scholarly journals Smart Recommendations for Renting Bikes in Bike-Sharing Systems

2021 ◽  
Vol 11 (20) ◽  
pp. 9654
Author(s):  
Holger Billhardt ◽  
Alberto Fernández ◽  
Sascha Ossowski
Keyword(s):  
Queuing Theory ◽  
Real Data ◽  
Transport Systems ◽  
Bike Sharing ◽  
Usage Patterns ◽  
One Step ◽  
The One ◽  
The Individual ◽  
Recommendation Strategy ◽  
Better Than

Vehicle-sharing systems—such as bike-, car-, or motorcycle-sharing systems—have become increasingly popular in big cities in recent years. On the one hand, they provide a cheaper and environmentally friendlier means of transportation than private cars, and on the other hand, they satisfy the individual mobility demands of citizens better than traditional public transport systems. One of their advantages in this regard is their availability, e.g., the possibility of taking (or leaving) a vehicle almost anywhere in a city. This availability obviously depends on different strategic and operational management decisions and policies, such as the dimension of the fleet or the (re)distribution of vehicles. Agglutination problems—where, due to usage patterns, available vehicles are concentrated in certain areas, whereas no vehicles are available in others—are quite common in such systems, and need to be dealt with. Research has been dedicated to this problem, specifying different techniques to reduce imbalanced situations. In this paper, we present and compare strategies for recommending stations to users who wish to rent or return bikes in station-based bike-sharing systems. Our first contribution is a novel recommendation strategy based on queuing theory that recommends stations based on their utility to the user in terms of lower distance and higher probability of finding a bike or slot. Then, we go one step further, defining a strategy that recommends stations by combining the utility of a particular user with the utility of the global system, measured in terms of the improvement in the distribution of bikes and slots with respect to the expected future demand, with the aim of implicitly avoiding or alleviating balancing problems. We present several experiments to evaluate our proposal with real data from the bike sharing system BiciMAD in Madrid.

ON-LINE MODELLING AND FORECASTING OF A MOVING CAR INFORMATION USING TD-HMLP NETWORK

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Z. Saad ◽  
M. Y. Mashor ◽  
Wan Khairunizam
Keyword(s):  
Fuel Injection ◽  
Nonlinear Modeling ◽  
Trend Data ◽  
On Line ◽  
One Step ◽  
Multilayered Perceptron ◽  
The One ◽  
Recursive Prediction ◽  
Better Than ◽  
Modelling And Forecasting

The study proposed a model called trend data hybrid multilayered perceptron network (TD-HMLP) coupled with a modified recursive prediction error (MRPE) training algorithm as a nonlinear modeling. An on-line model was used to forecast speed, revolution and fuel balanced in a Proton Gen2 car tank. The car measured the injected fuel from fuel injection sensor and become an input for the TD-HMLP model to forecast the speed, revolution and fuel balanced in tank. These forecasted variables were also measured from the car sensors. The criterions for performances are based on the one step ahead forecasting (OSA), multi-step ahead forecasting (MSA) and adjusted R2. The forecasting result showed that TD-HMLP network is better than the conventional HMLP network to maintain higher value in adjusted R2 and produce better step in multi-step ahead forecasting. These preliminary results show that the proposed modeling approach is capable to be used as an on-line information forecaster of a moving car.

scholarly journals Superresolution Polarimetric ISAR Imaging Based on 2D CP-GTD Model

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Da-hai Dai ◽  
Jing-ke Zhang ◽  
Xue-song Wang ◽  
Shun-ping Xiao
Keyword(s):  
Real Data ◽  
Scattering Matrix ◽  
Geometrical Theory ◽  
Scattering Mechanism ◽  
New Approach ◽  
Scattering Centers ◽  
Isar Imaging ◽  
Geometrical Theory Of Diffraction ◽  
The One ◽  
Better Than

This paper presented a new approach to superresolution ISAR imaging based on a scattering model called coherent polarized geometrical theory of diffraction (CP-GTD) which is better matched to the physical scattering mechanism. The algorithm is a joint processing between polarization and superresolution essentially. It can also estimate the number, position, frequency dependence, span, and normalized scattering matrix of scattering centers instantaneously for each channel rather than the one which extracts parameters from each channel separately, and its performance is better than the latter because the fully polarized information is used. The superiority of the CP-GTD is verified by experiment results based on simulated and real data.

scholarly journals Business Innovations in the New Mobility Market during the COVID-19 with the Possibility of Open Business Model Innovation

2021 ◽  
Vol 7 (3) ◽  
pp. 195
Author(s):  
Katarzyna Turoń ◽  
Andrzej Kubik
Keyword(s):  
Business Models ◽  
Point Of View ◽  
Urban Transport ◽  
Transport Systems ◽  
Business Practices ◽  
Difficult Situation ◽  
The World ◽  
Bike Sharing ◽  
The One ◽  
Desk Research

