scholarly journals An ELM-Based Approach for Estimating Train Dwell Time in Urban Rail Traffic

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Wen-jun Chu ◽  
Xing-chen Zhang ◽  
Jun-hua Chen ◽  
Bin Xu
Keyword(s):  
Regression Models ◽  
Dwell Time ◽  
Polynomial Regression ◽  
Time Estimation ◽  
Estimation Model ◽  
Urban Rail ◽  
Overall Performance ◽  
Polynomial Regression Models ◽  
Learning Machine ◽  
Microsimulation Models

Dwell time estimation plays an important role in the operation of urban rail system. On this specific problem, a range of models based on either polynomial regression or microsimulation have been proposed. However, the generalization performance of polynomial regression models is limited and the accuracy of existing microsimulation models is unstable. In this paper, a new dwell time estimation model based on extreme learning machine (ELM) is proposed. The underlying factors that may affect urban rail dwell time are analyzed first. Then, the relationships among different factors are extracted and modeled by ELM neural networks, on basis of which an overall estimation model is proposed. At last, a set of observed data from Beijing subway is used to illustrate the proposed method and verify its overall performance.

Growth relationships of individual flowers during late stages of floral development of Rhododendron L. 'Prize' and 'Gloria'

1998 ◽  
Vol 76 (8) ◽  
pp. 1350-1358
Author(s):  
H Brent Pemberton ◽  
Harold F Wilkins ◽  
James S Hodges
Keyword(s):  
Regression Models ◽  
Polynomial Regression ◽  
Cold Treatment ◽  
Female Flower ◽  
Growth Patterns ◽  
Strongly Correlated ◽  
Floral Part ◽  
Growth Measurement ◽  
Hormonal Content ◽  
Polynomial Regression Models

Single terminal inflorescences from two-stemmed plants of Rhododendron L. cv. 'Prize' and 'Gloria' were recurrently sampled during a 9°C cold treatment and subsequent forcing period in an 18°C growth chamber until plants reached anthesis. At each sample period, bud length and width were measured on each inflorescence, while subtending bud scale, petal, stamen ('Gloria' only), style, peduncle and ovary length, ovary width, and flower weight were determined on the two most basally attached flowers within an inflorescence for each cultivar. Polynomial regression models were calculated for each floral growth measurement over time, except for bud length and width, for each of the four flowers within a cultivar. Comparison of regression models revealed differences in floral part growth patterns among the various flowers within each cultivar. During the first week of placement in 18°C forcing temperatures after the cold treatment, bud length was the only floral part to grow on 'Prize' plants, while only female flower parts grew on 'Gloria' plants. These results indicate differences in growth resumption patterns between cultivars after cold storage. However, petal and style length were strongly correlated to flower weight for both cultivars indicating that these measurements could be used in laboratory or field situations to determine the floral stage of growth. The growth equations described would be useful for controlling the variability among shoots and flowers for analytical determinations, such as hormonal content analysis, and for studying relationships of floral growth patterns to environmental stimuli that could be used to control flowering. The statistical techniques used in this research make it possible to reduce the number of plants for such studies, as measurements taken on different flowers on the same plant can be used for floral part growth comparisons despite the inherent correlation present between such measurements.Key words: morphology, dormancy, growth modeling, multivariate multiple regression, controlled environment.

scholarly journals Testing the Generality of a Passenger Disregarded Train Dwell Time Estimation Model at Short Stops: Both Comparison and Theoretical Approaches

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Dewei Li ◽  
Yonghao Yin ◽  
Hong He
Keyword(s):  
Dwell Time ◽  
Time Estimation ◽  
Work Conditions ◽  
Critical Issue ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Estimation Model ◽  
Railway Stations ◽  
Theoretical Approaches ◽  
Improved Model

Train dwell time estimation is a critical issue in both scheduling and rescheduling phases. In a previous paper, the authors proposed a novel dwell time estimation model at short stops which did not require the passenger data. This model shows promising results when applied to Dutch railway stations. This paper focuses on testing and improving the generality of the model by two steps: first, the model is tested by applying more independent datasets from another city and comparing the estimation accuracy with the previous Dutch case; second, the model’s generality is tested by a theoretical approach through the analysis of individual model parameters, variables, model scenarios, and model structure as well as work conditions. The validation results during peak hours show that the MAPE of the model is 11.4%, which is slightly better than the results for the Dutch railway stations. A more generalized predictor called “dwell time at the associated station” is used to replace the square root term in the original model. The improved model can estimate train dwell time in all the investigated stations during both peak and off-peak periods. We conclude that the proposed train dwell time estimation model is generic in the given condition.

scholarly journals EVOLUTION OF MORTALITY FOR COLORECTAL CANCER IN BRAZIL AND REGIONS, BY SEX, 1996-2015

2018 ◽  
Vol 55 (1) ◽  
pp. 61-65 ◽  
Author(s):  
Viviane Gomes Parreira DUTRA ◽  
Virgilio Augusto Gomes PARREIRA ◽  
Raphael Mendonça GUIMARÃES
Keyword(s):  
Colorectal Cancer ◽  
Regression Models ◽  
Polynomial Regression ◽  
Public Health Problem ◽  
Mortality Rates ◽  
Early Interventions ◽  
Polynomial Regression Models ◽  
And Behavior ◽  
Priority Populations ◽  
Colorectal Cancer Mortality

ABSTRACT BACKGROUND: Colorectal cancer is among the three most frequent neoplasms in Brazil, being a public health problem. OBJECTIVE: To describe distribution pattern of colorectal cancer mortality in Brazil and regions, according to sex, between 1996 and 2015. METHODS: Values of standardized and stratified mortality rates by sex between 1996 and 2015 were used, through polynomial regression models and joinpoint analysis. RESULTS: It was observed that, for linear trends in mortality rates, for both sexes, there is a statistically significant trend increasing in both models, with rates and trends, and higher for men than for women, respectively, 7.3% per year (R2=0.95, P<0.001) and 6.5% per year (R2=0.87, P<0.001). It is observed a difference in magnitude and behavior of trend between the regions. CONCLUSION: It is understood that it is important to know the trend of rates in order to define priority populations for early interventions that increase survival and reduce mortality.

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