An Overview of Machine Learning Techniques for Evaluation of Pavement Condition

Chavan, Aradhana; Pimplikar, S. S.; Deshmukh, Ashlesha

doi:10.1109/icccmla56841.2022.9989164

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…В качестве одного из них гипотетически может выступить машинное обучение (МО), уже доказавшее свою применимость для решения огромного спектра разнородных прикладных задач: программный инжиниринг [1], управление состоянием дорожного покрытия [2], построение сетей 5G [3], повышение обучаемости студентов [4], обеспечение непрерывности функционирования Интернета вещей [5], -и многие другие. Исходя из этих соображений, далее в статье будет проведен аналитический обзор возможностей МО, которые могут быть применены для поиска уязвимостей в ПО -что и определяет предметную область настоящего исследования.…”

Section: Introductionunclassified

Machine Learning vs Software Vulnerability Detection: Applicability Analysis and Conceptual System Synthesis

Leonov,

Buinevich

2023

jour

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The article is devoted to the searching for vulnerabilities in software problem, as well as the possibilities of application of such a promising area in information technology as machine learning. For this purpose, a review of scientific publications in this area from Russian and foreign citation databases is made. A comparative analysis of the review's results was made according to the following criteria: publication year, application field, idea, solved problem of machine learning, degree of realization of its models and methods; for each criterion basic conclusions were drawn. As a result, 7 principles of building a new conceptual system of searching for vulnerabilities in software with the help of machine learning are proposed, the short meaning of which is as follows: program's multilateral study, combination of known methods, the use of machine learning in each method and algorithm of its management, the possibility of correcting the expert's work, storing information in a database and its synchronization with external, advisory nature of the found vulnerabilities; single software application usage. Based on the stated principles, a graphical scheme of such a system has been developed.

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Section: Introductionunclassified

Machine Learning vs Software Vulnerability Detection: Applicability Analysis and Conceptual System Synthesis

Leonov,

Buinevich

2023

jour

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Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions

Tamagusko,

Gomes Correia,

Ferreira

2024

Infrastructures

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Effective road pavement management is vital for maintaining the functionality and safety of transportation infrastructure. This review examines the integration of Machine Learning (ML) into Pavement Management Systems (PMS), presenting an analysis of state-of-the-art ML techniques, algorithms, and challenges for application in the field. We discuss the limitations of conventional PMS and explore how Artificial Intelligence (AI) algorithms can overcome these shortcomings by improving the accuracy of pavement condition assessments, enhancing performance prediction, and optimizing maintenance and rehabilitation decisions. Our findings indicate that ML significantly advances PMS capabilities by refining data collection processes and improving decision-making, thereby addressing the intricacies of pavement deterioration. Additionally, we identify technical challenges such as ensuring data quality and enhancing model interpretability. This review also proposes directions for future research to overcome these hurdles and to help stakeholders develop more efficient and resilient road networks. The integration of ML not only promises substantial improvements in managing pavements but is also in line with the increasing demands for smarter infrastructure solutions.

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An Overview of Machine Learning Techniques for Evaluation of Pavement Condition

Cited by 2 publications

References 27 publications

Machine Learning vs Software Vulnerability Detection: Applicability Analysis and Conceptual System Synthesis

Machine Learning vs Software Vulnerability Detection: Applicability Analysis and Conceptual System Synthesis

Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions

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