Bo Liu, Libin Shen, Huanling You, Yan Dong, Jianqiang Li and Yong Li
The influence of road surface temperature (RST) on vehicles is becoming more and more obvious. Accurate predication of RST is distinctly meaningful. At present, however, the…
Abstract
Purpose
The influence of road surface temperature (RST) on vehicles is becoming more and more obvious. Accurate predication of RST is distinctly meaningful. At present, however, the prediction accuracy of RST is not satisfied with physical methods or statistical learning methods. To find an effective prediction method, this paper selects five representative algorithms to predict the road surface temperature separately.
Design/methodology/approach
Multiple linear regressions, least absolute shrinkage and selection operator, random forest and gradient boosting regression tree (GBRT) and neural network are chosen to be representative predictors.
Findings
The experimental results show that for temperature data set of this experiment, the prediction effect of GBRT in the ensemble algorithm is the best compared with the other four algorithms.
Originality/value
This paper compares different kinds of machine learning algorithms, observes the road surface temperature data from different angles, and finds the most suitable prediction method.
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Keywords
Ning Zhang and Bo Liu
This paper aims to find out how business aligns with robotic process automation (RPA) and whether the alignment has the same factors as for IT–business alignment.
Abstract
Purpose
This paper aims to find out how business aligns with robotic process automation (RPA) and whether the alignment has the same factors as for IT–business alignment.
Design/Methodology/Approach
Condition configurations for positive and negative impact for business alignment with RPA.
Findings
The positive and negative configurations that possibly impact business alignment with RPA.
Research limitations/implications
There are some human instincts during conditions dichotomization and limited number of cases.
Practical implications
The findings can be used to guide practice application in real industry.
Originality/value
This paper adopted crisp-set qualitative comparative analysis to find condition configurations for alignment of business and RPA for more generalization.
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Bo Liu, Jingwen Hou, Xiaoping Ma, Mengtong Shi, Sibo Lu and Ruoxuan Wang
Due to the conflicts between left turn traffic and opposite straight-going traffic in urban traffic network, some of the traffic lanes cannot be used to discharge vehicles during…
Abstract
Purpose
Due to the conflicts between left turn traffic and opposite straight-going traffic in urban traffic network, some of the traffic lanes cannot be used to discharge vehicles during its green phases and the intersection capacity can be greatly reduced. This study/paper aims to reduce the effect of conflicts and increase its capacity through the reasonable pre-signal phase time with the exchangeable lanes.
Design/methodology/approach
This paper took into consideration various influence factors to intersection capacity and formulated the capacity optimization model based on 0-1 mixed-integer programming model. This model is efficiently solved by standard branch-and-bound algorithms.
Findings
The authors took an intersection as an example and solved the optimal signal timing and entrance lane capacity via this model. Then, simulations were carried out to verify the effect of the exchangeable lanes strategy of this intersection through the simulation software VISSIM and take the traffic volume and delay as outputs, which indicated that this model has better performance.
Originality/value
The front-end control strategy can not only exploit the full potential of the intersection but also significantly improve the operational efficiency of the intersection. It plays a positive role in improving urban intersection congestion.
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Elias Shohei Kamimura, Anderson Rogério Faia Pinto and Marcelo Seido Nagano
This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).
Abstract
Purpose
This paper aims to present a literature review of the most recent optimisation methods applied to Credit Scoring Models (CSMs).
Design/methodology/approach
The research methodology employed technical procedures based on bibliographic and exploratory analyses. A traditional investigation was carried out using the Scopus, ScienceDirect and Web of Science databases. The papers selection and classification took place in three steps considering only studies in English language and published in electronic journals (from 2008 to 2022). The investigation led up to the selection of 46 publications (10 presenting literature reviews and 36 proposing CSMs).
Findings
The findings showed that CSMs are usually formulated using Financial Analysis, Machine Learning, Statistical Techniques, Operational Research and Data Mining Algorithms. The main databases used by the researchers were banks and the University of California, Irvine. The analyses identified 48 methods used by CSMs, the main ones being: Logistic Regression (13%), Naive Bayes (10%) and Artificial Neural Networks (7%). The authors conclude that advances in credit score studies will require new hybrid approaches capable of integrating Big Data and Deep Learning algorithms into CSMs. These algorithms should have practical issues considered consider practical issues for improving the level of adaptation and performance demanded for the CSMs.
Practical implications
The results of this study might provide considerable practical implications for the application of CSMs. As it was aimed to demonstrate the application of optimisation methods, it is highly considerable that legal and ethical issues should be better adapted to CSMs. It is also suggested improvement of studies focused on micro and small companies for sales in instalment plans and commercial credit through the improvement or new CSMs.
Originality/value
The economic reality surrounding credit granting has made risk management a complex decision-making issue increasingly supported by CSMs. Therefore, this paper satisfies an important gap in the literature to present an analysis of recent advances in optimisation methods applied to CSMs. The main contribution of this paper consists of presenting the evolution of the state of the art and future trends in studies aimed at proposing better CSMs.
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Prajowal Manandhar, Prashanth Reddy Marpu and Zeyar Aung
We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector…
Abstract
We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.
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In terms of understanding the new issues emerging in the practice of monetary policies and how to evaluate the latest theories of monetary policy, this paper proposes referring to…
Abstract
Purpose
In terms of understanding the new issues emerging in the practice of monetary policies and how to evaluate the latest theories of monetary policy, this paper proposes referring to Das Kapital and developing a monetary policy theory grounded in Marxist political economy.
Design/methodology/approach
Based on the discussion of interest-bearing capital in Das Kapital and using a heterogeneous agent model, this paper tries to explain the determining mechanism of interest rate, leverage ratio, and asset price.
Findings
The research finds that if there are differences in the techniques possessed by capital, the resulting disparities in production efficiency will lead to differences in profit rates and further influence the functional choices of capital in the movement of social total capital. Thus, with the formation of lending relationships, interest rates, leverage ratios, and asset prices will be endogenously determined simultaneously. Moreover, as the degree of technological diffusion influences the industrial capitalists’ willingness to take loans as well as the level of profit rates, there may be counter-cyclical changes in the returns on productive investment and financial investment at different stages of the technology life cycle, contributing to diverting funds out of the real economy. Besides, this paper discusses the challenges, tools, and goals of monetary policy within the credit money system.
Originality/value
Clarify the intrinsic mechanism of the functional differentiation of capital determined by heterogeneous technologies and exogenous capital-labor relation and analyze the impact of capital differentiation on the economy.
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Ya-Fei Liu, Yu-Bo Zhu, Hou-Han Wu and Fangxuan (Sam) Li
This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g…
Abstract
Purpose
This study aims to explore the differences in the tourists’ perceived destination image on travel e-commerce platforms (e.g. Ctrip and Fliggy) and social media platforms (e.g. Xiaohongshu and Weibo).