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Search Results: 1 - 10 of 17385 matches for " time-series "
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Weighted Time-Variant Slide Fuzzy Time-Series Models for Short-Term Load Forecasting  [PDF]
Xiaojuan Liu, Enjian Bai, Jian’an Fang
Journal of Intelligent Learning Systems and Applications (JILSA) , 2012, DOI: 10.4236/jilsa.2012.44030
Abstract: Short-term load forecast plays an important role in the day-to-day operation and scheduling of generating units. Season and temperature are the most important factors that affect the load change, but random factors such as big sport events or popular TV shows can change demand consumption in particular hours, which will lead to sudden load changes. A weighted time-variant slide fuzzy time-series model (WTVS) for short-term load forecasting is proposed to improve forecasting accuracy. The WTVS model is divided into three parts, including the data preprocessing, the trend training and the load forecasting. In the data preprocessing phase, the impact of random factors will be weakened by smoothing the historical data. In the trend training and load forecasting phase, the seasonal factor and the weighted historical data are introduced into the Time-variant Slide Fuzzy Time-series Models (TVS) for short-term load forecasting. The WTVS model is tested on the load of the National Electric Power Company in Jordan. Results show that the proposed WTVS model achieves a significant improvement in load forecasting accuracy as compared to TVS models.
An Analysis of the Relationship between Asian Steel Index and the Baltic Capsize Index  [PDF]
Ming-Tao Chou, Yuh-Ling Su, Tsung-Yu Chou, Han-Uei Liang
Modern Economy (ME) , 2015, DOI: 10.4236/me.2015.62018
Abstract: The Asian Steel Index (ASI) and Baltic Capsize Index (BCI)are important indices of the tramp shipping industry, where the BCI index reveals both the current tramp maritime transport fare and market status, while the ASI index is a composite index determined by the trade prices of steel. This paper first reviewed the literature of ASI and BCI indices to illustrate the current composition of the ASI index, as well as the BCI index in the present tramp maritime industry. A time-series analysis was then followed to construct the optimum model of ASI and BCI indices, and the results could be used as references for the maritime industry. According to the formulation of the multivariate time series models, the optimal mode was found to be VARMA (2,4), which meant that both the ASI and BCI indices would be affected by previous two series of data and have the error correction effect of 4 series. The results of this study confirm that ASI and BCI indices have impacts on each other, especially for the maritime zones of the BCI index, which are consistent with the status of China, a big country with high demands for raw steel material. Furthermore, this model allows the user to discover the impact multiplier of both indices. The construction of the model is hoped to help provide a reference for academics and businesses in the shipping industry.
RETRACTED: A Participatory Iterative Mapping Approach and Evaluation of Three Machine Learning Algorithms for Accurate Mapping of Cropping Patterns in a Complex Agro-Ecosystems  [PDF]
Gudina Legese Feyisa, Leo Palao, Andy Nelson, Khin Thawda Win, Kin Nge Htar, Murali Krishna Gumma, David E. Johnson
Advances in Remote Sensing (ARS) , 2016, DOI: 10.4236/ars.2016.51001
Abstract: Short Retraction Notice

This article has been retracted according to COPE's Retraction Guidelines. Since authors have their personal reasons, they have to withdraw this paper from journal Advances in Remote Sensing.

The full retraction notice in PDF is preceding the original paper which is marked \"RETRACTED\".
Speed Limit and Fatalities in the U.S.: Implication for Transportation Policy  [PDF]
Kashif Zaheer Malik, Ammar Aftab
Theoretical Economics Letters (TEL) , 2017, DOI: 10.4236/tel.2017.75094
The paper attempts to investigate into the prevalent notion that higher speed limits lead to increase in fatalities using Vector Auto Regressive (VAR) model for bivariate time series. The paper used Fatality Analysis Reporting System (FARS) time series data set from 1975 to 2010. The paper is the first one to make use of Vector Autoregressive Model (VAR) on this time series dataset to study the potential dual causality between speed and fatalities. The results of the paper partially support the causation between speed limit and fatalities, thus, complementing the results of the existing literature relating speed limits and fatalities such as “Influence of speed limits on roadway safety in Indiana” [1], “Driver Speed Behavior on US Streets” [2], and “Speed Limit Laws in America: Economics, Politics and Geography” [3]. However, instead of determining causation through various regression models, the paper establishes the causality by inducing a speed shock and analyses its impact upon fatalities. The paper concludes that in states with higher per capita automobiles and limited public transportation facilities such as Georgia, a sudden increase in speed limit has an immediate and higher impact upon accident related deaths, whereas, in states with lower per capita automobiles and higher public transportation services such as New York, the sudden increase of speed limit has minimal impact on accident related fatalities.
