Modeling Lane-Changing Behaviors in Merging Areas of Urban Expressways in Nanjing, China

2020 ◽  
Vol 2674 (7) ◽  
pp. 480-493
Author(s):  
Quan Chen ◽  
Hao Wang ◽  
Changyin Dong
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Regression Model ◽  
Video Processing ◽  
Logistic Regression Model ◽  
Decision Making Process ◽  
Lane Changing ◽  
Traffic Demand ◽  
Processing Algorithms ◽  
Precision Testing

Merging bottlenecks in urban expressways have attracted much attention in recent years. In this paper, vehicular mandatory lane-changing (MLC) data are collected from Yingtian Avenue in Nanjing, China using cameras. Based on a series of video processing algorithms, 656 MLC behaviors of 1,560 vehicles are extracted from videos. A logistic regression model is proposed to depict MLC at the merging bottleneck and estimate the possibility of accepting gaps for merging, which is validated by precision testing and simulation. During the simulation, a discretionary lane-changing (DLC) model is utilized and calibrated to describe vehicular DLC behaviors for the sake of consistency and completeness. Finally, by simulating different arrival rates of mainline and ramp, a linear regression model is built to predict breakdown at merging bottlenecks. According to data analysis, the MLC model represents high precision during the decision-making process. Besides, the breakdown prediction model implies strong correlation between traffic demand and breakdown occurrence.

scholarly journals Decision-Making Process in Colon Disease and Crohn’s Disease Treatment

2018 ◽  
Vol 12 (3) ◽  
pp. 227-231
Author(s):  
Agnieszka Dardzinska ◽  
Anna Kasperczuk
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Crohn’S Disease ◽  
Crohn's Disease ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Recommendation System ◽  
Decision Making Process ◽  
Disease Treatment ◽  
Precise Diagnosis

Abstract The article presents the process of building a logistic regression model, which aims to support the decision-making process in medicine. Currently, there is no precise diagnosis for ulcerative colitis (UC) and Crohn's disease (CD). Specialist physicians must exclude many other diseases occurring in the colon. The first goal of this study is a retrospective analysis of medical data of patients hospitalized in the Department of Gastroenterology and Internal Diseases and finding the symptoms differentiating the two analyzed diseases. The second goal is to build a system that clearly points to UC or CD, which shortens the time of diagnosis and facilitates the treatment of patients. The work focuses on building a model that can be the basis for the construction of classifiers, which are one of the basic elements in the medical recommendation system. The developed logistic regression model will define the probability of the disease and will indicate the statistically significant changes that affect the onset of the disease. The value of probability will be one of the main reasons for the decision.

scholarly journals Determinants of Women Empowerment at Domestic and Non-domestic Issues: Evidence from Chapai Nawabganj District in Bangladesh

1970 ◽  
Vol 3 ◽  
pp. 143-162 ◽  
Author(s):  
Mosiur Rahman ◽  
Uzzal K Karmaker ◽  
Abdur R Mia
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Mass Media ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Women Empowerment ◽  
Contributing Factors ◽  
Freedom Of Movement ◽  
Women's Participation ◽  
Equal Right

This paper makes an attempt to investigate the determinants of women empowerment at domestic and non-domestic issues in Bangladesh by examining the situation prevailing in one particular area of Chapai Nawabganj district using the information from 500 ever married women within the reproductive span (15-49 years). Our study documented that, although a large percentage of women were enjoying empowerment at various domestic and non domestic related issues still it is not in a satisfactory level. Only 4.5% women could take decision for child health care activities and 51.6% could caste vote with their own decision and 59.0% respondents could handled the daily expenditure for the family. Findings revealed that 79.7% respondent's expressed their opinion having freedom of movement outside the home without husband's permission and 83.0% respondents gave their opinion for equal right in education of son and daughter which seem to be a good indication regarding women's empowerment. From the logistic regression model considering decision-making power for household affairs as the dependent variable we saw that urban respondents, respondents living in combined family, having mass media facility have more decision making power regarding household affairs. The model also shows that as the level of education of the respondents increases their decision making power also rises From the logistic regression model concerning decision-making power about casting vote the main contributing factors that have significant impact on women's decisions making power towards vote were found to be respondent's education, type of family, mass media exposure, age at marriage, daily household expenditure, freedom of movement, decision for household affairs and women's participation as representative. Key words: household affairs; freedom of movement; caste of vote; daily expenditure; logistic regression analysis. DOI: 10.3126/dsaj.v3i0.2784 Dhaulagiri Journal of Sociology and Anthropology Vol.3 2009 143-162

scholarly journals Substation Decision-making Platform Based on Artificial Intelligence

