Digital currency price prediction is vital to both sellers and purchasers. Over these years, decomposition and integration models have been applied more and more to realize the goal of precise prediction, however, many of them tend to neglect the reconstruction of features or the residual series. Altogether, one of the biggest drawbacks of the decomposition and integration framework is the method applied requires manual parameter setting whether it is for decomposition or integration. Still, for the results, they are merely satisfied with the point prediction which brings high uncertainty. In this paper, an optimized feature reconstruction decomposition and two-step nonlinear integration method is proposed which gives consideration to feature reconstruction, nonlinear integration, optimization and interval prediction. The original data series is decomposed through improved variational mode decomposition based approximate entropy feature reconstruction system. Then, improved particle swarm optimization-gated recurrent unit (iPSO-GRU) is utilized in the first and second nonlinear integration part separately. Meanwhile, the residual series is given attention, if it is not a white noise series, the residual will be the input of iPSO-GRU whose result will be added back to the second integration result to form the point prediction result. Based on the point prediction result, interval prediction estimate will be generated as well via maximum likelihood function. This study chooses three kinds of digital currency as cases and the results show that the MAPE values of point prediction are all below 3.5%, and CP values of interval prediction are all 1 with suitable MWP. In addition, compared with other benchmark models, the proposed model shows better performance.
The exploration of the high thermal stability near-infrared (NIR) phosphors is significantly crucial for the development of plant lighting. However, NIR phosphors suffer from the poor chemical and thermal stability, which severely limits their long-term operation. Here, the successful improvement of luminous intensity (149.5%) and thermal stability at 423 K of Zn3Ga2GeO8 (ZGGO): Cr3+ phosphors is achieved for the introduction of Al3+ ions into the host. The release of carriers in deep traps inhibits the emission loss for the thermal disturbance. Furthermore, an NIR light emitting diodes (LEDs) lamp is explored by combining the optimized Zn3Ga1.1675Al0.8GeO8: 0.0325Cr3+ phosphors with a commercial 460 nm blue chip, and the emission band can match well with the absorption bands of photosynthetic pigments and the phytochrome (PR and PFR) of plants. The explored LEDs lamp further determines the growth and the pheromone content of the involved plants for the participation of the NIR emission originated from Cr3+ ions. Our work provides a promising NIR lamp as plant light with improved thermal stability for long-term operation. 相似文献
The state-of-the-art protonic ceramic conductor BaZr0.8Y0.2O3-δ (BZY20) requires an extremely high sintering temperature (≥1700 °C) to achieve the desired relative density and microstructure necessary to function as a proton conducting electrolyte. In this work, we developed a cold sintering pretreatment assisted moderate-temperature sintering method for the fabrication of high-quality pure BZY20 pellets. BZY20 pellets with high relative density of ~94% were fabricated with a final sintering temperature of 1500 °C (200 °C lower than the traditional sintering temperature). A comparison with BZY20 control samples indicated that the proper amount of BaCO3 introduced on the BZY20 particle surface and the high green density achieved by cold sintering pretreatment were the main drivers for lowering the sintering temperature. The electrical conductivity measurement by electrochemical impedance spectroscopy showed that the as-prepared BZY20 pellets have a proton conductivity comparable to the state-of-the-art values. The cold sintering pretreatment outlined in this work has the potential to lower the sintering temperatures for similar types of protonic ceramic materials under consideration for a wide range of energy conversion and storage applications. 相似文献
The transparent Er3+-Yb3+-doped fluoro-aluminosilicate glass-ceramic (GC) was prepared by melt-quenching. The crystal phase, morphology, and up-conversion (UC) luminescence of as-produced GC were characterized by X-ray diffraction, scanning electron microscopy, and fluorescence spectrophotometry, respectively. The results show that BaYF5 nanocrystals were uniformly distributed in the glass matrix of the as-produced GC. When the as-produced GC was subjected to heat treatment, the crystallinity was increased, but the crystal identity remains unchanged. Such heat-treatment doubled the intensity of the UC luminescence, and this enhancement was ascribed to the increased incorporation of both Er3+ and Yb3+ ions into the lower phonon energy environment of BaYF5 nanocrystals. Furthermore, the heat-treated GC was stable against further crystallization, and consequently its UC luminescence was stable at the application temperature. The heat-treated GC was found to possess an outstanding temperature-sensing capability. 相似文献