The current difficult situation in the world caused by the spread of the COVID-19 virus has led to the development of problems in many branches of the economy. However, it has significantly affected transport, which on the one hand, is the bloodstream of the economy and, on the other hand, creates a threat for virus infection. Thus, in various countries, different mobility-related restrictions during pandemic policies around the world have been introduced. What is more, plans for initiatives after lockdown have also started to appear. Moreover, not have only cities introduced appropriate management policies, but companies have also started providing logistics services, especially those offering new mobility solutions. We found a literature and research gap indicating the recording or combination of the different types of business practices and innovations used worldwide in new mobility companies in the case of a pandemic situation. Therefore, this article is dedicated to the business innovations that appear in the new mobility industry during the COVID-19 pandemic in connection to post-pandemic transportation plans in Asia, Europe, and America. In this work, we conducted two-level research based on the desk research and expert research methodologies. From the business point of view, the results show that car-sharing systems (most organizational practices) and ride-sharing services (most safety practices) have most adapted their business models to pandemic changes. In turn, bike-sharing services have implemented the fewest business practices and innovations. From the urban transport systems point of view, the results show that European authorities have proposed the most plans and practice projects for new mobility after the pandemic compared to Asia and America. The obtained results indicate, however, that business practices do not coincide with the authorities’ plans for transport after the pandemic. Moreover, the results show a lack of complementarity between the developed practices and a reluctance to create open innovations in the new mobility industry. The article supports the management of new mobility systems in times of pandemic and in post-COVID reality.

Assessing and Predicting Mobility Improvement of Integrating Bike-Sharing into Multimodal Public Transport Systems

2021 ◽  
pp. 036119812110450
Author(s):  
Christian Kapuku ◽  
Seung-Young Kho ◽  
Dong-Kyu Kim ◽  
Shin-Hyung Cho
Keyword(s):  
Machine Learning ◽  
Transport Systems ◽  
Mobility Performance ◽  
Smart Card Data ◽  
Machine Learning Model ◽  
Multimodal Transport ◽  
Shared Mobility ◽  
Bike Sharing ◽  
The City ◽  
Better Than

New shared mobility services have become increasingly common in many cities and shown potential to address urban transportation challenges. This study aims to analyze the mobility performance of integrating bike-sharing into multimodal transport systems and develop a machine learning model to predict the performance of intermodal trips with bike-sharing compared with those without bike-sharing for a given trip using transit smart card data and bike-sharing GPS data from the city of Seoul. The results suggest that using bike-sharing in the intermodal trips where it performs better than buses could enhance the mobility performance by providing up to 34% savings in travel time per trip compared with the scenarios in which bus is used exclusively for the trips and up to 33% savings when bike-sharing trips are used exclusively. The results of the machine learning models suggest that the random forest classifier outperformed three other classifiers with an accuracy of 90% in predicting the performance of bike-sharing and intermodal transit trips. Further analysis and applications of the mobility performance of bike-sharing in Seoul are presented and discussed.

FORECASTING DAILY FOREIGN EXCHANGE RATE IN INDIA WITH ARTIFICIAL NEURAL NETWORK

2003 ◽  
Vol 48 (02) ◽  
pp. 181-199 ◽  
Author(s):  
CHAKRADHARA PANDA ◽  
V. NARASIMHAN
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Exchange Rate ◽  
Random Walk ◽  
Autoregressive Model ◽  
Out Of Sample ◽  
One Step ◽  
Artificial Neural ◽  
The One ◽  
Better Than

This study compares the efficiency of a non-linear model called artificial neural network with linear autoregressive and random walk models in the one-step-ahead prediction of daily Indian rupee/US dollar exchange rate. We find that neural network and linear autoregressive models outperform random walk model in in-sample and out-of-sample forecasts. The in-sample forecasting of neural network is found to be better than that of linear autoregressive model. As far as out-of-sample forecasting is concerned, the results are mixed and we do not find a "winner" model between neural network and linear autoregressive model. However, neural network is able to improve upon the linear autoregressive model in terms of sign predictions. In addition to this, we also find that the number of input nodes has greater impact on neural network's performance than the number of hidden nodes.

scholarly journals How Important is the Integration of Public Passenger Transport

2017 ◽  
Vol 8 (2) ◽  
pp. 59-68 ◽  
Author(s):  
Michaela Mrníková ◽  
Miloš Poliak ◽  
Patrícia Šimurková ◽  
Salvador Hernandez ◽  
Norbert Reuter
Keyword(s):  
The Other ◽  
Transport Systems ◽  
Passenger Transport ◽  
Other Hand ◽  
The One ◽  
The Individual

