Cauchy Density-Based Algorithm for VANETs Clustering in 3D Road Environments

Al-Obaidi, Ahmed Salih; Jubair, Mohammed Ahmed; Aziz, Izzatdin Abdul; Ahmad, Mohd Riduan; Mostafa, Salama A.; Mahdin, Hairulnizam; Al-Tickriti, Abdullah Talaat; Hassan, Mustafa Hamid

doi:10.1109/access.2022.3187698

Cited by 24 publications

(2 citation statements)

References 21 publications

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“…Various clustering methods, such as the commonly used Euclidean distance, employ distinct metrics to ascertain proximity. Ultimately, each data point becomes a member of a particular cluster [22]. The Cauchy clustering algorithm, on the other hand, relies on density.…”

Section: Trained Data By Using Cauchy Clustering Algorithmmentioning

confidence: 99%

Hybrid Model-Based Cauchy and Machine Learning Algorithms for IoTIntrusion Detection System

2023

IJIES

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The internet of things (IoT) cybersecurity presents a crucial challenge in our daily lives. An intrusion detection system (IDS) is valuable for protecting IoT data against malicious attacks. Moreover, intrusion datasets are often imbalanced in the number of attacks, increasing the bias in machine learning towards classes with high frequency. Normally, this case affects a training model's performance and ability to make a correct prediction. This paper presents a hybrid model that merges dynamic evolving cauchy clustering (DECS) with ranking classification. The DECS model operates based on the self-similarity principle, strategically distributing data into clusters to counteract the impact of imbalanced data. Furthermore, the rank classification algorithm predicts classes for new attacks. The NF-ToN-IoT dataset was used to test the validity performance of the proposed model and compared with standard machine learning algorithms (K-nearest neighbours, random forest, and decision tree). The proposed model outperforms standard cauchy clustering regarding mean square error (MSE), exhibiting a noteworthy reduction to 0.0534. Furthermore, the silhouette score, which indicates clustering quality, notably improved, reaching 0.4707. Additionally, the proposed model attained an accuracy rate of 67.77% and an F1-score of 76.52%, while the standard Random Forest achieved better accuracy at 66.34% and an F1-score of 68.48%.

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Section: Trained Data By Using Cauchy Clustering Algorithmmentioning

confidence: 99%

Hybrid Model-Based Cauchy and Machine Learning Algorithms for IoTIntrusion Detection System

2023

IJIES

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“…China only began to introduce construction projects from the international Frontiers in Ocean Engineering community in the 1980s. With the continuous improvement of economic level and the wide application and progress of science and technology since the implementation of the reform and opening-up policy, great changes have taken place in the international construction engineering field [3][4]. The state has issued a series of relevant normative documents to ensure the quality of construction projects, shorten the construction period, and promote the survival of the fittest of construction enterprises to achieve faster and better benefits.…”

Section: Introductionmentioning

confidence: 99%

Quality Management of Offshore Engineering Project Based on Clustering Algorithm

2022

FOE

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With the rapid development of social economy, environmental problems have become increasingly prominent. Quality management is an important link in offshore engineering projects. This paper first introduces the research status at home and abroad in recent years, summarizes the construction background and main problems of China's shipbuilding industry and water conservancy projects, and then analyzes in detail the common methods and applications in the field of marine engineering technology and construction engineering, Finally, it is proposed to establish a perfect and effective quality management mechanism for construction projects using clustering method and verify that this mode plays a good role in actual engineering projects through specific cases. The performance test of the management system is carried out. The test results show that the quality management system for offshore engineering projects based on Clustering algorithm has a short data processing time, low delay time and low memory consumption

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Centralized RSU Deployment Strategy for Effective Communication in Multi-hop Vehicular Adhoc Networks (VANETs)

Rashid,

Audah,

Hamdi

et al. 2023

Lecture Notes in Networks and Systems

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Cauchy Density-Based Algorithm for VANETs Clustering in 3D Road Environments

Abstract: We wish to acknowledge the tremendous support from Department of Computer and Information Sciences (CISD), UTP, Malaysia for all academic support and facilities.

Cited by 24 publications

References 21 publications

Hybrid Model-Based Cauchy and Machine Learning Algorithms for IoTIntrusion Detection System

Hybrid Model-Based Cauchy and Machine Learning Algorithms for IoTIntrusion Detection System

Quality Management of Offshore Engineering Project Based on Clustering Algorithm

Centralized RSU Deployment Strategy for Effective Communication in Multi-hop Vehicular Adhoc Networks (VANETs)

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