Performance evaluation of series and parallel strategies for financial time series forecasting

Background:Improving financial time series forecasting is one of the most challenging and vital issues facing numerous financial analysts and decision makers.Given its direct impact on related decisions,various attempts have been made to achieve more accurate and reliable forecasting results,of which the combining of individual models remains a widely applied approach.In general,individual models are combined under two main strategies:series and parallel.While it has been proven that these strategies can improve overall forecasting accuracy,the literature on time series forecasting remains vague on the choice of an appropriate strategy to generate a more accurate hybrid model.Methods:Therefore,this study’s key aim is to evaluate the performance of series and parallel strategies to determine a more accurate one.Results:Accordingly,the predictive capabilities of five hybrid models are constructed on the basis of series and parallel strategies compared with each other and with their base models to forecast stock price.To do so,autoregressive integrated moving average(ARIMA)and multilayer perceptrons(MLPs)are used to construct two series hybrid models,ARIMA-MLP and MLP-ARIMA,and three parallel hybrid models,simple average,linear regression,and genetic algorithm models.Conclusion:The empirical forecasting results for two benchmark datasets,that is,the closing of the Shenzhen Integrated Index(SZII)and that of Standard and Poor’s 500(S&P 500),indicate that although all hybrid models perform better than at least one of their individual components,the series combination strategy produces more accurate hybrid models for financial time series forecasting.

“Series and parallel” design of ether linkage and imidazolium cation synergistically regulated four-armed polymerized ionic liquid for all-solid-state polymer electrolyte

Developing all-solid-state polymer electrolytes(SPEs) with high electrochemical performances and stability is of great importance for exploiting of high energy density and safe batteries. Herein, ether linkage and imidazolium ionic liquid(ILs) are incorporated into the multi-armed polymer backbone though the series and parallel way. The parallel polymeric ionic liquid(P-P(PEGMA-IM)) maximizes the synergistic effect of ILs and ether linkage, which endowed the material with low crystallinity and high flame retardancy. The P-P(PEGMA-IM) based P-SPE presents a high ionic conductivity of 0.489 m S/cm at 60°C, an excellent lithium-ion transference number of 0.46 and a wide electrochemical window of 4.87 V.The assembled lithium metal battery using P-SPE can deliver a capacity of 151 m Ah/g at 0.2 C, and the capacity retention ratio reaches 82% with a columbic efficiency beyond 99%. The overpotential of P-SPE based symmetric battery is 0.08 V, and there is no apparent magnifying even after 130 h cycling. This new design provides a new avenue for exploitation of advanced SPEs for the next-generation batteries.

Characteristics of Si-PIN nuclear radiation detectors stacked in series and parallel

The silicon-based diodes coated with a thin film of neutron reactive materials have been shown to produce excellent neutron detectors. We have fabricated the thin-film-coated single Si-PIN neutron detectors and stacked ones coupled in series and parallel in this work. The stacked detectors show the advantage of improving the detection efficiency of neutron detecting, which essentially attributes to the increase of the effective detection area. It is shown that the stacked detector in series has more superior performance than the parallel one. This work provides a feasible method to develop solid-state semiconductor neutron detectors with high neutron detection efficiency and high response speed.

An Explicit Solution for a Series and Parallel Queue with Retrial,Losses,and Bernoulli Schedule

This paper deals with the series and parallel queueing system in which there are two servers whose service time follow two exponential distributions.Each arriving customer either enters into the tandem service with probability or joins the service of the single server with complementary probability.We assume that the customers of arriving at the first server who find the first server is busy join an orbit and retry to enter the server after some time and of arriving at the second server who find the second server is busy are lost.For this model,we obtain the explicit expressions of the joint stationary distribution between the number of customers in the orbit and the states of the servers.

Modular Reciprocating HVDC Circuit Breaker with Current-limiting and Bi-directional Series-parallel Branch Switching Capability

The high-voltage direct current(HVDC)circuit breaker is becoming popular with the rapid development of the flexible HVDC grid for efficient DC fault ride-through purposes.This paper proposes a novel module for reciprocating HVDC circuit breaker topology,whose branch connections are able to switch between series and parallel modes to limit the rising rate and interrupt the DC fault currents.Diode-bridge submodules(DBSMs)are used to compose the main branch for current interruption.Besides fault clearance,the proposed topology has the advantageous function of DC fault current limiting by employing DBSMs with bi-directional conduction capability.The topology can easily switch among branch connection modes through the assembled trans-valves,and their resistance and reactance are very small in the normal state when branches are in parallel and the values become promptly large in the transient state when the branches are series connected.With the modular design,it is easy to change the number of branches or sub-modules and the types of sub-modules to adapt to more specific needs.A 6-terminal modular multi-level converter(MMC)based HVDC grid is established in PSCAD/EMTDC,and various simulation scenarios are carried out to validate the proposed topology.

Hybrid robust fault detection and isolation of satellite reaction wheel actuators

In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric uncertainties.The proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation module.First,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external disturbances.The residual evaluation module is developed based on the suggested series and parallel forms.Further,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and noises.The obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.

Electrode pattern design for GaAs betavoltaic batteries

The sensitivities of betavoltaic batteries and photovoltaic batteries to series and parallel resistance are studied.Based on the study,an electrode pattern design principle of GaAs betavoltaic batteries is proposed.GaAs PIN junctions with and without the proposed electrode pattern are fabricated and measured under the illumination of ^（63）Ni.Results show that the proposed electrode can reduce the backscattering and shadowing for the beta particles from ^（63）Ni to increase the GaAs betavoltaic battery short circuit currents effectively but has little impact on the fill factors and ideal factors.