Application of nonlinear adaptive filter based on nearest neighbors in phase space on EMD end effect

Forecasting surface temperature and pressure to a reasonable degree of accuracy atleast 3 hours ahead of the scheduled departure of an aircraft helps the aircrew to make the optimum planning for the payload and cargo load. The method of generalised Adaptive Filter (AF) algorithm as suggested by Makridakis and Wheelright (1978) has been used to forecast temperature and pressure over Madras airport and the forecast efficiency is compared with that obtained through method of persistency, auto regressive processes and other statistical techniques. The dimensions of attractors of the phase space trajectories of these variables have been estimated using the Grassberger and Procaccia (1983) algorithm of correlation fractal dimension with a view to find out the predictability of these variables and the minimum and maximum number of parameters needed for modelling these variables.

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Nearest Neighbors Time Series Forecaster Based on Phase Space Reconstruction for Short-Term Load Forecasting

Energies ◽

10.3390/en13205309 ◽

2020 ◽

Vol 13 (20) ◽

pp. 5309

Author(s):

Jose R. Cedeño González ◽

Juan J. Flores ◽

Claudio R. Fuerte-Esquivel ◽

Boris A. Moreno-Alcaide

Keyword(s):

Phase Space ◽

National Level ◽

Load Forecasting ◽

Nearest Neighbors ◽

Electric Utility ◽

Phase Space Reconstruction ◽

Support Vector ◽

Short Term ◽

Essential Information ◽

Short Term Load Forecasting

Load forecasting provides essential information for engineers and operators of an electric system. Using the forecast information, an electric utility company’s engineers make informed decisions in critical scenarios. The deregulation of energy industries makes load forecasting even more critical. In this article, the work we present, called Nearest Neighbors Load Forecasting (NNLF), was applied to very short-term load forecasting of electricity consumption at the national level in Mexico. The Energy Control National Center (CENACE—Spanish acronym) manages the National Interconnected System, working in a Real-Time Market system. The forecasting methodology we propose provides the information needed to solve the problem known as Economic Dispatch with Security Constraints for Multiple Intervals (MISCED). NNLF produces forecasts with a 15-min horizon to support decisions in the following four electric dispatch intervals. The hyperparameters used by Nearest Neighbors are tuned using Differential Evolution (DE), and the forecaster model inputs are determined using phase-space reconstruction. The developed models also use exogenous variables; we append a timestamp to each input (i.e., delay vector). The article presents a comparison between NNLF and other Machine Learning techniques: Artificial Neural Networks and Support Vector Regressors. NNLF outperformed those other techniques and the forecasting system they currently use.

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Soft Computing Methods with Phase Space Reconstruction for Wind Speed Forecasting—A Performance Comparison

Energies ◽

10.3390/en12183545 ◽

2019 ◽

Vol 12 (18) ◽

pp. 3545

Author(s):

Juan. J. Flores ◽

José R. Cedeño González ◽

Héctor Rodríguez ◽

Mario Graff ◽

Rodrigo Lopez-Farias ◽

...

Keyword(s):

Artificial Intelligence ◽

Time Series ◽

Phase Space ◽

Wind Speed ◽

Differential Evolution ◽

Nearest Neighbors ◽

Phase Space Reconstruction ◽

Performance Comparison ◽

Wind Speed Forecasting ◽

Reconstruction Methods

This article presents a comparison of wind speed forecasting techniques, starting with the Auto-regressive Integrated Moving Average, followed by Artificial Intelligence-based techniques. The objective of this article is to compare these methods and provide readers with an idea of what method(s) to apply to solve their forecasting needs. The Artificial Intelligence-based techniques included in the comparison are Nearest Neighbors (the original method, and a version tuned by Differential Evolution), Fuzzy Forecasting, Artificial Neural Networks (designed and tuned by Genetic Algorithms), and Genetic Programming. These techniques were tested against twenty wind speed time series, obtained from Russian and Mexican weather stations, predicting the wind speed for 10 days, one day at a time. The results show that Nearest Neighbors using Differential Evolution outperforms the other methods. An idea this article delivers to the reader is: what part of the history of the time series to use as input to a forecaster? This question is answered by the reconstruction of phase space. Reconstruction methods approximate the phase space from the available data, yielding m (the system’s dimension) and τ (the sub-sampling constant), which can be used to determine the input for the different forecasting methods.

