Real-time Intraday Traffic Volume Forecasting – A Hybrid Application Using Singular Spectrum Analysis and Artificial Neural Networks

The present paper provides a comparative evaluation of hybrid Singular Spectrum Analysis (SSA) and Artificial Neural Networks (ANN) against conventional ANN, applied on real time intraday traffic volume forecasting. The main research objective was to assess the applicability and functionality of intraday traffic volume forecasting, based on toll station measurements. The proposed methodology was implemented and evaluated upon a custom developed forecasting software toolbox, based on the software Mathworks MatLab, by using real data from Iasmos-Greece toll station. Experimental results demonstrated a superior ex post forecasting accuracy of the proposed hybrid forecasting methodology against conventional ANN, when compared to performance of usual statistical criteria (Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, Coefficient of Determination R2, Theil's inequality coefficient). The obtained results revealed that the hybrid model could advance forecasting accuracy of a conventional ANN model in intraday traffic volume forecasting, while embedding hybrid forecasting algorithm in an Intelligent Transport System could provide an advanced decision support module for transportation system maintenance, operation and management

On the computation of equilibria in discrete first-price auctions

We study the computational complexity of computing Bayes-Nash equilibria in first-price auctions with discrete value distributions and discrete bidding space, under general subjective beliefs. It is known that such auctions do not always have pure equilibria. In this paper we prove that the problem of deciding their existence is NP-complete, even for approximate equilibria. On the other hand, it can be shown that mixed equilibria are guaranteed to exist; however, their computational complexity has not been studied before. We establish the PPAD-completeness of computing a mixed equilibrium and we complement this by an efficient algorithm for finding symmetric approximate equilibria in the special case of iid priors. En route to these results, we develop a computational equivalence framework between continuous and discrete first-price auctions, which can be of independent interest, and which allows us to transfer existing positive and negative results from one setting to the other. Finally, we show that correlated equilibria of the auction can be computed in polynomial time

Planetary boundary layer height variability over Athens, Greece, based on the synergy of Raman lidar and radiosonde data: application of the Kalman filter and other techniques (2011-2016)

The temporal evolution of the Planetary Boundary Layer height over Athens, Greece for a 5-year period (2011-2016) is presented. Using the EOLE Raman lidar system, the range-corrected lidar signals were selected around 12:00 UTC and 00:00 UTC for a total of 332 cases (165 days and 167 nights). The Kalman filter and other techniques were used to determine PBL height. The mean PBL height was found to be around 1617±324 m (12:00 UTC) and 892±130 m (00:00 UTC).Peer ReviewedPostprint (published version

Vertical Profiles of Aerosol Optical and Microphysical Properties During a Rare Case of Long-range Transport of Mixed Biomass Burning-polluted Dust Aerosols from the Russian Federation-kazakhstan to Athens, Greece

Multi-wavelength aerosol Raman lidar measurements with elastic depolarization at 532 nm were combined with sun photometry during the HYGRA-CD campaign over Athens, Greece, on May-June 2014. We retrieved the aerosol optical [3 aerosol backscatter profiles (baer) at 355-532-1064 nm, 2 aerosol extinction (aaer) profiles at 355-532 nm and the aerosol linear depolarization ratio (δ) at 532 nm] and microphysical properties [effective radius (reff), complex refractive index (m), single scattering albedo (ω)]. We present a case study of a long distance transport (~3.500-4.000 km) of biomass burning particles mixed with dust from the Russian Federation-Kazakhstan regions arriving over Athens on 21-23 May 2014 (1.7-3.5 km height). On 23 May, between 2-2.75 km we measured mean lidar ratios (LR) of 35 sr (355 nm) and 42 sr (532 nm), while the mean Ångström exponent (AE) aerosol backscatter-related values (355nm/532nm and 532nm/1064nm) were 2.05 and 1.22, respectively; the mean value of δ at 532 nm was measured to be 9%. For that day the retrieved mean aerosol microphysical properties at 2-2.75 km height were: reff=0.26 μm (fine mode), reff=2.15 μm (coarse mode), m=1.36+0.00024i, ω=0.999 (355 nm, fine mode), ω=0.992(355 nm, coarse mode), ω=0.997 (532 nm, fine mode), and ω=0.980 (532 nm, coarse mode)

