Journal articles on the topic 'Mixed frequency time series'
To see the other types of publications on this topic, follow the link: Mixed frequency time series.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Mixed frequency time series.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Götz, Thomas B., Alain Hecq, and Jean-Pierre Urbain. "Forecasting Mixed-Frequency Time Series with ECM-MIDAS Models." Journal of Forecasting 33, no. 3 (March 3, 2014): 198–213. http://dx.doi.org/10.1002/for.2286.
Full text
2
Ghysels, Eric, and J. Isaac Miller. "Testing for Cointegration with Temporally Aggregated and Mixed-Frequency Time Series." Journal of Time Series Analysis 36, no. 6 (March 9, 2015): 797–816. http://dx.doi.org/10.1111/jtsa.12129.
Full text
3
Miller, J. Isaac. "Conditionally Efficient Estimation of Long-Run Relationships Using Mixed-Frequency Time Series." Econometric Reviews 35, no. 6 (October 20, 2014): 1142–71. http://dx.doi.org/10.1080/07474938.2014.976527.
Full text
4
Seong, Byeongchan. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models." Economic Modelling 91 (September 2020): 463–68. http://dx.doi.org/10.1016/j.econmod.2020.06.020.
Full text
5
Tank, A., E. B. Fox, and A. Shojaie. "Identifiability and estimation of structural vector autoregressive models for subsampled and mixed-frequency time series." Biometrika 106, no. 2 (April 8, 2019): 433–52. http://dx.doi.org/10.1093/biomet/asz007.
Full textAbstract:
Summary Causal inference in multivariate time series is challenging because the sampling rate may not be as fast as the time scale of the causal interactions, so the observed series is a subsampled version of the desired series. Furthermore, series may be observed at different sampling rates, yielding mixed-frequency series. To determine instantaneous and lagged effects between series at the causal scale, we take a model-based approach that relies on structural vector autoregressive models. We present a unifying framework for parameter identifiability and estimation under subsampling and mixed frequencies when the noise, or shocks, is non-Gaussian. By studying the structural case, we develop identifiability and estimation methods for the causal structure of lagged and instantaneous effects at the desired time scale. We further derive an exact expectation-maximization algorithm for inference in both subsampled and mixed-frequency settings. We validate our approach in simulated scenarios and on a climate and an econometric dataset.
6
Götz, Thomas B., and Klemens Hauzenberger. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure." Econometrics Journal 24, no. 3 (January 16, 2021): 442–61. http://dx.doi.org/10.1093/ectj/utab001.
Full textAbstract:
Summary In order to simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural change, we introduce a time-varying parameter mixed-frequency vector autoregression (VAR). Time variation enters in a parsimonious way: only the intercepts and a common factor in the error variances can vary. Computational complexity therefore remains in a range that still allows us to estimate moderately large VARs in a reasonable amount of time. This makes our model an appealing addition to any suite of forecasting models. For eleven U.S. variables, we show the competitiveness compared to a commonly used constant-coefficient mixed-frequency VAR and other related model classes. Our model also accurately captures the drop in the gross domestic product during the COVID-19 pandemic.
7
Khiabani, Naser, and Fateme Rajabi. "Modeling with Mixed Frequency Variables: A Review of Recently Extended Methods in Time Series Econometrics." Journal of Planning and Budgeting 24, no. 2 (September 1, 2019): 3–30. http://dx.doi.org/10.29252/jpbud.24.2.3.
Full text
8
Belovas, Igoris, Leonidas Sakalauskas, Vadimas Starikovičius, and Edward W. Sun. "Mixed-Stable Models: An Application to High-Frequency Financial Data." Entropy 23, no. 6 (June 11, 2021): 739. http://dx.doi.org/10.3390/e23060739.
Full textAbstract:
The paper extends the study of applying the mixed-stable models to the analysis of large sets of high-frequency financial data. The empirical data under review are the German DAX stock index yearly log-returns series. Mixed-stable models for 29 DAX companies are constructed employing efficient parallel algorithms for the processing of long-term data series. The adequacy of the modeling is verified with the empirical characteristic function goodness-of-fit test. We propose the smart-Δ method for the calculation of the α-stable probability density function. We study the impact of the accuracy of the computation of the probability density function and the accuracy of ML-optimization on the results of the modeling and processing time. The obtained mixed-stable parameter estimates can be used for the construction of the optimal asset portfolio.
9
Martínez-Ortiz, Pedro A., and José M. Ferrándiz. "A New Algorithm to Accelerate Harmonic Analysis of Time Series." ISRN Applied Mathematics 2013 (February 11, 2013): 1–8. http://dx.doi.org/10.1155/2013/916731.
Full textAbstract:
The Lomb periodogram has been traditionally a tool that allows us to elucidate if a frequency turns out to be important for explaining the behaviour of a given time series. Many linear and nonlinear reiterative harmonic processes that are used for studying the spectral content of a time series take into account this periodogram in order to avoid including spurious frequencies in their models due to the leakage problem of energy from one frequency to others. However, the estimation of the periodogram requires long computation time that makes the harmonic analysis slower when we deal with certain time series. Here we propose an algorithm that accelerates the extraction of the most remarkable frequencies from the periodogram, avoiding its whole estimation of the harmonic process at each iteration. This algorithm allows the user to perform a specific analysis of a given scalar time series. As a result, we obtain a functional model made of (1) a trend component, (2) a linear combination of Fourier terms, and (3) the so-called mixed secular terms by reducing the computation time of the estimation of the periodogram.
10
FRANCO, Ray John Gabriel, and Dennis S. MAPA. "ANALYZING THE DYNAMICS OF GROSS DOMESTIC PRODUCT GROWTH. A MIXED FREQUENCY MODEL APPROACH." Theoretical and Practical Research in the Economic Fields 5, no. 2 (December 31, 2014): 117. http://dx.doi.org/10.14505/tpref.v5.2(10).01.
Full textAbstract:
Frequency mismatch has been a problem in time series econometrics. Many monthly economic and financial indicators are normally aggregated to match quarterly macroeconomic series such as Gross Domestic Product when performing econometric analysis. However, temporal aggregation, although widely accepted, is prone to information loss. To address this issue, mixed frequency modelling is employed by using state space models with time-varying parameters. Quarter-on-quarter growth rate of GDP estimates are treated as monthly series with missing observation. Using Kalman filter algorithm, state space models are estimated with eleven monthly economic indicators as explanatory variables. A one-step-ahead forecast for GDP growth rates is generated and as more indicators are included in the model, the predicted values became closer to the actual data. Further evaluation revealed that among the group competing models, using Consumer Price Index (CPI), growth rates of Philippine Stock Exchange Index (PSEi), Exchange Rate, Real Money Supply, Wholesale Price Index (WPI) and Merchandise Exports are the more important determinants of GDP growth and generated the most desirable forecasts (lower forecast errors).
11
Yang, Ranran, Lei Wang, Qingjiu Tian, Nianxu Xu, and Yanjun Yang. "Estimation of the Conifer-Broadleaf Ratio in Mixed Forests Based on Time-Series Data." Remote Sensing 13, no. 21 (November 3, 2021): 4426. http://dx.doi.org/10.3390/rs13214426.
