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Title: :  ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM
PaperId: :  21734
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 5 2023
DUI:    16.0415/IJARIIE-21734
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
JAYA SHREE RBANNARI AMMAN INSTITUTE OF ENGINEERING
TRISHA CBANNARI AMMAN INSTITUTE OF ENGINEERING
ANUSHREE NBANNARI AMMAN INSTITUTE OF ENGINEERING

Abstract

MACHINE LEARNING
Keywords - Traffic incident detection, factor analysis, weighted random forest, unbalanced data, and SMOTE analysis.
In order to reduce casualties and property damage, efficient and precise traffic incident detection is essential. In order to address the issue of unbalanced event data, this work offers a novel methodology known as FA-WRF (Factor Analysis and Weighted Random Forest). This approach combines dimensionality reduction through factor analysis with classification using weighted random forests, data preparation through the Synthetic Minority Over-sampling Technique (SMOTE), and data preparation with SMOTE. The included feature of severity detection is highlighted in this paper, as is the evaluation of the FA-WRF model using well-established metrics such as detection rate, false alarm rate, classification rate, and area under the receiver operating characteristic curve (AUC). The superiority of the FA-WRF model is illustrated using real-world expressway traffic data characterized by imbalanced incidents through thorough comparisons with various machine learning algorithms such as Support Vector machine, k-nearest neighbors, Logistic Regression, and decision trees. In addition to advancing incident detection, our technique has encouraging prospects for enhancing traffic management procedures and well-informed decision-making procedures in the context of transportation networks.

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IJARIIE JAYA SHREE R, TRISHA C, and ANUSHREE N. "ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 5 2023 Page 1312-1322
MLA JAYA SHREE R, TRISHA C, and ANUSHREE N. "ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM." International Journal Of Advance Research And Innovative Ideas In Education 9.5(2023) : 1312-1322.
APA JAYA SHREE R, TRISHA C, & ANUSHREE N. (2023). ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM. International Journal Of Advance Research And Innovative Ideas In Education, 9(5), 1312-1322.
Chicago JAYA SHREE R, TRISHA C, and ANUSHREE N. "ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 5 (2023) : 1312-1322.
Oxford JAYA SHREE R, TRISHA C, and ANUSHREE N. 'ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, 2023, p. 1312-1322. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/ENHANCED_TRAFFIC_INCIDENT_DETECTION_USING_FACTOR_ANALYSIS_AND_WEIGHTED_RANDOM_FOREST_ALGORITHM_ijariie21734.pdf (Accessed : ).
Harvard JAYA SHREE R, TRISHA C, and ANUSHREE N. (2023) 'ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM', International Journal Of Advance Research And Innovative Ideas In Education, 9(5), pp. 1312-1322IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/ENHANCED_TRAFFIC_INCIDENT_DETECTION_USING_FACTOR_ANALYSIS_AND_WEIGHTED_RANDOM_FOREST_ALGORITHM_ijariie21734.pdf (Accessed : )
IEEE JAYA SHREE R, TRISHA C, and ANUSHREE N, "ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, pp. 1312-1322, Sep-Oct 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/ENHANCED_TRAFFIC_INCIDENT_DETECTION_USING_FACTOR_ANALYSIS_AND_WEIGHTED_RANDOM_FOREST_ALGORITHM_ijariie21734.pdf [Accessed : ].
Turabian JAYA SHREE R, TRISHA C, and ANUSHREE N. "ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 5 ().
Vancouver JAYA SHREE R, TRISHA C, and ANUSHREE N. ENHANCED TRAFFIC INCIDENT DETECTION USING FACTOR ANALYSIS AND WEIGHTED RANDOM FOREST ALGORITHM. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(5) : 1312-1322. Available from: https://ijariie.com/AdminUploadPdf/ENHANCED_TRAFFIC_INCIDENT_DETECTION_USING_FACTOR_ANALYSIS_AND_WEIGHTED_RANDOM_FOREST_ALGORITHM_ijariie21734.pdf
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