Towards reliable retrievals of cloud droplet number for non-precipitating planetary boundary layer clouds and their susceptibility to aerosol

Remote sensing has been a key resource for developing extensive and detailed datasets for studying and constraining aerosol-cloud-climate interactions. However, aerosol-cloud collocation challenges, algorithm limitations, as well as difficulties in unraveling dynamic from aerosol-related effects on cloud microphysics, have long challenged precise retrievals of cloud droplet number concentrations. By combining a series of remote sensing techniques and in situ measurements at ground level, we developed a semi-automated approach that can address several retrieval issues for a robust estimation of cloud droplet number for non-precipitating Planetary Boundary Layer (PBL) clouds. The approach is based on satellite retrievals of the PBL cloud droplet number (Ndsat) using the geostationary meteorological satellite data of the Optimal Cloud Analysis (OCA) product, which is obtained by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT). The parameters of the retrieval are optimized through closure with droplet number obtained from a combination of ground-based remote sensing data and in situ observations at ground level. More specifically, the remote sensing data are used to retrieve cloud-scale vertical velocity, and the in situ aerosol measurements at ground level were used constrain as input to a state-of-the-art droplet activation parameterization to predict the respective Cloud Condensation Nuclei (CCN) spectra, cloud maximum supersaturation and droplet number concentration (Nd), accounting for the effects of vertical velocity distribution and lateral entrainment. Closure studies between collocated Nd and Ndsat are then used to evaluate exising droplet spectral width parameters used for the retrieval of droplet number, and determine the optimal values for retrieval. This methodology, used to study aerosol-cloud interactions for non-precipitating clouds formed over the Athens Metropolitan Area (AMA), Greece from March to May 2020, shows that droplet closure can be achieved to within 30%, comparable to the level of closure obtained in many in situ studies. Given this, the ease of applying this approach with satellite data obtained from SEVIRI with high temporal (15 min) and spatial resolution (3.6 km × 4.6 km), opens the possibility of continuous and reliable Ndsat, giving rise to high value datasets for aerosol-cloud-climate interaction studies

Growth and natural mortality of Maurolicus muelleri and Benthosema glaciale in the Northeast Atlantic Ocean

Mesopelagic fish are considered a possible future fisheries resource, but the biological sustainability of their potential exploitation has not yet been assessed. Sustainability should be evaluated at the population level, for which accurate stock-specific life-history parameters are required. Here, we use a length-based model to estimate life-history parameters related to growth and natural mortality, and their uncertainty, for the assessment of Northeast Atlantic populations of Maurolicus muelleri (Gmelin, 1789, Mueller’s Pearlside) and Benthosema glaciale (Reinhardt, 1837, glacier lantern fish). We compare three different approaches to estimate natural mortality rates and provide recommendations for future data collection and monitoring programs. For M. muelleri, we estimated an asymptotic length of 57.98 mm and a von Bertalanffy growth constant of 1.28 year−1, while for B. glaciale, we estimated an asymptotic length of 78.93 mm and a von Bertalanffy growth constant of 0.41 year−1. Estimates of natural mortality rates for M. muelleri were around 1.29 year−1 and 1.80 year−1 based on empirical formulae with the estimated growth parameters and maximum age, respectively, and around 1.51 year−1 with the length-converted catch curve method for B. glaciale estimates ranged between 0.5, 0.68, and 0.75 year−1, with the three respective methods. Due to limited data availability, the estimated uncertainty of the provided life-history parameters is large and should be considered in the evaluation of the sustainability of potential mesopelagic exploitation following the precautionary approach

Aerosol absorption profiling from the synergy of lidar and sun-photometry : The ACTRIS-2 campaigns in Germany, Greece and Cyprus

© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).Aerosol absorption profiling is crucial for radiative transfer calculations and climate modelling. Here, we utilize the synergy of lidar with sun-photometer measurements to derive the absorption coefficient and single scattering albedo profiles during the ACTRIS-2 campaigns held in Germany, Greece and Cyprus. The remote sensing techniques are compared with in situ measurements in order to harmonize and validate the different methodologies and reduce the absorption profiling uncertainties.Peer reviewe