Full textAbstract:
Most natural forests are mixed forests, a mixed broadleaf-conifer forest is essentially a heterogeneously mixed pixel in remote sensing images. Satellite missions rely on modeling to acquire regional or global vegetation parameter products. However, these retrieval models often assume homogeneous conditions at the pixel level, resulting in a decrease in the inversion accuracy, which is an issue for heterogeneous forests. Therefore, information on the canopy composition of a mixed forest is the basis for accurately retrieving vegetation parameters using remote sensing. Medium and high spatial resolution multispectral time-series data are important sources for canopy conifer-broadleaf ratio estimation because these data have a high frequency and wide coverage. This paper highlights a successful method for estimating the conifer-broadleaf ratio in a mixed forest with diverse tree species and complex canopy structures. Experiments were conducted in the Purple Mountain, Nanjing, Jiangsu Province of China, where we collected leaf area index (LAI) time-series and forest sample plot inventory data. Based on the Invertible Forest Reflectance Model (INFORM), we simulated the normalized difference vegetation index (NDVI) time-series of different conifer-broadleaf ratios. A time-series similarity analysis was performed to determine the typical separable conifer-broadleaf ratios. Fifteen Gaofen-1 (GF-1) satellite images of 2015 were acquired. The conifer-broadleaf ratio estimation was based on the GF-1 NDVI time-series and semi-supervised k-means cluster method, which yielded a high overall accuracy of 83.75%. This study demonstrates the feasibility of accurately estimating separable conifer-broadleaf ratios using field measurement data and GF-1 time series in mixed broadleaf-conifer forests.
12
김현석. "The forecasting evaluation of the high-order mixed frequency time series model to the marine industry." Journal of Shipping and Logistics 35, no. 1 (March 2019): 93–109. http://dx.doi.org/10.37059/tjosal.2019.35.1.93.
Full text
13
Anderson, Brian D. O., Manfred Deistler, Elisabeth Felsenstein, Bernd Funovits, Lukas Koelbl, and Mohsen Zamani. "MULTIVARIATE AR SYSTEMS AND MIXED FREQUENCY DATA: G-IDENTIFIABILITY AND ESTIMATION." Econometric Theory 32, no. 4 (April 2, 2015): 793–826. http://dx.doi.org/10.1017/s0266466615000043.
Full textAbstract:
This paper is concerned with the problem of identifiability of the parameters of a high frequency multivariate autoregressive model from mixed frequency time series data. We demonstrate identifiability for generic parameter values using the population second moments of the observations. In addition we display a constructive algorithm for the parameter values and establish the continuity of the mapping attaching the high frequency parameters to these population second moments. These structural results are obtained using two alternative tools viz. extended Yule Walker equations and blocking of the output process. The cases of stock and flow variables, as well as of general linear transformations of high frequency data, are treated. Finally, we briefly discuss how our constructive identifiability results can be used for parameter estimation based on the sample second moments.
14
Shi, Sheng-zhe, Ting Jiang, Fan Wang, and Xiao-long Zheng. "Study on the Measured Signal Analysis Method Based on Sine Curve-fit Method for Ship Model Seakeeping Test." Journal of Physics: Conference Series 2419, no. 1 (January 1, 2023): 012030. http://dx.doi.org/10.1088/1742-6596/2419/1/012030.
Full textAbstract:
Abstract Ship model seakeeping test measure data included frequency ponderances of syntonic waves, mixed waves, and white noise, which affect the test result. Heave time series and pitch time series of planning hull model seakeeping test are calculated by the three-parameter sine wave curve-fit method. Amplitude, angular frequency, and phase angle are obtained. The result shows that the distortion degrees of heave and pitch decrease gradually with an increase in wavelength; when the test wavelength is 8.8m, the distortion degrees of heave and pitch are the smallest, which reach 2.79% and 4.69%; however, at a wavelength of 11m, the distortion degrees of heave and pitch increase.
15
Li, Xinxin, Xixia Ma, Xiaodong Li, and Wenjiang Zhang. "Method Consideration of Variation Diagnosis and Design Value Calculation of Flood Sequence in Yiluo River Basin, China." Water 12, no. 10 (September 29, 2020): 2722. http://dx.doi.org/10.3390/w12102722.
Full textAbstract:
The conventional approaches of the design flood calculation are based on the assumption that the hydrological time series is subject to the same distribution in the past, present, and future, i.e., the series should be consistent. However, the traditional methods may result in overdesign in the water conservancy project since the series has non-stationary variations due to climate change and human activities. Therefore, it is necessary to develop a new approach for frequency estimation of non-stationary time series of extreme values. This study used four kinds of mutation test methods (the linear trend correlation coefficient, Mann–Kendall test, sliding t-test, and Pettitt test) to identify the trend and mutation of the annual maximum flow series (1950–2006) of three hydrological stations in the Yiluo River Basin. Then we evaluated the performance of two types of design flood methods (the time series decomposition-synthesis method, the mixed distribution model) under the impacts of climate change and human activities on hydro-meteorological conditions. The results showed that (a) the design flood value obtained by the time series decomposition-synthesis method based on the series of the backward restore is larger than that obtained by the decomposition synthesis method based on the series of the forward restore; (b) when the return period is 100 years or less, the design flood value obtained by the mixed distribution model using the capacity ratio parameter estimation method is less than that obtained by the hybrid distribution model with simulated annealing parameter estimation method; and (c) both methods can overcome sequence inconsistency in design frequencies. This study provides insight into the frequency estimation of non-stationary time series of extreme values under the impacts of climate change and human activities on hydro-meteorological conditions.
16
Li, Jianzhu, Yanchen Zheng, Yimin Wang, Ting Zhang, Ping Feng, and Bernard Engel. "Improved Mixed Distribution Model Considering Historical Extraordinary Floods under Changing Environment." Water 10, no. 8 (July 31, 2018): 1016. http://dx.doi.org/10.3390/w10081016.
Full textAbstract:
Historical extraordinary floods are an important factor in non-stationary flood frequency analysis and they may occur at any time, regardless of whether the environment is changing or not. Based on mixed distribution (MD) modeling, this paper proposed an improved mixed distribution (IMD) model to consider the discontinuity and non-stationarity of flood samples simultaneously, which adds historical extraordinary floods in both sub-series divided by a change point. As a case study, the annual maximum peak discharge and volume series of Ankang hydrological station, located in the upper Hanjiang River Basin of China, were selected to identify non-stationarity by using the variation diagnosis system. MD and IMD were used to fit the flood characteristic series and a genetic algorithm was employed to estimate the optimal parameters. Compared with the design flood values fitted by the stationary Pearson type-III distribution, the results computed by IMD decreased at low return periods and increased at high return periods, with the difference varying from −6.67% to 7.19%. The results highlighted that although the design flood values of IMD are slightly larger than those of MD with different return periods, IMD provided a better result than MD. IMD provides a new perspective for non-stationary flood frequency analysis.
17
Permutt, S., W. Mitzner, and G. Weinmann. "Model of gas transport during high-frequency ventilation." Journal of Applied Physiology 58, no. 6 (June 1, 1985): 1956–70. http://dx.doi.org/10.1152/jappl.1985.58.6.1956.