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Adaptive predict-filter of chaotic time series constructed Based on the neighbou rhood in the reconstructed phase space(Ⅰ)linear adaptive filter

Acta Physica Sinica ◽

10.7498/aps.52.1096 ◽

2003 ◽

Vol 52 (5) ◽

pp. 1096

Author(s):

Gan Jian-Chao ◽

Xiao Xian-Ci

Keyword(s):

Time Series ◽

Phase Space ◽

Adaptive Filter ◽

Chaotic Time Series ◽

Reconstructed Phase Space

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A one-dimensional self-gravitating stellar gas

Symposium - International Astronomical Union ◽

10.1017/s0074180900105261 ◽

1966 ◽

Vol 25 ◽

pp. 46-48 ◽

Cited By ~ 2

Author(s):

M. Lecar

Keyword(s):

Gravitational Field ◽

Phase Space ◽

Motion Picture ◽

Space Distribution ◽

Two Dimensional ◽

One Dimensional ◽

Phase Space Distribution ◽

Dimensional Phase Space ◽

The Mean

“Dynamical mixing”, i.e. relaxation of a stellar phase space distribution through interaction with the mean gravitational field, is numerically investigated for a one-dimensional self-gravitating stellar gas. Qualitative results are presented in the form of a motion picture of the flow of phase points (representing homogeneous slabs of stars) in two-dimensional phase space.

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Observation of Superlattice Dislocations on Cube Planes in Ni3Al

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100071314 ◽

1973 ◽

Vol 31 ◽

pp. 174-175 ◽

Cited By ~ 1

Author(s):

J. M. Oblak ◽

W. H. Rand

Keyword(s):

Nearest Neighbor ◽

Antiphase Boundary ◽

Nearest Neighbors ◽

High Energy ◽

Cross Slip ◽

Octahedral Plane ◽

Trapping Mechanism ◽

Slip Traces

The energy of an a/2 <110> shear antiphase. boundary in the Ll2 expected to be at a minimum on {100} cube planes because here strue ture is there is no violation of nearest-neighbor order. The latter however does involve the disruption of second nearest neighbors. It has been suggested that cross slip of paired a/2 <110> dislocations from octahedral onto cube planes is an important dislocation trapping mechanism in Ni3Al; furthermore, slip traces consistent with cube slip are observed above 920°K.Due to the high energy of the {111} antiphase boundary (> 200 mJ/m2), paired a/2 <110> dislocations are tightly constricted on the octahedral plane and cannot be individually resolved.

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Probing vacancies and structural distortions at individual defects in ceramics using EELS

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100165859 ◽

1996 ◽

Vol 54 ◽

pp. 678-679

Author(s):

D. J. Wallis ◽

N. D. Browning

Keyword(s):

Structural Information ◽

Core Loss ◽

Nearest Neighbors ◽

Ceramic Materials ◽

Scanning Transmission Electron Microscope ◽

Real Space ◽

Atomic Scale ◽

Structure Property ◽

Scanning Transmission ◽

Key Issues

In electron energy loss spectroscopy (EELS), the near-edge region of a core-loss edge contains information on high-order atomic correlations. These correlations give details of the 3-D atomic structure which can be elucidated using multiple-scattering (MS) theory. MS calculations use real space clusters making them ideal for use in low-symmetry systems such as defects and interfaces. When coupled with the atomic spatial resolution capabilities of the scanning transmission electron microscope (STEM), there therefore exists the ability to obtain 3-D structural information from individual atomic scale structures. For ceramic materials where the structure-property relationships are dominated by defects and interfaces, this methodology can provide unique information on key issues such as like-ion repulsion and the presence of vacancies, impurities and structural distortion.An example of the use of MS-theory is shown in fig 1, where an experimental oxygen K-edge from SrTiO3 is compared to full MS-calculations for successive shells (a shell consists of neighboring atoms, so that 1 shell includes only nearest neighbors, 2 shells includes first and second-nearest neighbors, and so on).

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