A new effective parameter estimation approach is presented for the Multiscale Kalman Smoother (MKS) algorithm. As demonstrated, it shows promising potentials in deriving better data products involving sources from dif...
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A new effective parameter estimation approach is presented for the Multiscale Kalman Smoother (MKS) algorithm. As demonstrated, it shows promising potentials in deriving better data products involving sources from different spatial scales and precisions. The proposed approach employs a multiobjective parameter estimation framework, which includes three multiobjective estimation schemes (MO schemes), rather than using the conventional maximum likelihood scheme (ML scheme), to estimate the MKS parameters. Unlike the ML scheme, the MO schemes are not built on strict statistical assumptions related to prediction errors and observation errors, rather, they directly associate the fused data of multiple scales with multiple objective functions. In the MO schemes, objective functions are defined to facilitate consistency among the fused data at multiple scales and the input data at their original scales as well in terms of spatial patterns and magnitudes. Merits of the new approach are evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data that contain noises which follow either the multiplicative error model or the additive error model. Our results show that the MKS fused precipitation performs better using the MO framework. Improvements are particularly significant for the fused precipitation associated with fine spatial resolutions. This is due mainly to the adoption of more criteria and constraints in the MO framework. The weakness of the original ML scheme, arising from its blindly putting more weights into the data associated with finer resolutions, is circumvented in the proposed new MO framework.
This study incorporates the newly available Gravity Recovery and Climate Experiment (GRACE) water storage data and water table data from well logs to reduce parameter uncertainty in Soil and Water Assessment Tool (SWA...
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This study incorporates the newly available Gravity Recovery and Climate Experiment (GRACE) water storage data and water table data from well logs to reduce parameter uncertainty in Soil and Water Assessment Tool (SWAT) calibration using a SUFI2 (sequential uncertainty fitting) framework for the Lower Missouri River Basin. Model evaluations are performed in multiple stages using a multiobjective function consisting of multisite streamflow and GRACE water storage data as well as a groundwater component. Results show that (1) a model calibrated with both streamflow and GRACE data simultaneously can maintain the water balance for the whole basin, but may improperly partition surface flow and base flow. Additional inclusion of the groundwater constraint can significantly improve the model performance in groundwater hydrological processes. In our case, the estimation of specific yield of shallow aquifers has been increased to 102 from previous much underestimated level (<103). (2) The daily streamflow data are needed to confine the parameters related to water flow in channels such as the Manning's coefficient, which are less sensitive to the monthly simulations. (3) Parameters are nonuniformly sensitive for different goal variables, and thus, proper specification of a prior distribution of parameters may be the key factor for global optimization algorithms to obtain stable and realistic model performance.
Coupling matrix synthesis technique based on multi-objective evolutionary algorithm (MOEA) is proposed for pseudoelliptic low-pass filter prototypes with lossy resonators and arbitrary topology. MOEA-based synthesis c...
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Coupling matrix synthesis technique based on multi-objective evolutionary algorithm (MOEA) is proposed for pseudoelliptic low-pass filter prototypes with lossy resonators and arbitrary topology. MOEA-based synthesis can deal with multi-objective functions so that different filter characteristics of high-performance lossy filter, such as return loss, out of band rejection and passband flatness, can be optimised simultaneously. In the proposed MOEA-based lossy filter synthesis, a chromosome pair coding model is defined to treat real and imaginary parts of complex coupling matrix of a lossy filter, and additional constraints on Q-factor to characterise lossy resonator in the filter are applied. For demonstration, non-dominated sorting genetic algorithm II with extended arithmetic crossover and adaptive mutation operator are used to synthesise three symmetric/asymmetric lossy filters. The results indicate that the proposed MOEA-based synthesis technique can provide perfect passband ripple as required in high-performance microwave filters.
Task scheduling in the cloud is the multiobjective optimization problem, and most of the task scheduling problems fail to offer an effective trade-off between the load, resource utilization, makespan, and Quality of S...
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Task scheduling in the cloud is the multiobjective optimization problem, and most of the task scheduling problems fail to offer an effective trade-off between the load, resource utilization, makespan, and Quality of Service (QoS). To bring a balance in the trade-off, this paper proposes a method, termed as crow-penguin optimizer for multiobjective task scheduling strategy in cloud computing (CPO-MTS). The proposed algorithm decides the optimal execution of the available tasks in the available cloud resources in minimal time. The proposed algorithm is the fusion of the Crow Search optimization Algorithm (CSA) and the Penguin Search Optimization Algorithm (PeSOA), and the optimal allocation of the tasks depends on the newly designed optimization algorithm. The proposed algorithm exhibits a better convergence rate and converges to the global optimal solution rather than the local optima. The formulation of the multiobjectives aims at a maximum value through attaining the maximum QoS and resource utilization and minimum load and makespan, respectively. The experimentation is performed using three setups, and the analysis proves that the method attained a better QoS, makespan, Resource Utilization Cost (RUC), and load at a rate of 0.4729, 0.0432, 0.0394, and 0.0298, respectively.
The present industrial and domestic applications needs the drive which is low cost, small size, reliable to different operating conditions, simple in design of controller. For a good dynamic control of any machine, kn...
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ISBN:
(纸本)9781467350907;9781467350891
The present industrial and domestic applications needs the drive which is low cost, small size, reliable to different operating conditions, simple in design of controller. For a good dynamic control of any machine, knowledge of the rotor position is required. But the position sensor can be an expensive part of a drive system and because it normally be subject to a hot and electrically noisy environment, it can also be unreliable. Sensorless control is desirable, but most sensorless method involves extensive computation. This paper presents the sensorless scheme for four quadrant operation with minimal computation and simple. Eventhough due to the absence of windings in rotor the cost of machine is cheap, the torque ripple produced by the drive is more when compared to other drives due to non linearity characteristics of inductance profile. The present scheme of control predicts the position of rotor by using the phase current alone. The multiobjective function in the controller design provides the requirement of varying turn on and off angle with sampling frequency of term makes the controller very precise in every region of drives with minimum ripple content. The tracking speed of drive to get fast response in particular application like electric vehicles, wind power generator, vacuum cleaners.
The present industrial and domestic applications needs the drive which is low cost, small size, reliable to different operating conditions, simple in design of controller. For a good dynamic control of any machine, kn...
详细信息
ISBN:
(纸本)9781467350891
The present industrial and domestic applications needs the drive which is low cost, small size, reliable to different operating conditions, simple in design of controller. For a good dynamic control of any machine, knowledge of the rotor position is required. But the position sensor can be an expensive part of a drive system and because it normally be subject to a hot and electrically noisy environment, it can also be unreliable. Sensorless control is desirable, but most sensorless method involves extensive computation. This paper presents the sensorless scheme for four quadrant operation with minimal computation and *** due to the absence of windings in rotor the cost of machine is cheap, the torque ripple produced by the drive is more when compared to other drives due to non linearity characteristics of inductance profile. The present scheme of control predicts the position of rotor by using the phase current alone. The multiobjective function in the controller design provides the requirement of varying turn on and off angle with sampling frequency of term makes the controller very precise in every region of drives with minimum ripple content. The tracking speed of drive to get fast response in particular application like electric vehicles, wind power generator, vacuum cleaners.
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