Full textAbstract:
We analyze gas exchange during high-frequency ventilation (HFV) by a stochastic model that divides the dead space into N compartments in series where each compartment has a volume equal to tidal volume (V). We then divide each of these compartments into alpha subcompartments in series, where each subcompartment receives a well-mixed concentration from one compartment and passes a well-mixed concentration to another in the direction of flow. The number of subcompartments is chosen on the basis that 1/alpha = (sigma t/-t)2, where -t is mean transit time across a compartment of volume, and sigma t is standard deviation of transit times. If (sigma t/-t)D applies to the transit times of the entire dead space, the magnitude of gas exchange is proportional to (sigma t/-t)D, frequency, and V raised to some power greater than unity in the range where V is close to VD. When V is very small in relation to VD, gas exchange is proportional to (sigma t/-t)2D, frequency, and V raised to a power equal to either one or two depending on whether the flow is turbulent or streamline, respectively. (sigma t/-t)D can be determined by the relation between the concentration of alveolar gas at the air outlet and volume expired as in a Fowler measurement of the volume of the dead space.
18
Shojaie, Ali, and Emily B. Fox. "Granger Causality: A Review and Recent Advances." Annual Review of Statistics and Its Application 9, no. 1 (March 7, 2022): 289–319. http://dx.doi.org/10.1146/annurev-statistics-040120-010930.
Full textAbstract:
Introduced more than a half-century ago, Granger causality has become a popular tool for analyzing time series data in many application domains, from economics and finance to genomics and neuroscience. Despite this popularity, the validity of this framework for inferring causal relationships among time series has remained the topic of continuous debate. Moreover, while the original definition was general, limitations in computational tools have constrained the applications of Granger causality to primarily simple bivariate vector autoregressive processes. Starting with a review of early developments and debates, this article discusses recent advances that address various shortcomings of the earlier approaches, from models for high-dimensional time series to more recent developments that account for nonlinear and non-Gaussian observations and allow for subsampled and mixed-frequency time series.
19
Schreyer, Frederic, and Remco I. Leine. "A Mixed Shooting – Harmonic Balance Method for Unilaterally Constrained Mechanical Systems." Archive of Mechanical Engineering 63, no. 2 (June 1, 2016): 297–314. http://dx.doi.org/10.1515/meceng-2016-0017.
Full textAbstract:
Abstract In this paper we present a mixed shooting – harmonic balance method for large linear mechanical systems on which local nonlinearities are imposed. The standard harmonic balance method (HBM), which approximates the periodic solution in frequency domain, is very popular as it is well suited for large systems with many degrees of freedom. However, it suffers from the fact that local nonlinearities cannot be evaluated directly in the frequency domain. The standard HBM performs an inverse Fourier transform, then calculates the nonlinear force in time domain and subsequently the Fourier coefficients of the nonlinear force. The disadvantage of the HBM is that strong nonlinearities are poorly represented by a truncated Fourier series. In contrast, the shooting method operates in time-domain and relies on numerical time-simulation. Set-valued force laws such as dry friction or other strong nonlinearities can be dealt with if an appropriate numerical integrator is available. The shooting method, however, becomes infeasible if the system has many states. The proposed mixed shooting-HBM approach combines the best of both worlds.
20
Rezaul Karim, A. N. M. "Effect of Mixed Spikes on Different Types of Complex Waves." Journal of Mathematics Research 11, no. 6 (November 19, 2019): 70. http://dx.doi.org/10.5539/jmr.v11n6p70.
Full textAbstract:
This article treats analytically. This paper presents a novel approach to complex waves. This article outlines the understanding of the various effects of spike representations used to make models of the predictive variable effects of the second-order portion of power while revealing the relationship between the time series segments that are recorded from a single unit. MATLAB has been used to show the effects of mixed spikes in graphs. The resulting power portion has varied representation effects in which both the random and fixed effects are expressed as functions of the frequency domain.
21
Konno, Hiroki, Adrian Dobroiu, Safumi Suzuki, Masahiro Asada, and Hiroshi Ito. "Discrete Fourier Transform Radar in the Terahertz-Wave Range Based on a Resonant-Tunneling-Diode Oscillator." Sensors 21, no. 13 (June 25, 2021): 4367. http://dx.doi.org/10.3390/s21134367.
Full textAbstract:
We used a resonant-tunneling-diode (RTD) oscillator as the source of a terahertz-wave radar based on the principle of the swept-source optical coherence tomography (SS-OCT). Unlike similar reports in the terahertz range, we apply the stepwise frequency modulation to a subcarrier obtained by amplitude modulation instead of tuning the terahertz carrier frequency. Additionally, we replace the usual optical interference with electrical mixing and, by using a quadrature mixer, we can discriminate between negative and positive optical path differences, which doubles the measurement range without increasing the measurement time. To measure the distance to multiple targets simultaneously, the terahertz wave is modulated in amplitude at a series of frequencies; the signal returning from the target is detected and homodyne mixed with the original modulation signal. A series of voltages is obtained; by Fourier transformation the distance to each target is retrieved. Experimental results on one and two targets are shown.
22
Bardet, L., C. M. Duluc, V. Rebour, and J. L'Her. "Regional frequency analysis of extreme storm surges along the French coast." Natural Hazards and Earth System Sciences 11, no. 6 (June 14, 2011): 1627–39. http://dx.doi.org/10.5194/nhess-11-1627-2011.
Full textAbstract:
Abstract. A good knowledge of extreme storm surges is necessary to ensure protection against flood. In this paper we introduce a methodology to determine time series of skew surges in France as well as a statistical approach for estimating extreme storm surges. With the aim to cope with the outlier issue in surge series, a regional frequency analysis has been carried out for the surges along the Atlantic coast and the Channel coast. This methodology is not the current approach used to estimate extreme surges in France. First results showed that the extreme events identified as outliers in at-site analyses do not appear to be outliers any more in the regional empirical distribution. Indeed the regional distribution presents a curve to the top with these extreme events that a mixed exponential distribution seems to recreate. Thus, the regional approach appears to be more reliable for some sites than at-site analyses. A fast comparison at a given site showed surge estimates with the regional approach and a mixed exponential distribution are higher than surge estimates with an at-site fitting. In the case of Brest, the 1000-yr return surge is 167 cm in height with the regional approach instead of 126 cm with an at-site analysis.
23
Lozano, Wilson, Conrado Calvo, Oscar Arias-Mutis, Ana Díaz, Luis Such-Miquel, Jichao Zhao, Antonio Alberola, Francisco Chorro, and Manuel Zarzoso. "Diet-Induced Metabolic Syndrome Reduced Heart Rate Variability and Increased Irregularity and Complexity of Short-Term RR Time Series in Rabbits." Animals 9, no. 8 (August 18, 2019): 572. http://dx.doi.org/10.3390/ani9080572.
Full textAbstract:
Metabolic syndrome (MetS) has been linked to a higher prevalence of sudden cardiac death (SCD), but the mechanisms are not well understood. One possible underlying mechanism may be an abnormal modulation of autonomic activity, which can be quantified by analyzing heart rate variability (HRV). Our aim was to investigate the modifications of short-term HRV in an experimental rabbit model during the time-course of MetS development. NZW rabbits were randomly assigned to a control (n = 10) or a MetS group (n = 13), fed 28 weeks with control or high-fat, high-sucrose diets. After anesthesia, a 15-min ECG recording was acquired before diet administration and at weeks 14 and 28. We analyzed short RR time series using time-domain, frequency-domain and nonlinear analyses. A mixed-model factorial ANOVA was used for statistical analysis. Time-domain analysis showed a 52.4% decrease in the standard deviation of heart rate in animals from the MetS group at week 28, but no changes in the rest of parameters. In the frequency domain, we found a 9.7% decrease in the very low frequency and a 380.0% increase of the low frequency bands in MetS animals at week 28, whereas high frequency remained unchanged. Nonlinear analyses showed increased complexity and irregularity of the RR time series in MetS animals.