Time Optimal Control in Time Series Movement  [PDF]
Ognjen Vukovic
Journal of Applied Mathematics and Physics (JAMP) , 2015, DOI: 10.4236/jamp.2015.39139
Abstract: The paper analyses time series that exhibit equilibrium states. It analyses the formation of equilibrium and how the system can return to the aforementioned equilibrium. The tool that is used in the aforementioned analysis is time optimal control in the phase plane. It is proved that equilibrium state is sustainable if initial state is not too far from the equilibrium as well as control vector is large enough. On the other hand, if initial state is one standard deviation away from equilibrium state, it is proved that equilibrium cannot be reached. It is the same case with control vector. If it is unbounded, time optimal control cannot be applied. The approach that is introduced represents unconventional method of analysing equilibrium in time series.
Economic Interdependence: Evidence from China and ASEAN-5 Countries  [PDF]
Arunnan Balasubramaniam, Chin-Hong Puah, Shazali Abu Mansor
Modern Economy (ME) , 2012, DOI: 10.4236/me.2012.31017
Abstract: This study aimed to examine the interdependence relationship among five Association of Southeast Asian Nations (ASEAN-5) countries (Indonesia, Malaysia, the Philippines, Singapore, and Thailand) and China from a business cycles perspective. The Granger non-causality test proposed by [1] was used to examine causal linkages in business cycles. The empirical results indicated common business cycles between China and ASEAN-5 economies. This suggested that China and ASEAN-5 share similar business cycles and could complement each other in the long run. A discussion of important insights for regional economic policy coordination in which similar business cycles provide a platform for common regional trade, as well as suggestions for monetary policies, conclude the paper.
A Semi Automated Method for Laminated Sediments Analysis  [PDF]
Mapathe Ndiaye, Eric Davaud, Daniel Ariztegui, Meissa Fall
International Journal of Geosciences (IJG) , 2012, DOI: 10.4236/ijg.2012.31023
Abstract: We developed a software performing laminae counting, thickness measurements, spectral and wavelet analysis of laminated sediments embedded signal. We validated the software on varved sediments. Varved laminae are automatically counted using an image analysis classification method based on K-Nearest Neighbors (KNN) algorithm. In a next step, the signal corresponding to varved black laminae thickness variation is retrieved. The obtained signal is a good proxy to study the paleoclimatic constraints controlling sedimentation. Finally, the use of spectral and wavelet analysis methods on the variation of black laminae thickness revealed the existence of frequencies and periods which can be linked to known paleoclimatic events.
On Extracting Probability Distribution Information from Time Series
Andres M. Kowalski,Maria Teresa Martin,Angelo Plastino,George Judge
Entropy , 2012, DOI: 10.3390/e14101829
Abstract: Time-series (TS) are employed in a variety of academic disciplines. In this paper we focus on extracting probability density functions (PDFs) from TS to gain an insight into the underlying dynamic processes. On discussing this “extraction” problem, we consider two popular approaches that we identify as histograms and Bandt–Pompe. We use an information-theoretic method to objectively compare the information content of the concomitant PDFs.
Sesgos en estimación, tama?o y potencia de una prueba sobre el parámetro de memoria larga en modelos ARFIMA
Casta?o,Elkin; Gallón,Santiago; Gómez,Karoll;
Lecturas de Economía , 2010,
Abstract: casta?o et al. (2008) proposed a test to investigate the existence of long memory based on the fractional differencing parameter of an arfima (p, d, q) model. they showed that using an autoregressive approximation with order equal to the nearest integer of p* = t1/3 for the short-term component of this model, the test for the short memory null hypothesis against the long memory alternative hypothesis has greater power than other long memory tests, and also has an adequate size. we studied the estimation bias generated on d, and the effect on the power and size of the test when the short-term component is ignored and when the used models do not approximate it adequately. additionally we analyze whether the obtained results by casta?o et al. (2008) can be improved employing a different autoregressive approximation.
Opini?o pública, estratégia presidencial e a??o do congresso no Brasil: "quem manda?"
Pereira, Carlos;Power, Timothy;Rennó, Lúcio;
Opini?o Pública , 2005, DOI: 10.1590/S0104-62762005000200005
Abstract: the relationship between elite behavior and mass preferences is in the essence of discussions about representative democracy. however, very little is known about who influences whom and how long it takes for such influence to be felt. this article presents results from a time-series dataset that allows us to verify the relationship between the mood of public opinion, presidents' choice of policy making instrument (extraordinary vs. ordinary legislation) and congressional support to presidents' policy initiatives in brazil. we collected monthly observations of presidential popularity, patterns of roll-call voting in congress and presidents use of "medidas provisórias" as well as regular legislation. this dataset allows us to test, using time-series techniques, the impact of these variables on each other and the amount of lags it takes for these impacts to become significant.
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