ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2015-12-25
    Description: The power prediction for photovoltaic (PV) power plants has significant importance for their grid connection. Due to PV power’s periodicity and non-stationary characteristics, traditional power prediction methods based on linear or time series models are no longer applicable. This paper presents a method combining the advantages of the wavelet decomposition (WD) and artificial neural network (ANN) to solve this problem. With the ability of ANN to address nonlinear relationships, theoretical solar irradiance and meteorological variables are chosen as the input of the hybrid model based on WD and ANN. The output power of the PV plant is decomposed using WD to separated useful information from disturbances. The ANNs are used to build the models of the decomposed PV output power. Finally, the outputs of the ANN models are reconstructed into the forecasted PV plant power. The presented method is compared with the traditional forecasting method based on ANN. The results shows that the method described in this paper needs less calculation time and has better forecasting precision.
    Electronic ISSN: 1996-1073
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by MDPI Publishing
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2018-06-25
    Description: Remote Sensing, Vol. 10, Pages 1002: Inland Water Atmospheric Correction Based on Turbidity Classification Using OLCI and SLSTR Synergistic Observations Remote Sensing doi: 10.3390/rs10071002 Authors: Shun Bi Yunmei Li Qiao Wang Heng Lyu Ge Liu Zhubin Zheng Chenggong Du Meng Mu Jie Xu Shaohua Lei Song Miao Atmospheric correction is an essential prerequisite for obtaining accurate inland water color information. An inland water atmospheric correction algorithm, ACbTC (Atmospheric Correction based on Turbidity Classification), was proposed in this study by using OLCI (Ocean and Land Color Instrument) and SLSTR (Sea and Land Surface Temperature Radiometer) synergistic observations for the first time. This method includes two main steps: (1) water turbidity classification by the GRA index (GRAdient of the spectrum index); and (2) atmospheric correction by synergistic use of OLCI and SLSTR images. The algorithm was validated with 72 in situ sampling sites in Lake Erhai, Lake Hongze, and Lake Taihu, and compared with other atmospheric correction methods, i.e., C2RCC (Case 2 Regional Coast Colour processor), MUMM (Management Unit of the North Seas Mathematical Models), FLAASH (Fast Line-of-sight Atmospheric Analysis of Hypercubes), POLYMER (POLYnomial based algorithm applied to MERIS), and BPAC (Bright Pixel Atmospheric Correction). The results show that (1) the GRA index performed better than the proposed turbidity classification indices, i.e., the Diff (spectral difference index) and the Tind (turbid index), in inland lakes by using the reflectance peak at 1020 nm in clean water; (2) the synergistic use of OLCI and SLSTR performed feasibly for atmospheric correction, and the ACbTC algorithm achieved full-band average values of the mean absolute percentage error (MAPE) = 29.55%, mean relative percentage error (MRPE) = 13.98%, and the root mean square of error (RMSE) = 0.0039 sr−1, which were more reliable than C2RCC, MUMM, FLAASH, POLYMER, and BPAC; and (3) the synergistic use of the 17th band (865 nm) on OLCI and the 5th band (1613 nm) on SLSTR are suitable for clean inland lakes, while both the 5th band (1613 nm) and 6th band (2250 nm) on SLSTR are advisable for the turbidity.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2017-06-07
    Description: Segmentation techniques play an important role in understanding high-resolution polarimetric synthetic aperture radar (PolSAR) images. PolSAR image segmentation is widely used as a preprocessing step for subsequent classification, scene interpretation and extraction of surface parameters. However, speckle noise and rich spatial features of heterogeneous regions lead to blurred boundaries of high-resolution PolSAR image segmentation. A novel segmentation algorithm is proposed in this study in order to address the problem and to obtain accurate and precise segmentation results. This method integrates statistical features into a fractal net evolution algorithm (FNEA) framework, and incorporates polarimetric features into a simple linear iterative clustering (SLIC) superpixel generation algorithm. First, spectral heterogeneity in the traditional FNEA is substituted by the G0 distribution statistical heterogeneity in order to combine the shape and statistical features of PolSAR data. The statistical heterogeneity between two adjacent image objects is measured using a log likelihood function. Second, a modified SLIC algorithm is utilized to generate compact superpixels as the initial samples for the G0 statistical model, which substitutes the polarimetric distance of the Pauli RGB composition for the CIELAB color distance. The segmentation results were obtained by weighting the G0 statistical feature and the shape features, based on the FNEA framework. The validity and applicability of the proposed method was verified with extensive experiments on simulated data and three real-world high-resolution PolSAR images from airborne multi-look ESAR, spaceborne single-look RADARSAT-2, and multi-look TerraSAR-X data sets. The experimental results indicate that the proposed method obtains more accurate and precise segmentation results than the other methods for high-resolution PolSAR images.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2018-04-07
    Description: Sensors, Vol. 18, Pages 1114: Oil Motion Control by an Extra Pinning Structure in Electro-Fluidic Display Sensors doi: 10.3390/s18041114 Authors: Yingying Dou Biao Tang Jan Groenewold Fahong Li Qiao Yue Rui Zhou Hui Li Lingling Shui Alex Henzen Guofu Zhou Oil motion control is the key for the optical performance of electro-fluidic displays (EFD). In this paper, we introduced an extra pinning structure (EPS) into the EFD pixel to control the oil motion inside for the first time. The pinning structure canbe fabricated together with the pixel wall by a one-step lithography process. The effect of the relative location of the EPS in pixels on the oil motion was studied by a series of optoelectronic measurements. EPS showed good control of oil rupture position. The properly located EPS effectively guided the oil contraction direction, significantly accelerated switching on process, and suppressed oil overflow, without declining in aperture ratio. An asymmetrically designed EPS off the diagonal is recommended. This study provides a novel and facile way for oil motion control within an EFD pixel in both direction and timescale.
    Electronic ISSN: 1424-8220
    Topics: Chemistry and Pharmacology , Electrical Engineering, Measurement and Control Technology
    Published by MDPI Publishing
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...