24
Carlucci, Margherita, Ilaria Zambon, Andrea Colantoni, and Luca Salvati. "Socioeconomic Development, Demographic Dynamics and Forest Fires in Italy, 1961–2017: A Time-Series Analysis." Sustainability 11, no. 5 (March 1, 2019): 1305. http://dx.doi.org/10.3390/su11051305.
Full textAbstract:
Empirical studies investigating long-term trends in wildfires’ frequency and severity have been relatively scarce in Europe. Number of fire events, total burnt area and average fire size were studied between 1961 and 2017 in Italy with the aim to identify homogeneous time periods with similar wildfire frequency and severity and correlate them with the background socioeconomic context. Fire attributes had a diverging behavior over time: the number of fires was the highest in the 1970s and the early 1980s; total burnt area was relatively more constant over time with a peak in the 1980s; and, finally, average fire size decreased quite homogeneously from the peak observed in the 1960s and early 1970s. The number of fires and average fire size were significantly influenced by the value of the same variable one year before. Investigating long-term historical outlines of forest fires, a mixed approach based on time-series statistical analysis, multivariate techniques and regressive models intended to define changes in fire regimes and socioeconomic development. In fact, the comparative valuation of the socioeconomic aspects and wildfire trends can reveal a key step to recognizing mitigation and preventive possibilities. Through a multivariate analysis, a substantial difference in the socioeconomic profile can emerge by decade, evidencing a (more or less) rapid socioeconomic development in relation to the evolution of forest fires in Italy.
25
Dharmadhikari, Susheel, Riddhiman Raut, Asok Ray, and Amrita Basak. "A Unified Mixed Deep Neural Network for Fatigue Damage Detection in Components with Different Stress Concentrations." Applied Sciences 13, no. 3 (January 25, 2023): 1542. http://dx.doi.org/10.3390/app13031542.
Full textAbstract:
The article presents a mixed deep neural network (DNN) approach for detecting micron-scale fatigue damage in high-strength polycrystalline aluminum alloys. Fatigue testing is conducted using a custom-designed apparatus integrated with a confocal microscope and a moving stage to accurately pinpoint the instance of micron-scale crack emergence. The specimens are monitored throughout the duration of the experiment using a pair of high-frequency ultrasonic transducers. The mixed DNN is trained with ultrasonic time-series data that are obtained from two sets of specimens categorized by different stress concentration factors. To understand the effects of mixing the data from both types of specimens, a parametric analysis is performed by varying the amount of training data from each specimen to develop a series of mixed DNNs. The mixed DNN, when tested on unseen data from both specimens, exhibits an accuracy of over 95%. This article, therefore, demonstrates a successful alternative to customized DNNs for new types, geometries, or stress concentration factors in the materials under consideration.
26
Zhou, A. Y. "Amplitude and Period Changes in the δ Sct Star AN Lyncis." International Astronomical Union Colloquium 185 (2002): 332–33. http://dx.doi.org/10.1017/s0252921100016390.
Full textAbstract:
AbstractWe report a study of time-dependent behaviour of the light variations in the δ Set star AN Lyn, based on an analysis of new time-series CCD observations and existing data. The amplitude of the main frequency increased from 1994 to 2000 at a rate of 0.006 mmag/yr. The light variation of AN Lyn can be explained currently by amplitude variability mixed with multiperiodic pulsation. With the extended data base, results on XX Cyg are also reported.
27
Jung, Ranu, and Min Shao. "Robustness of coarse graining spectral analysis in estimating frequency and Hurst exponent from mixed time series with harmonic and fractal components." Neurocomputing 32-33 (June 2000): 1055–63. http://dx.doi.org/10.1016/s0925-2312(00)00279-4.
Full text
28
Zizzo, Anne Rahbek, Ida Kirkegaard, Niels Uldbjerg, John Hansen, and Henning Mølgaard. "Towards better reliability in fetal heart rate variability using time domain and spectral domain analyses. A new method for assessing fetal neurological state?" PLOS ONE 17, no. 3 (March 1, 2022): e0263272. http://dx.doi.org/10.1371/journal.pone.0263272.
Full textAbstract:
Objectives Fetal heart rate variability (FHRV) has shown potential in fetal surveillance. Therefore, we aimed to evaluate the reliability of time domain and spectral domain parameters based on non-invasive fetal electrocardiography (NI-FECG). Method NI-FECG, with a sampling frequency of 1 kHz, was obtained in 75 healthy, singleton pregnant women between gestational age (GA) 20+0 to 41+0. The recording was divided into a) heart rate pattern (HRP) and b) periods fulfilling certain criteria of stationarity of RR-intervals, termed stationary heart rate pattern (SHRP). Within each recording, the first and the last time series from each HRP with less than 5% artifact correction were analyzed and compared. Standard deviation of normal-to-normal RR-intervals (SDNN), root mean square of successive differences (RMSSD), high frequency power (HF-power), low frequency power (LF-power), and LF-power/HF-power were performed. A multivariate mixed model was used and acceptable reliability was defined as intraclass correlation coefficient (ICC) ≥ 0.80 and a coefficient of variation (CV) ≤ 15%. Based on these results, the CV and ICC were computed if the average of two to six time series was used. Results For GA 28+0 to 34+6, SDNN and RMSSD exhibited acceptable reliability (CV < 15%; ICC > 90%), whereas GA 35+0 to 41+0and 20+0 to 27+6 showed higher CVs. Spectral domain parameters also showed high CVs However, by using the mean value of two to six time series, acceptable reliability in SDNN, RMSSD and HF-power from GA 28+0 was achieved. Stationarity of RR-intervals showed high influence on reliability and SHRP was superior to HRP, whereas the length of the time series showed minor influence. Conclusion Acceptable reliability seems achievable in SDNN, RMSSD and HF-power from gestational week 28. However, stationarity of RR-intervals should be considered when selecting time series for analyses.
29
XIE, Xintao, Hao LI, Liqiang PAN, Shuai XIAO, Mengjiao LI, and Zhenyu WU. "Research on Economics of Mixed Energy Storage for Smoothing Wind Power Fluctuation with Consideration of Confidence Level." MATEC Web of Conferences 232 (2018): 04055. http://dx.doi.org/10.1051/matecconf/201823204055.
Full textAbstract:
This paper proposes a research method for mitigating wind power fluctuations in a hybrid energy storage system considering the confidence level of wind power volatility. First, the typical daily wind power output is subjected to Fourier spectrum analysis to determine the frequency range of wind power output, and combined with low-pass filtering to find the optimal cutoff frequency, for obtaining energy storage reference power; Then determining the optimal energy storage reference power by comparing the energy storage reference powers solved at different confidence levels. Finally, empirical mode decomposition (EMD) is used to decompose the stored energy into a series of intrinsic mode functions(IMFs), demarcation of the energy storage reference power with minimum aliasing in the instantaneous frequency-time curve, the high frequency part is configured by power type energy storage, and the low frequency part is configured by energy type energy storage. The simulation of the wind farms in a certain area of Hunan Province is carried out. The result shows that proper reduction of confidence level can reduce energy storage power and capacity.
