‐emerging vehicular applications and services. To efficiently harmonize the spectrum operation between DSRC and Wi‐Fi networks, several dynamic spectrum‐sharing schemes are already proposed to improve the spectral efficiency over a limited bandwidth situation and as well to satisfy the ever‐increasing demand for bandwidth resource. Different from most previous literature that mainly focused on the performance analysis of cellular‐network‐centric spectrum sharing, we aim to analyze the performance of the mainstream dynamic spectrum‐sharing schemes specially designed for the coexistence of DSRC and Wi‐Fi networks against various combinations of network parameters through a hybrid network model and performance indicators. We employ the Poisson point process to model a hybrid network where DSRC vehicles and Wi‐Fi devices coexist, and introduce the performance indicators of spectrum efficiency and data rate to assess the utility of different spectrum sharing candidates. Through the presented hybrid model and performance indicators, we collect extensive numerical and simulation results to investigate four typical spectrum allocation schemes for DSRC and Wi‐Fi coexistence, that is non‐sharing scheme, original sharing scheme, and Qualcomm's and Cisco's proposals, respectively. The results show that the dynamic spectrum sharing in the 5.9‐GHz band can significantly raise the performance of Wi‐Fi network without excessively degrading the DSRC system, and especially the Cisco's proposal prefers to protect the DSRC profit while the Qualcomm's draft favors Wi‐Fi exclusively. Copyright © 2016 John Wiley & Sons, Ltd.

Contact characteristic analysis of spindle–toolholder joint at high speeds based on the fractal model

Due to the influence of centrifugal force, accurate contact stiffness model of spindle–toolholder joint at high speeds is crucial in predicting the dynamic behavior and chatter vibration of spindle–toolholder system. In this paper, a macro–micro scale hybrid model is presented to obtain the contact stiffness of spindle–toolholder joint in high speeds. The hybrid model refers to the finite element model in macro-scale and three-dimensional fractal model in micro-scale. The taper contact surface of spindle–toolholder joint is assumed flat in macro-scale and the finite element method is used to obtain the pressure distribution at different speeds. In micro-scale, the topography of contact surfaces is fractal featured and determined by fractal parameters. Asperities in micro-scale are considered as elastic and plastic deformation. Then, the contact ratio, radial and torsional contact stiffness of spindle–toolholder joint can be calculated by integrating the micro asperities. Experiments with BT40 type toolholder–spindle assembly are conducted to verify the proposed model in the case of no speed. The reasonable intervals of spindle speed and drawbar force can be obtained based on the presented hybrid model, which will provide theoretical basis for the application and optimization of the spindle–toolholder system.

Transient Lightning Impulse Performance Analysis for Composite Transmission Line Tower

In this paper, the transient impulse performances of a 330-kV composite transmission line tower under direct lightning strokes are comprehensively presented. An equivalent distributed parameter model combined with lumped capacitance elements for the tower is established. The wave impedances of the hybrid model are determined by using analytic equations. The lumped capacitances are calculated by 3-D finite element method (FEM). An accurate model for extended grounding structure (EGS) of the tower base considering the soil ionization is used to simulate its impulse performances. The wave process of the tower is analyzed by using the electromagnetic transient program (EMTP). The proper grounding conductor system is determined for the case of a superior lightning impulse performance considering three diverse grounding configurations. The influence of radius of the grounding conductor is assessed. The numerical electromagnetic field analysis, finite-difference time-domain (FDTD) simulation is applied to verify the validity of the presented hybrid model. Then, the influence of the wave-front time of the lightning current, the soil resistivity, the dimension of the EGS, and their combined effect on the transient impulse performances for the EGS are analyzed and discussed.

Tunable magnetic helicity in Mn1−xFexGe: A Monte Carlo simulation

Motivated by recent experiments on B20 compound Mn1−xFexGe, we explore the variations of spin structures and magnetic helicity γm in Mn1−xFexGe as a function of concentration x, using Monte Carlo simulation. We propose a simple spin model including hybrid Dzyaloshinskii-Moriya (DM) interactions with different signs in FeGe and MnGe. The results reveal a series of spin structures with helicity γm varying continuously from negative values to positive values upon decreasing x (0.0 ≤ x ≤ 1.0). The simulated x-dependence of the spin structures is consistent with experimental observations, suggesting the validity of the present hybrid model. This study sheds light on control of magnetic helicity in helimagnets, by mixing crystals with different DM interactions.

DESIGN AND IMPLEMENTATION OF IMAGE COMPRESSION USING SET PARTITIONING IN HIERARCHICAL TREES AND HYBRID WAVELET TRANSFORM

To store digital image and video in raw form require large amount of memory space. Image compression means reducing the size of image file without degrading quality of image. Depending on the reconstructed image to be exactly same as the original or some unknown loss may incurred image compression divided into two techniques lossy and lossless techniques. In this paper we present hybrid model which is the combination of several compression techniques. This paper present DWT, DCT and SPIHT implementation. Simulation has been carried out on different images like Lena , Barbra, Cameraman, Test drive . Result analysis is done through parameters like MSE, PSNR and Elapsed time. Values of this parameters will go better than the old algorithms because here we apply SPIHT lossless technique and also due to hybrid combination of DWT and DCT we will get good level of compression. The result analysis shows that the proposed hybrid algorithm performs much better in terms of PSNR with a higher compression ratio as compared to standalone DWT and DCT techniques.

A hybrid continuum and molecular mechanics model for the axial buckling of chiral single-walled carbon nanotubes

The purpose of this study is to describe the axial buckling behavior of chiral single-walled carbon nanotubes (SWCNTs) using a combined continuum-atomistic approach. To this end, the nonlocal Flugge shell theory is implemented into which the nonlocal elasticity of Eringen incorporated. Molecular mechanics is used in conjunction with density functional theory (DFT) to precisely extract the effective in-plane and bending stiffnesses and Poisson's ratio used in the developed nonlocal Flugge shell model. The Rayleigh-Ritz procedure is employed to analytically solve the problem in the context of calculus of variation. The results generated from the present hybrid model are compared with those from molecular dynamics simulations as a benchmark of good accuracy and excellent agreement is achieved. The influences of small scale factor, commonly used boundary conditions and chirality on the critical buckling load are fully explored. It is indicated that the importance of the small length scale is affected by the type of boundary conditions considered.