Browsing by Subject "Periodicity"

Now showing 1 - 3 of 3

Open Access
Modeling and forecasting of monthly PM2.5 emission of Paris by periodogram-based time series methodology
(Springer, 2021-09-03) Akdi, Y.; Gölveren, E.; Ünlü, K. D.; Yücel, Mustafa Eray
In this study, monthly particulate matter (PM2.5) of Paris for the period between January 2000 and December 2019 is investigated by utilizing a periodogram-based time series methodology. The main contribution of the study is modeling the PM2.5 of Paris by extracting the information purely from the examined time series data, where proposed model implicitly captures the effects of other factors, as all their periodic and seasonal effects reside in the air pollution data. Periodicity can be defined as the patterns embedded in the data other than seasonality, and it is crucial to understand the underlying periodic dynamics of air pollutants to better fight pollution. The method we use successfully captures and accounts for the periodicities, which could otherwise be mixed with seasonality under an alternative methodology. Upon the unit root test based on periodograms, it is revealed that the investigated data has periodicities of 1 year and 20 years, so harmonic regression is utilized as an alternative to Box-Jenkins methodology. As the harmonic regression displayed a better performance both in and out-of-sample forecasts, it can be considered as a powerful alternative to model and forecast time series with a periodic structure.
Open Access
Period estimation of an almost periodic signal using persistent homology with application to respiratory rate measurement
(Institute of Electrical and Electronics Engineers Inc., 2017) Erden, F.; Çetin, A. Enis
Time-frequency techniques have difficulties in yielding efficient online algorithms for almost periodic signals. We describe a new topological method to find the period of signals that have an almost periodic waveform. Proposed method is applied to signals received from a pyro-electric infrared sensor array for the online estimation of the respiratory rate (RR) of a person. Timevarying analog signals captured from the sensors exhibit an almost periodic behavior due to repetitive nature of breathing activity. Sensor signals are transformed into two-dimensional point clouds with a technique that allows preserving the period information. Features, which represent the harmonic structures in the sensor signals, are detected by applying persistent homology and the RR is estimated based on the persistence barcode of the first Betti number. Experiments have been carried out to show that our method makes reliable estimates of the RR.
Open Access
Periodic location routing problem : an application of mobile health services in rural area
(2017-06) Savaşer, Sinem
Lack of sufficient healthcare services in rural areas has been a considerable problem throughout the world for a long time. One of the alternative ways to address and solve this problem is providing mobile healthcare services in which the providers are traveling and visiting patients. These services have been obligatory in Turkey since 2010 and there are certain requirements that are enforced by Ministry of Health, such as having multiple routinized visits, having alternative visiting rules and dedicating doctors to specified villages. Based on the characteristics of this problem, it is categorized under Periodic Location Routing Problem (PLRP) literature. The common characteristic of the solution methodologies in the PLRP literature is to predefine a set of alternative schedules and select the best one among those. Unlike the other approaches that have been already studied, the developed integer programming model determines the schedules of the doctors via its constraints, dedicates each doctor to same villages through the planning horizon and satisfies certain visiting rules. The performance of the model is tested by utilizing the data set of Burdur. The proposed model is solved to optimality in reasonable times for the small instances; however, significant optimality gaps remain at the end of predefined time limits of the larger instances. In order to obtain prominent results in shorter durations, a \cluster first, route second" based heuristic algorithm is developed. Based on the computational experiments, it is observed that the solution times are significantly improved and optimal or near-optimal solutions are obtained with the heuristic approach.