30
Kenney, Bernard C. "Under-Ice Circulation and the Residence Time of a Shallow Bay." Canadian Journal of Fisheries and Aquatic Sciences 48, no. 1 (January 1, 1991): 152–62. http://dx.doi.org/10.1139/f91-021.
Full textAbstract:
Vertical temperature profiles measured along the axis of Wupaw Bay in March of three consecutive years showed that the water column was inversely stratified under ice. The depth of the (inverse) thermocline varied monotonically along the length of the bay, with the most rapid change occurring in the channel connecting the bay to Southern Indian Lake. Using prototype instrumentation, the associated two-layer current in the connecting channel was measured. The current near bottom often exceeded 1 cm/s and was directed out of the bay. The upper layer current generally flowed into the bay but was more variable than the bottom current and at times reversed direction. Although the circulation is relatively weak, the water exchange through the channel makes an important contribution to the residence time of water in Wupaw Bay during March. A short (2 h) time series showed that the temperature structure was highly variable below the surface mixed layer. High-frequency random fluctuations in temperature were observed together with active overturning events indicative of significant levels of turbulence under ice. Nonlinear effects also dominated regions with the largest temperature gradients where temperature oscillations appeared wavelike but were higher in frequency than the measured Brunt–Vaisala frequency.
31
Paulik, Georgie, Craig Steel, and Arnoud Arntz. "Imagery rescripting for the treatment of trauma in voice hearers: a case series." Behavioural and Cognitive Psychotherapy 47, no. 6 (April 12, 2019): 709–25. http://dx.doi.org/10.1017/s1352465819000237.
Full textAbstract:
AbstractBackground: High rates of trauma and post-traumatic stress disorder (PTSD) are reported in people who hear voices (auditory hallucinations). A recent meta-analysis of trauma interventions in psychosis showed only small improvements in PSTD symptoms and voices. Imagery Rescripting (ImRs) may be a therapy that is more effective in this population because it generalizes over memories, which is ideal in this population with typically repeated traumas.Aims: The primary aims of this study were to investigate whether ImR reduces (1) PTSD symptoms, and (2) voice frequency and distress in voice hearers.Method: We used a single arm open trial study, case-series design. Twelve voice hearers with previous traumas that were thematically related to their voices participated. Brief weekly assessments (administered in sessions 1–8, post-intervention, and at 3-month follow-up) and longer measures (administered pre-, mid- and post-intervention) were administered. Mixed regression analysis was used to analyse the results.Results: There was one treatment drop-out. Results of the weekly measure showed significant linear reductions over time in all three primary variables – voice distress, voice frequency, and trauma intrusions – all with large effect sizes. These effects were maintained (and continued to improve for trauma intrusions) at 3-month follow-up. On the full assessment tools, all measures showed improvement over time, with five outcomes showing significant time effects: trauma, voice frequency, voice distress, voice malevolence and stress.Conclusions: The findings of the current study suggest that ImRs for PTSD symptoms is generally well tolerated and can be therapeutically beneficial among individuals who hear voices.
32
Liang, Zhenjie, Futian Weng, Yuanting Ma, Yan Xu, Miao Zhu, and Cai Yang. "Measurement and Analysis of High Frequency Assert Volatility Based on Functional Data Analysis." Mathematics 10, no. 7 (April 1, 2022): 1140. http://dx.doi.org/10.3390/math10071140.
Full textAbstract:
Information and communication technology have enabled the collection of high-frequency financial asset time series data. However, the high spatial and temporal resolution nature of these data makes it challenging to compare financial asset characteristics patterns and identify the risk. To address this challenge, a method for realized volatility calculation based on the functional data analysis (FDA) method is proposed. A time–price functional curve is constructed by the functional data analysis method to calculate the realized volatility as the curvature integral of the time–price functional curve. This method could effectively eliminate the interference of market microstructure noise, which could not only allow capital asset price to be decomposed into a continuous term and a noise term by asymptotic convergence, but also could decouple the noise from the discrete-time series. Additionally, it could obtain the value of volatility at any given time, which is no concern about correlations between repeated, mixed frequencies and unequal intervals sampling problems and relaxes the structural constraints and distribution setting of data acquisition. To demonstrate our methods, we analyze a per-second level financial asset dataset. Additionally, sensitivity analysis on the selection of the no equally spaced sample is conducted, and we further add noise to ensure the robustness of our methods and discuss their implications in practice, especially being conducive to more micro analysis of the volatility of the financial market and understanding the rapidly changing changes.
33
Cha, Oakyoon, and Randolph Blake. "Evidence for neural rhythms embedded within binocular rivalry." Proceedings of the National Academy of Sciences 116, no. 30 (July 8, 2019): 14811–12. http://dx.doi.org/10.1073/pnas.1905174116.
Full textAbstract:
Evidence for perceptual periodicity emerges from studies showing periodic fluctuations in visual perception and decision making that are accompanied by neural oscillations in brain activity. We have uncovered signs of periodicity in the time course of binocular rivalry, a widely studied form of multistable perception. This was done by analyzing time series data contained in an unusually large dataset of rivalry state durations associated with states of exclusive monocular dominance and states of mixed perception during transitions between exclusive dominance. Identifiable within the varying durations of dynamic mixed perception are rhythmic clusters of durations whose incidence falls within the frequency band associated with oscillations in neural activity accompanying periodicity in perceptual judgments. Endogenous neural oscillations appear to be especially impactful when perception is unusually confounding.
34
van Rij, Jacolien, Petra Hendriks, Hedderik van Rijn, R. Harald Baayen, and Simon N. Wood. "Analyzing the Time Course of Pupillometric Data." Trends in Hearing 23 (January 2019): 233121651983248. http://dx.doi.org/10.1177/2331216519832483.
Full textAbstract:
This article provides a tutorial for analyzing pupillometric data. Pupil dilation has become increasingly popular in psychological and psycholinguistic research as a measure to trace language processing. However, there is no general consensus about procedures to analyze the data, with most studies analyzing extracted features from the pupil dilation data instead of analyzing the pupil dilation trajectories directly. Recent studies have started to apply nonlinear regression and other methods to analyze the pupil dilation trajectories directly, utilizing all available information in the continuously measured signal. This article applies a nonlinear regression analysis, generalized additive mixed modeling, and illustrates how to analyze the full-time course of the pupil dilation signal. The regression analysis is particularly suited for analyzing pupil dilation in the fields of psychological and psycholinguistic research because generalized additive mixed models can include complex nonlinear interactions for investigating the effects of properties of stimuli (e.g., formant frequency) or participants (e.g., working memory score) on the pupil dilation signal. To account for the variation due to participants and items, nonlinear random effects can be included. However, one of the challenges for analyzing time series data is dealing with the autocorrelation in the residuals, which is rather extreme for the pupillary signal. On the basis of simulations, we explain potential causes of this extreme autocorrelation, and on the basis of the experimental data, we show how to reduce their adverse effects, allowing a much more coherent interpretation of pupillary data than possible with feature-based techniques.
