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The use of hybrid methods for change points and trends detection in rainfall series of northern Algeria

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Zerouali B. , Chettih M. , Abda Z. , Mesbah M. , Djemai M.

Acta Geophysica

2020

tom Vol. 68, no. 5

1443--1460

The aim of this research is to assess relatively new hybrid methods for changes points and trends detection on rainfall series: Dynamic Programming Bayesian Change Point Approach (BA), Şen’s innovative trend method (ITM) and its double (D-ITM) and triple (T-ITM) version using the multi-scale analysis of the discrete wavelet transform (DWT) as a coupling method. Three representatives rainfall stations of northern Algeria were analysed at annual scale during the period 1920–2011. Moreover, correlation and spectral analysis (CSA) was applied for periodicity analysis. The CSA indicates the dominance of interannual to multidecadal rainfall periodicity fuctuations (2-years, 5-years and 20-years) characterising long term structured processes. Moreover, an abrupt downward trend with signifcant probability was detected from the 1970s with a relatively wet period between the periods 1950–1970 and 2001–2011. The latter is observed in particular in the central and eastern stations, well-explained by the BA-DWT. The results showed that the comparison results from diferent modelling approaches found that the hybrid models (BA-DWT, ITM-DWT, D-ITM-DWT, T-ITM-DWT) often perform better than the conventional approach (BA, ITM, D-ITM, T-ITM), where the computation time is very reasonable. The analysis revealed that information stemming from discrete wavelet spectrums signifcantly increased the accuracy of the methods for detecting hidden change points and trends.

How transit improvements are perceived by passengers? Results of a before-after customer satisfaction survey

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Sahraei M. , Mesbah M. , Habibian M. , Saeidi T. , Soltanpour A.

Archives of Transport

2023

tom Vol. 65, iss. 1

56--66

Although customer satisfaction surveys are widely utilized by transit agencies, there are limited analyses in the literature on the perception of passengers as a result of service improvements. A before-after study can help to evaluate the effect of changes from customer’s points of view and thus guarantee a continuous improvement in the service. In this paper, customer satisfaction was directly observed through a Customer Satisfaction Survey (CSS) before and after certain changes. Furthermore, Structural Equation Modeling (SEM) is utilized to evaluate passenger’s perception of the service attribute importance. Finally, an Importance-Performance Analysis (IPA) is adapted to analyze the changes in satisfaction and importance from the passenger’s perspective on each service attribute. In both before and after cases, a consistent SEM structure is used. The follow-up IPA provides transit agencies with priorities to improve service attributes and helps managers to devote their resources to key attributes that matter to the riders. Metro line 3 in Tehran was selected as the case study which is 33.7 km long with 25 stations. Two surveys were performed one before (with the sample size of 300), and one after (with the sample size of 384) a set of changes the most important of which was a headway reduction. The SEM was developed with five latent variables of main service, comfort, information, protection, and physical appearance. This structure was assessed on both the before and after data collections and showed to be valid. Security at the station and security on board were the most important service attributes in both waves according to their factor loadings, while ethics and behavioral messages had the smallest factor loading and the least importance. Comparing the attributes in both surveys suggested that reducing the headway was effective, although it did not seem to be sufficient for enhancing the overall customer satisfaction and improvements need to be continued.