This article provides a bivariate binary logit model and statistical inference procedures for parameter estimation and hypothesis testing. The bivariate binary logit (BBL) model is an extension of the binary logit model that has two correlated binary...
Session-based recommendation predicts an anonymous user’s next action, whether she or he is likely to purchase based on the user’s behavior in the current session as sequences. Most recent research on session-based recommendations makes p...
Expanding university campuses face a dual challenge: meeting higher internal travel demand while reducing congestion and emissions. Using stated-preference data (412 respondents; 9 choice tasks per person), this study quantifies the expected adoption...
A generalized multinomial logit (G-MNL) model is proposed to alleviate the four challenges inherent to the conditional logit model, including (1) simultaneous unidentifiability, (2) the immediacy of decision-making, (3) the homogeneity of preferences...
This study presents a comprehensive comparative analysis of the effect of route set size on stochastic user equilibrium (SUE) traffic assignment, focusing on both logit-based (Multinomial Logit (MNL) and Path Size Logit (PSL)) and weibit-based models...
The currently available transport modeling tools are used to evaluate the effects of behavior change. The aim of this study is to analyze the interaction between the transport mode choice and travel behavior of an individual—more specifically, to ide...
In binomial regression, a link function is used to join the linear predictor variables and the expectation of the response variable. This paper proposes a flexible link function from a new class of generalized logistic distribution, namely a flexible...
Looking ahead to the future-stage autonomous transportation system (ATS), personal mobility service (PMS) aims to provide the recommended travel options based on both microscopic individual travel demand and the macroscopic supply system objectives....
A new approach for estimating the aggregate hierarchical logit model is presented. Though usually derived from random utility theory assuming correlated stochastic errors, the model can also be derived as a solution to a maximum entropy problem. Unde...
Many studies have analyzed the road characteristics that affect the severity of truck crashes. However, most of these studies have only examined road alignment or grade separately, without considering their combined effects. The purpose of this artic...
Customer overall satisfaction regarding a public transport system is dependent on the satisfaction of the users with the attributes that make up the service, as well as the contribution that each of these attributes makes to explain the overall satis...
This paper focuses on business financial health evaluation with the use of selected mathematical and statistical methods. The issue of financial health assessment and prediction of business failure is a widely discussed topic across various industrie...
Predicting financial distress is one of the most well-known issues in corporate finance. Investors and other stakeholders often use prediction models as relevant tools for identifying weaknesses to eliminate potential threats to business partners. Th...
Few-shot learning (FSL) is a challenging problem. Transfer learning methods offer a straightforward and effective solution to FSL by leveraging pre-trained models and generalizing them to new tasks. However, pre-trained models often lack the ability...
Maximum entropy models are often used to describe supply and demand behavior in urban transportation and land use systems. However, they have been criticized for not representing behavioral rules of system agents and because their parameters seems to...
Despite the availability of electronic navigators and automated vehicles, static wayfinding instructions remain widely used due to their resistance to signal disturbances, as well as their economic and environmental advantages over electronic signs....
In a recent study, it was demonstrated that the maximum simulated likelihood (MSL) estimator produces significant biases when applied to the bivariate normal and bivariate Poisson-lognormal models. The study’s conclusion suggests that similar b...
The effective identification of the economic withholding behavior of the generators can help ensure the fair operation of the electricity market. A SCAD-logit model is proposed to improve the performance of the logit model for the massive data of ele...
Accurate detection of fetal distress from cardiotocography (CTG) is clinically critical but remains subjective and error-prone. In this research, we present a leakage-safe Calibrated Global Logit Fusion (CGLF) framework that couples TabNet’s sp...
Studying the location of an airport is essential for optimizing its functionality, ensuring safety, and maximizing its economic benefits. There are many airports located within a short distance of each other, and users can often choose to travel betw...
A model-building framework is proposed that combines two data mining techniques, TreeNet and association rules analysis (ASA) with multinomial logit model building. TreeNet provides plots that play a key role in transforming quantitative variables in...
Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions. Most BO methods rely on Gaussian process (GP) surrogates, which perform well in continuous domains but encounter difficulties when decision variables...
This study evaluates fixed and learned logit fusion for clip-level pre-drowsiness classification on an adaptively curated cohort from the University of Texas at Arlington Real-Life Drowsiness Dataset (UTA-RLDD). The target is an operationally defined...
In this paper, the government behavior of leasing different land use rights in Beijing, China, is analyzed using data analysis based on the multinomial logit model. The factors that lead the government to lease different land use rights are considere...
This study investigates the role of symmetric probabilistic models in predicting financial distress in the automotive industry, with a focus on companies operating in the Slovak Republic. Financial distress prediction represents a binary classificati...