35
Jiao, Eden Xiaoying, and Jason Li Chen. "Tourism forecasting: A review of methodological developments over the last decade." Tourism Economics 25, no. 3 (November 26, 2018): 469–92. http://dx.doi.org/10.1177/1354816618812588.
Full textAbstract:
This study reviewed 72 studies in tourism demand forecasting during the period from 2008 to 2017. Forecasting models are reviewed in three categories: econometric, time series and artificial intelligence (AI) models. Econometric and time series models that have already been widely used before 2007 remained their popularity and were more often used as benchmark models for forecasting performance evaluation and comparison with respect to new models. AI models are rapidly developed in the past decade and hybrid AI models are becoming a new trend. And some new trends with regard to the three categories of models have been identified, including mixed frequency, spatial regression and combination and hybrid models. Different combination components and combination techniques have been discussed. Results in different studies proved superiority of combination forecasts over average single forecasts performance.
36
Pan, James N. "Optoelectronic CMOS Transistors: Performance Advantages for Sub-7nm ULSI, RF ASIC, Memories, and Power MOSFETs." MRS Advances 4, no. 48 (2019): 2585–91. http://dx.doi.org/10.1557/adv.2019.211.
Full textAbstract:
AbstractSubstantial increase of output current, and Ion / Ioff ratio for sub-7nm low power CMOS transistors, can be accomplished using a novel optoelectronic technology, which is 100% compatible with existing CMOS process flow. For RF or mixed signal ASICs, adding photonic components may improve the cut-off frequency, and reduce series resistance. Products that utilize power regulating devices, such as power MOSFETs, will benefit from the optoelectronic configuration to achieve much lower Rdson and high voltage at the same time. For semiconductor memories, such as DRAM or FLASH, the photonic technique may reduce the ERASE / WRITE / access time and improve the reliability.
37
ASHINO, RYUICHI, TAKESHI MANDAI, and AKIRA MORIMOTO. "BLIND SOURCE SEPARATION OF SPATIO-TEMPORAL MIXED SIGNALS USING PHASE INFORMATION OF ANALYTIC WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 04 (July 2010): 575–94. http://dx.doi.org/10.1142/s0219691310003651.
Full textAbstract:
The cocktail party problem deals with the specialized human listening ability to focus one's listening attention on a single talker among a cacophony of conversations and background noises. The blind source separation problem is how to enable computers to solve the cocktail party problem in a satisfactory manner. The simplest version of spatio-temporal mixture problem, which is a type of blind source separation problem, has been solved by a generalized version of the quotient signal estimation method based on the analytic wavelet transform, under the assumption that the time delays are integer multiples of the sampling period. The analytic wavelet transform is used to represent time-frequency information of observed signals. Without the above assumption, improved algorithms, utilizing phase information of the analytic wavelet transforms of the observed signals, are proposed. A series of numerical simulations is presented.
38
Chen, Yu-Ru, Jeffrey D. Paduan, Michael S. Cook, Laurence Zsu-Hsin Chuang, and Yu-Jen Chung. "Observations of Surface Currents and Tidal Variability Off of Northeastern Taiwan from Shore-Based High Frequency Radar." Remote Sensing 13, no. 17 (August 30, 2021): 3438. http://dx.doi.org/10.3390/rs13173438.
Full textAbstract:
A network of high-frequency radars (HFRs) has been deployed around Taiwan. The wide-area data coverage is dedicated to revealing near real-time sea-surface current information. This paper investigates three primary objectives: (1) describing the seasonal current synoptic variability; (2) determining the influence of wind forcing; (3) describing the tidal current field pattern and variability. Sea surface currents derived from HFR data include both geostrophic components and wind-driven components. This study explored vector complex correlations between the HFR time series and wind, which was sufficient to identify high-frequency components, including an Ekman balance among the surface currents and wind. Regarding the characteristics of mesoscale events and the tidal field, a year-long high-resolution surface dataset was utilized to observe the current–eddy–tide interactions over four seasons. The harmonic analysis results derived from surface currents off of northeastern Taiwan during 2013 are presented. The results agree well with the tidal parameters estimated from tide-gauge station observations. The analysis shows that this region features a strong, mixed, mainly semidiurnal tide. Continued monitoring by a variety of sensors (e.g., satellite and HFR) would improve the understanding of the circulation in the region.
39
GÜLERCE, MUSTAFA, and GAZANFER ÜNAL. "FORECASTING OF OIL AND AGRICULTURAL COMMODITY PRICES: VARMA VERSUS ARMA." Annals of Financial Economics 12, no. 03 (September 2017): 1750012. http://dx.doi.org/10.1142/s2010495217500129.
Full textAbstract:
The aim of this paper is to show that the estimates made with vector autoregressive–moving-average (ARMA) models based on the coherent time intervals of the multiple time series give more precise results than the univariate case. The previous literature on dynamic correlations (co-movement) in between food and energy prices has mixed results and mainly based on parametric approaches. Therefore, partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) methods are used, respectively, to uncover the coherency simultaneously for time and frequency domains. In our study; world oil, corn, soybeans, wheat and sugar prices are examined instead of the return and volatility relationship between oil and agricultural commodities due to model-free approach of wavelet analysis.
40
Meng, Huibo, Zhiqiang Liu, Yanfang Yu, and Jianhua Wu. "Time-frequency analysis of Hilbert spectrum of pressure fluctuation time series in a Kenics Static Mixer based on empirical mode decomposition." Brazilian Journal of Chemical Engineering 29, no. 1 (March 2012): 167–82. http://dx.doi.org/10.1590/s0104-66322012000100018.
Full text
41
Acatrinei, Marius Cristian. "Financial stability indicator for non-banking markets." Journal of Financial Studies 5, no. 9 (November 15, 2020): 3–9. http://dx.doi.org/10.55654/jfs.2021.5.9.01.
Full textAbstract:
"A mixed frequency indicator is designed to incorporate and extract information from time-series data that are available at different frequencies: daily, monthly, quarterly, etc. Currently, the non-banking financial markets in Romania are supervised by the Financial Supervisory Authority and are composed of three distinct markets: the capital market, insurance, and private pension funds. Due to the mutual exposure between them, facilitated by the financial instruments held in their investment portfolios, there are common risk factors that influence their dynamics. Although a financial shock can affect all three sectors at the same time, the impact can be measured at a different frequency and with a different lag. Surveillance data for capital markets and pension funds are available every month, with a gap of one month, while for insurance the data are available quarterly, but with a gap of two months, similar to GDP data. If a sudden financial event disrupts financial markets or a change in the macroeconomic environment changes the medium-term outlook, what is the impact on non-bank financial intermediation? The stability indicator for non-banking financial markets is a monthly indicator estimated from mixed frequency data. The indicator is designed to provide a signal of financial instability in non-banking financial markets, to the extent that all three markets are disrupted at once."
42
Önder, Irem, Ulrich Gunter, and Arno Scharl. "Forecasting Tourist Arrivals with the Help of Web Sentiment: A Mixed-frequency Modeling Approach for Big Data." Tourism Analysis 24, no. 4 (November 13, 2019): 437–52. http://dx.doi.org/10.3727/108354219x15652651367442.