2021 ◽  
Author(s):  
Jianhua Qin ◽  
Xueqiong Zhu ◽  
Zhen Wang ◽  
Jingtan Ma ◽  
Shan Gao ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Logistic Regression ◽  
Quantitative Analysis ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Final Decision ◽  
Equipment Failure ◽  
Operational Data ◽  
Electrical Data

In view of the actual needs faced by the substation maintenance, this paper proposes a kind of substation decision-making platform based on artificial intelligence. The platform formalizes and integrates the basic data, electrical data and the operational data of the equipment, qualitatively triggers the maintenance task abide by the result of the logistic regression model, provides further results of data processing through quantitative analysis, and provides knowledge navigation to the operation guidance of the corresponding equipment. The platform matches the electrical data with the inference engine stored in the knowledge base. If the data match the condition of the inference successfully, the inference is triggered and the action is executed. The result is provided to the relevant staff as a suggestion to assist the final decision. After the task is completed, the cause, effect and solution of the equipment failure are backfilled and expanded into the equipment base as a new instance.  

Modelling and Analyzing Consumer Behaviour Employing Observational Data

2018 ◽  
Vol 3 (1) ◽  
pp. 42-57
Author(s):  
Yuliia Kyrdoda ◽  
A.Malek Hammami ◽  
Drakos Periklis ◽  
Panagiotis Kaldis
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Consumer Behaviour ◽  
Explanatory Power ◽  
Demographic Characteristics ◽  
Marketing Strategies ◽  
Purchase Behavior ◽  
Factors Affecting

The purpose of this article is to investigate and model retail consumer purchase behavior and determine factors affecting the purchasing decision. The following hypotheses were verified: H1 tests the influence of “Decision-making Time” over “Final Purchase”. H2 tests “Promotion” over “Final Purchase”. H3, H4 and H5 were established to test the influence of demographic characteristics (respectively: Age, Nationality, Gender) over “Final Purchase”. SPSS 23 was used to analyze the collected data from the observations completed in the supermarket. In order to identify the explanatory power of the variables, a Logistic Regression model was developed. Empirical findings indicated that demographic characteristics (Age, Nationality, Gender), as well as “Time” and “Promotion,” have a significant effect on “Purchase” and that “Time” has a greater impact on “Purchase.” These results could be used to design marketing strategies in order to increase sales. However, a few limitations occurred during the study such as observation timing, the unicity of location and observers' subjectivity.

scholarly journals Can ESG Performance Affect Bond Default Rate? Evidence from China

2020 ◽  
Vol 12 (7) ◽  
pp. 2954 ◽  
Author(s):  
Peixin Li ◽  
Rongxi Zhou ◽  
Yahui Xiong
Keyword(s):  
Decision Making ◽  
Corporate Governance ◽  
Logistic Regression ◽  
Logistic Regression Model ◽  
Decision Making Process ◽  
National Context ◽  
Social Responsibilities ◽  
Default Rate ◽  
Default Risks ◽  
Improve Stability

Capturing determinants of bond default risks has aroused heated discussions ever since the “rigid payment” system collapsed in China. Within this context; this paper aims to clarify the relation between an issuer’s environmental; social; and corporate (ESG) performance and its bond default rate. We developed an ESG factors-embedded Logistic Regression model to empirically examine Chinese default bonds and outstanding industrial bonds from 2014 to 2019. Results indicate that the bond default rate is positively correlated with the company’s energy consumption and negatively correlated with its attention to social responsibilities; and corporate governance; in addition to its financial performances. In conclusion; to fully take ESG factors into consideration during the decision-making process and daily operations might improve stability and credibility of corporations in modern Chinese national context.

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