Health preference research (HPR) is the subfield of health economics dedicated to understanding the value of health and health-related objects using observational or experimental methods. In a discrete choice experiment (DCE), the utility of objects...
The beef cattle industry is an important part of herbivorous animal husbandry and an important industry to enrich the dietary structure of residents and promote the income of farmers and herdsmen. The cow is an important foundation to support the hea...
In this study, we propose two models for predicting people’s activity. The first model is the pedestrian distribution prediction (or postdiction) model by multiple regression analysis using space syntax indices of urban fabric and people distribution...
Federated learning under label skew aggregates models trained with different local class distributions. Local logit adjustment can reduce class-dependent bias, but the adjusted loss updates both the encoder and classifier in client-specific direction...
Theoretically speaking, the data of a stated preference survey could be suggested for the calibration of a stochastic route choice model. However, it is unrealistic to implement the questionnaire survey for such a large number of alternative routes....
This study quantifies the impact of individual attributes, the built environment, and travel characteristics on the use of bike-sharing and the willingness of shifting to bike-sharing-related travel modes (bike-sharing combined with other public tran...
Traffic crashes involving pedestrians have a high frequency in developing countries. Among road users, pedestrians are the most vulnerable, as their involvement in traffic crashes is usually followed by severe and fatal injuries. This study aims to i...
Over the past few decades, demarketing has come up as an unorthodox but potentially strong approach that can be used to counter the negative effects of oversaturation in tourism destinations. This study investigates the difference that demarketing st...
Parking shortages and high costs in Chinese central business districts (CBDs) remain major urban challenges. Emerging automated vehicles (AVs) are expected to diversify parking options and mitigate these problems. However, AV users’ parking pre...
Accurate volumetric quantification of brain tumor subregions in magnetic resonance imaging (MRI) is sensitive to local prediction bias, because boundary over-expansion, missed enhancing foci, and class confusion at subregion transitions can propagate...
Parking reservation systems (PRS) are promoted as smart urban parking tools, yet their continued use remains limited because users face both technological uncertainty and schedule-related uncertainty. This study develops a behavioral analysis framewo...
The hotel market has become extremely competitive over the past years. Hotels try to differentiate themselves through their services and facilities. To make the best choice when searching for accommodation, guests increasingly use rating systems of b...
Transportation planning plays an essential role in improving the transportation system. Therefore, planners should have the ability to forecast the response of transportation demand to changes in the characteristics of the travellers. This has led re...
Long-tailed data are very common in industrial scenarios because equipment failures occur with a low probability, resulting in far fewer faulty samples than normal ones. However, when facing long-tailed data distributions, existing deep learning meth...
31 October 2021
Traditional biomass utilization is connected with negative environmental and human health impacts. However, its transition to cleaner cooking fuels is still low where the household’s fuels preferences play an important role in the process. To examine...
This study tests whether the random-parameter structure of a Multinomial Logit crash-type model is itself spatially stable, using individual-level likelihood-ratio tests estimated separately for Ankara (28,825 crashes) and İzmir (24,280 crashes)...
Automatic Speech Recognition (ASR) provides a new way of human-computer interaction. However, it is vulnerable to adversarial examples, which are obtained by deliberately adding perturbations to the original audios. Thorough studies on the universal...
The basic function of the Park and Ride (P&R) facility is to allow users to leave their vehicle on the outskirts of the city and to continue their journey to the city center using means of public transport, e.g., bus, tram, trolleybus, subway, tr...
Motorcycles are a prominent contributor to most fatalities arising from traffic incidents, primarily due to drivers’ failure to adhere to traffic laws. Notably, differences in traffic violation frequency between urban and rural motorcyclists ca...
Sperm morphology is one of the most critical indicators of male fertility. This paper presents a deep learning-based approach to classify sperm cells into 18 morphological classes, including one normal and 17 abnormal types. Two state-of-the-art conv...
For most studies that have been carried out, a country’s level of income and aggregate wealth go a long way in shaping the overall welfare of citizens therein. This study seeks to investigate the relationship between wealth status and education...
In high-density urban areas, pedestrian route choice behavior is influenced differently by the attributes of the objective environment, depending on the purpose of the trip. To explore this issue, this paper first constructs the traditional Path Size...
Demand-Responsive Transport (DRT) services ensure the implementation of more sustainable transport solutions and focuses on the creation of more flexible and personalised public transport systems. They help to reduce the use of cars, improve service...
With the considerable increase in ownership of motor vehicles, traffic crashes have become a challenge. This paper presents a study of naturalistic driving conducted to collect driving data. The experiments were performed on different road types in t...
Understanding the risk factors of e-bike collisions can improve e-bike riders’ safety awareness and help traffic professionals to develop effective countermeasures. This study investigates risk factors that significantly contribute to the sever...
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