Full textAbstract:
Online news media coverage regarding a destination, a form of big data, can affect destination image and influence the number of tourist arrivals. Sentiment analysis extracts the valence of an author's perception about a topic by rating a segment of text as either positive or negative. The sentiment of online news media can be viewed as a leading indicator for actual tourism demand. The aim of this study is to examine if web sentiment of online news media coverage of four European cities (Berlin, Brussels, Paris, and Vienna) possesses information to predict actual tourist arrivals. This study is the first to use web sentiment for forecasting tourism demand. Automated semantic routines were conducted to analyze the sentiment of online news media coverage. Due to the differing data frequencies of tourist arrivals (monthly) and web sentiment indicators (daily), the MIxed-DAta Sampling (MIDAS) modeling approach was applied. Results indicate that MIDAS models including various web sentiment indicators outperform time-series and naive benchmarks in terms of typical accuracy measures. This study shows that utilizing online news media coverage as an indication of destination image can improve tourism demand forecasting. Because destination image is dynamic, the results can vary depending on time period of the analysis and the destination. A managerial implication of the forecast evaluation exercise is that destination management organizations (DMOs) should add models incorporating web sentiment data to their forecast modeling toolkit to further improve the accuracy of their tourism demand forecasts.
43
ZHANG, F., J. GROHS, J. STEFFEN, H. IßLER, and C. KLINGSHIRN. "SELF-OSCILLATIONS AND OPTICAL CHAOS OF AN INDUCED ABSORBER IN COUPLED CAVITIES." International Journal of Bifurcation and Chaos 04, no. 05 (October 1994): 1375–81. http://dx.doi.org/10.1142/s0218127494001106.
Full textAbstract:
In this paper we investigate the nonlinear dynamics of an induced absorber (CdS) in two coupled, hybrid, optoelectronic ring-cavities. By changing the cw-pumping intensity an inverse successive-subharmonic-oscillation cascade followed by a chaotic oscillation is experimentally observed with a narrow bistable input-output characteristics of the absorber. The related numerical simulations are given. For fixed delayed times a new type of frequency hysteresis is found. In the case of one very short and one very long delay time, a series of mixed self-oscillation modes, which is composed from the modes corresponding to the two delay times, is observed.
44
Zhang, Yabing, Yang Liu, Hejun Zhu, Tongjun Chen, and Juanjuan Li. "Modified viscoelastic wavefield simulations in the time domain using the new fractional Laplacians." Journal of Geophysics and Engineering 19, no. 3 (May 24, 2022): 346–61. http://dx.doi.org/10.1093/jge/gxac022.
Full textAbstract:
Abstract Accurately characterizing seismic attenuation effects on wave propagations is crucially important for structure interpretation and reservoir evaluation. The conventional fractional viscoelastic wave equation is not satisfactory on accuracy for small Q values. To solve this issue, we derive a novel fractional viscoelastic wave equation by combining an accurate relationship between angular frequency and complex wavenumber. The dissipation- and dispersion-dominated wave equations are also derived to simulate the amplitude-dissipation and phase-dispersion characteristics. The truncated Taylor-series expansion (TE) algorithm is developed to approximate the mixed-domain operators. After that, the generalized pseudospectral approach can be directly used to solve the new wave equation. In addition, an accurate viscoelastic wave equation constructed by the fractional time derivatives is used to calculate reference solutions to evaluate the accuracy of the new expression. Modelling results indicate that the newly proposed viscoelastic wave equation using the new fractional Laplacians is more accurate than the conventional one, especially in a small Q medium (i.e. QP = QS = 5). Furthermore, we also examine the accuracy of the TE approximation with a series of Q values. A homogeneous model and the modified BP2004 viscoelastic model are used to investigate the accuracy of viscoelastic wave propagations using the TE algorithm. All modelling results fully demonstrate the performance of the newly proposed viscoelastic wave equation and numerical algorithm.
45
Cox, Tom J. S., Justus E. E. van Beusekom, and Karline Soetaert. "Tune in on 11.57 µHz and listen to primary production." Biogeosciences 14, no. 22 (November 28, 2017): 5271–80. http://dx.doi.org/10.5194/bg-14-5271-2017.
Full textAbstract:
Abstract. In this paper we present an elegant approach to reconstruct slowly varying gross primary production (GPP) as a function of time, based on O2 time series. The approach, called complex demodulation, is based on a direct analogy with amplitude-modulated (AM) radio signals. The O2 concentrations oscillating at the diel frequency (or 11.57 µHz) can be seen as a carrier wave, while the time variation in the amplitude of this carrier wave is related to the time-varying GPP. The relation follows from an analysis in the frequency domain of the governing equations of O2 dynamics. After the theoretical derivation, we assess the performance of the approach by applying it to three artificial O2 time series, generated with models representative of a well-mixed vertical water column, a river and an estuary. These models are forced with hourly observed incident irradiance, resulting in a variability of GPP on scales from hours to months. The dynamic build-up of algal biomass further increases the seasonality. Complex demodulation allows for reconstruction, with great precision, of time-varying GPP of the vertical water column and the river model. Surprisingly, it is possible to derive daily averaged GPP – complex demodulation thus reconstructs the amplitude of every single diel cycle. Also, in estuaries time-varying GPP can be reconstructed to a great extent. But there, the influence of the tides prevent achieving the same temporal resolution. In particular, the combination of horizontal O2 gradients with quasi-diurnal harmonics in the tides interferes with the complex demodulation procedure and introduces spurious amplitude variation that can not be attributed to GPP. We demonstrate that these spurious effects also occur in real-world time series (Hörnum Tief, Germany). The spurious effects due to K1 and P1 quasi-diurnals can not be distinguished from GPP. However, the spurious fluctuations introduced by O1 and Q1 can be removed to a large extent by increasing the averaging time to 15 days. As such, we demonstrate that a good estimate of the running 15-day average of GPP can be obtained in tidal systems. Apart from the direct merits of estimating GPP from O2 time series, the analysis in the frequency domain enhances our insights into O2 dynamics in tidal systems in general, and into the performance of O2 methods to estimate GPP in particular.
46
Abdou, Musonera, Edouard Musabanganji, and Herman Musahara. "Tourism Demand Modelling and Forecasting: A Review of Literature." African Journal of Hospitality, Tourism and Leisure 10(4), no. 10(4) (August 31, 2021): 1370–93. http://dx.doi.org/10.46222/ajhtl.19770720.168.
Full textAbstract:
This research examines 145 key papers from 1979 to 2020 in order to gain a better sense of how tourism demand forecasting techniques have changed over time. The three types of forecasting models are econometric, time series, and artificial intelligence (AI) models. Econometric and time series models that were already popular in 2005 maintained their popularity, and were increasingly used as benchmark models for forecasting performance assessment and comparison with new models. In the last decade, AI models have advanced at an incredible rate, with hybrid AI models emerging as a new trend. In addition, some new developments in the three categories of models, such as mixed frequency, spatial regression, and combination and hybrid models have been introduced. The main conclusions drawn from historical comparisons forecasting methods are that forecasting models have become more diverse, that these models have been merged, and that forecasting accuracy has improved. Given the complexities of predicting tourism demand, there is no single approach that works well in all circumstances, and forecasting techniques are still evolving.
47
Murawski, S. A., and J. T. Finn. "Biological Bases for Mixed-Species Fisheries: Species Co-distribution in Relation to Environmental and Biotic Variables." Canadian Journal of Fisheries and Aquatic Sciences 45, no. 10 (October 1, 1988): 1720–35. http://dx.doi.org/10.1139/f88-204.