Abstract The significance of the issue of an effective mode of passenger transport is currently increasing. On the one hand, there is the increasing economic demand of public passenger transport, on the other hand, there is the growing traffic share of individual automobile transport. The objective of the paper is to analyze public passenger transport without mutual integration of individual transport systems resulting in the fact that it is not sufficiently able to compete with individual automobile transport. It is proposed the integration of different modes of public passenger transport as a way to increase the competitiveness of public passenger transport. Aim of this paper is to analyze the individual elements of integration systems and describe why integration of public passenger transport systems is needed.

scholarly journals Preparation of acicular mesoporous char sulfonic acid and its application for conversion of fructose to 5-hydroxymethylfurfural

BioResources ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 324-338
Author(s):  
Shuang Zhang ◽  
Xiaohui Han ◽  
Yanjie Liu ◽  
Ling Liu ◽  
Jiajun Yang ◽  
...  
Keyword(s):  
Sulfonic Acid ◽  
Mesoporous Structure ◽  
Amorphous Structure ◽  
Mass Ratio ◽  
Step Method ◽  
Average Pore ◽  
Promising Strategy ◽  
One Step ◽  
The One ◽  
Better Than

Acicular mesoporous char sulfonic acid was prepared through a one-step method of removing the template at the same time of sulfonation using ethylene tar (ET) as the carbon source and acicular nanometer magnesium hydroxide as the hard template. This method was judged as better than the two-step method of removing the template before sulfonation because it protected the mesoporous structure from damage to a certain extent. When the mass ratio of ET to Mg(OH)2 was 1:3 and carbonization temperature was 550 °C, the catalyst prepared using the one-step method had the highest activity. The obtained catalyst had an amorphous structure with a specific surface area of 446.5 m2/g, an acid density of 4.68 mmol/g, and an average pore diameter of 3.5 nm. When the catalyst was applied in the dehydration of fructose to synthesize 5-hydroxymethylfurfural (5-HMF), 97.5% fructose conversion and 80.1% 5-HMF yield can be obtained. The activity of the catalyst did not decrease after 5 cycles, which indicated that the catalyst had good stability. This research provides a promising strategy for preparation of mesoporous char sulfonic acid and comprehensive utilization of ET.

scholarly journals Influence Diagnostics in Log-Normal Regression Model with Censored Data

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Javeria Khaleeq ◽  
Muhammad Amanullah ◽  
Zahra Almaspoor
Keyword(s):  
Regression Model ◽  
Real Data ◽  
Biological Data ◽  
Skewed Distribution ◽  
Explanatory Variables ◽  
Normal Regression ◽  
Influence Diagnostics ◽  
One Step ◽  
The One ◽  
Log Normal

Dealing with the biological data, the skewed distribution is approximated by the Log-Normal Regression model (LNRM). Traditional estimation techniques for the LNRM are sensitive to unusual observations. These observations greatly affect the model analysis, which makes imprecise conclusions. To overcome this issue, we proposed to develop diagnostics measures based on local influence diagnostics to identify such curious observations in the LNRM under censoring. The proposed measures are derived by perturbing the case weight, response, and explanatory variables. Furthermore, we also consider the One-Step Newton-Raphson method and generalized cook’s distance. We study the Monte Carlo simulation and its application to real data to illustrate the developed approaches.

The Effect of Foregone Outcomes on Choices From Experience

2012 ◽  
Vol 59 (2) ◽  
pp. 55-67 ◽  
Author(s):  
Eldad Yechiam ◽  
Tim Rakow
Keyword(s):  
Cognitive Modeling ◽  
Model Fitting ◽  
Relative Weight ◽  
Simulation Models ◽  
Equal Weight ◽  
Individual Level ◽  
Binary Choices ◽  
One Step ◽  
The One ◽  
The Individual

We examined the relative weight given to obtained and foregone outcomes (i.e., outcomes from the non-chosen options) in repeated choices using cognitive modeling. Previous modeling studies have yielded mixed results. When participants’ choices are analyzed by models that predict the next choice ahead in a sequence of decisions, the results imply that people give less weight to foregone than to obtained outcomes. In contrast, in simulation models of n trials ahead, the results imply that, on average, people give equal weight to foregone and obtained outcomes. Using datasets of experience-based binary choices with fixed (stationary) payoff distributions (Erev & Haruvy, in press) and dynamic (nonstationary) payoff distributions (Rakow & Miler, 2009), we employed generalization tests at the individual level to examine whether the findings derived from the one-step-ahead method are due to overfitting. The results of trial-ahead model fitting implied that for the nonstationary tasks only, foregone outcomes received lower weight. However, when this dataset was assessed via generalization criteria at the individual level, equal weighting of foregone and obtained outcomes was the best assumption. This implies that overfitting is implicated in the superior fit of models that assume discounting of foregone outcomes.

Sign in / Sign up

Export Citation Format

Share Document