Full textAbstract:
Factors influencing the degree of temporal and spatial co-occurrence of seven important demersal fish species on Georges Bank (Northwest Atlantic) were analyzed. Species/age co-occurrence data from a 24-yr time series of research vessel bottom trawl surveys were evaluated in relation to temperature and depth preferences, spatial distribution, and species/age abundance trends. Co-occurrence of various species/age groups varied greatly by season and was significantly correlated with overlap in temperature/depth preference indices and annual species abundance. Although species abundance and proportion of survey tows having particular species varied widely over the time series, trends in spatial dispersion indices of particular species were not generally related to abundance. Multiple regression models incorporating temperature and depth preference overlap and species abundance as independent variables accounted for a high proportion of total variance in the transformed proportion of survey tows containing co-occurring species (mean R2 = 0.69 for age 1 + fishes, mean R2 = 0.44 for age 0). Results indicate that although the frequency of technological (bycatch) interaction among pairs of species may be highly variable depending on season, area, and year, co-occurrence among species is nonetheless relatively predictable. Minimization of the potential adverse impacts of mixed-species harvesting (i.e. failure to achieve management goals for all species simultaneously) may be accomplished by exploiting stocks individually during periods of maximum spatial separation and by using information on the determinants of species co-distribution to more accurately forecast bycatch levels.
48
Alford, Matthew H., Meghan F. Cronin, and Jody M. Klymak. "Annual Cycle and Depth Penetration of Wind-Generated Near-Inertial Internal Waves at Ocean Station Papa in the Northeast Pacific." Journal of Physical Oceanography 42, no. 6 (June 1, 2012): 889–909. http://dx.doi.org/10.1175/jpo-d-11-092.1.
Full textAbstract:
Abstract The downward propagation of near-inertial internal waves following winter storms is examined in the context of a 2-yr record of velocity in the upper 800 m at Ocean Station Papa. The long time series allow accurate estimation of wave frequency, whereas the continuous data in depth allow separation into upward- and downward-propagating components. Near-inertial kinetic energy (KEin) dominates the record. At all measured depths, energy in downgoing motions exceeds that of upward-propagating motions by factors of 3–7, whereas KEin is elevated by a factor of 3–5 in winter relative to summer. The two successive winters are qualitatively similar but show important differences in timing and depth penetration. Energy is seen radiating downward in a finite number of wave groups, which are tagged and catalogued to determine the vertical group velocity cgz, which has a mean of about 1.5 × 10−4 m s−1 (13 m day−1). Case studies of three of these are presented in detail. Downward energy flux is estimated as cgz × KEin (i) by summing over the set of events, (ii) from time series near the bottom of the record, and (iii) from the wavenumber–frequency spectrum and the dispersion relationship. These estimates are compared to the work done on near-inertial motions in the mixed layer by the wind, which is directly estimated from mixed layer near-inertial currents and winds measured from a surface buoy 10 km away. All three methods yield similar values, indicating that 12%–33% of the energy input into the mixed layer transits 800 m toward the deep sea. This simple picture neglects lateral energy flux carried by the first few vertical modes, which was not measured. The substantial deep penetration implies that near-inertial motions may play a role in mixing the deep ocean, but the strong observed variability calls for a need to better understand the role of lateral mesoscale structures in modulating the vertical propagation.
49
Son, Y. T., K. I. Chang, S. T. Yoon, Y. B. Kim, T. Rho, C. K. Kang, and K. R. Kim. "Time-series measurements of biochemical and physical properties in the southwestern East/Japan Sea during the spring transition in 2010." Biogeosciences Discussions 10, no. 5 (May 8, 2013): 7831–78. http://dx.doi.org/10.5194/bgd-10-7831-2013.
Full textAbstract:
Abstract. An ocean buoy, UBIM, deployed during the spring transition from February and May, 2010 reveals for the first time highly-resolved temporal variation of biochemical properties of the upper layer of the Ulleung Basin in the southwestern East/Japan Sea. Meteorological data shows the typical spring transition occurred during the mooring period, weakening of wind speed, increase in shortwave radiation, and change in total heat flux from net cooling to net heating. Power spectrum of chlorophyll fluorescence (CF) peaks at semidiurnal tidal, near-inertial, diurnal, and subtidal frequencies. The diurnal variation of CF is characterized by high CF during the daytime and low CF at night. Dissolved oxygen and CF are correlated with high (low) dissolved oxygen accompanied by high (low) CF, indicating the dissolved oxygen is mainly determined by biological activities. The time series measurement captured the onset of subsurface spring bloom at 30 m, and collocated temperature and current data gives an insight into a mechanism that triggers the onset of the spring bloom not documented so far. The entire mooring period can be divided into pre-bloom period from the beginning of the mooring to early April, and bloom period afterwards. Mean CF values during the pre-bloom and bloom periods are 0.9 μg L−1 and 1.9 μg L−1, respectively. Mean mixed layer depth (MLD) shoaled from 22 m during the pre-bloom period to 15 m during the bloom period. Despite of the increase in shortwave radiation, average PAR values at 20 m show lower value during the bloom period as compared to that during the pre-bloom period. Low-frequency modulation of MLD ranging from 10 m to 53 m during the entire mooring period is mainly determined by shoaling and deepening of isothermal (isopycnal) depths. Temperature structure in the upper 110 m is characterized by alternating uplifting and lowering of isotherms, which is caused by the placement of the mooring site on the cold (cyclonic) or warm side of the frontal jet, the East Korean Warm Current. The frontal variability is thought to be due to the low-frequency path variatio of the East Korean Warm Current. The occurrence of the spring bloom at 30 m is concomitant with the appearance of colder East Sea Intermediate Water (ESIW) at buoy UBIM that results in the subsurface cooling and the shoaling of isotherms to the shallower depth levels than those occurred during the pre-bloom period. It is suggested that the springtime spreading of the ESIW is one of the important factors that triggers the onset of subsurface spring bloom below the mixed layer. The time lag between the peaks of CF and the occurrence of the shallowest isothermal depths is about several days, which appears to be the timescale for the growth of phytoplankton.
50
M. M. LUNAGARIA, H. P. DABHI, and VYAS PANDEY. "Trends in the temperature and rainfall extremes during recent past in Gujarat." Journal of Agrometeorology 17, no. 1 (June 1, 2015): 118–23. http://dx.doi.org/10.54386/jam.v17i1.986.
Full textAbstract:
In the present study, an attempt has been made to analyze the temperature and rainfall extremes observed in Gujarat during the recent past. Observed daily data of maximum and minimum temperature and rainfall for 32 geographically well distributed locations in Gujarat for the available time series during year 1958 to 2011 has been used to calculate various extreme climate indices and their trends. Results revealed signature of warming in Gujarat as indicated by statewide uniform increase in numbers of warm nights (TR25), decrease in cold days (FD10), decrease in frequency cool nights (TN10p), increase in minimum of minimum temperature (TNn) and increase in frequency of warm nights (TN90p). The results also indicated an increase in total amount of precipitation (PRCPTOT) and extremely wet days (R99p) over more numbers of stations of the state. However, most temperature and rainfall extremes showed mixed over the state.