Data mining approach to analyse the road accidents in India

Jain, Ayushi; Ahuja, Garima; Anuranjana,; Mehrotra, Deepti

doi:10.1109/icrito.2016.7784948

Cited by 23 publications

(11 citation statements)

References 4 publications

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“…A data mining approach [14] was proposed to analyse road accidents in India. The intention of this approach was to create a model which sort out the heterogeneity of the data by grouping the similar objects together to find the accident prone areas in the country with respect to different accident factors.…”

Section: Methodsmentioning

confidence: 99%

“…The methods considered for analysis are Long Short-Term Memory, Deep Belief Network, supervised Latent Dirichlet Allocation, Support Vector Machine [4], Hybrid Clustering, association rule mining [5], Random Forest, AdaBoostM1, Naïve Bayes, J48, PART [6], Preliminary real time autonomous accident detection system [7], Naïve Bayes, C4.5, C&RT, RndTree, Decision List, rule induction, random tree [8], Multi-class Support Vector Machine [9], Naïve Bayes, J48, Random Forest algorithm, Apriori association rule mining [11], Decision Trees, Neural Networks [12], K means clustering, Decision tree [14] and Support Vector Machines [15]. The comparison is done by the experimental results of the methods in terms of accuracy, precision, recall and F-measure.…”

Section: Performance Evaluationmentioning

confidence: 99%

“…[9], Naïve Bayes, J48, Random Forest algorithm, Apriori association rule mining [11], Decision Trees, Neural Networks [12], K means clustering, Decision tree [14] and Support Vector Machines [15]. X axis denotes the methods and Y axis denotes the precision.…”

Section: B Precisionmentioning

confidence: 99%

See 2 more Smart Citations

A Review on Road Accident Detection Using Data Mining Techniques

N¹,

Punithavalli²

2018

ijarcs

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Transportation has evolved greatly over time. With modern technology, the automobile industry has obtained new heights with respect to comfort, speed, efficiency and security. Despite improvement in technology, there has been increase in the rate of accidents. A large number of precious lives are lost because of road traffic accidents every day. The common reason behind road accident is driver's mistake. It is essential to have effective road accident detection mechanism to save life. Data mining techniques are widely used for road accident detection. The main focus of this survey is to provide an overview of the literature in road accident detection with various techniques and approaches implemented in them, their merits and demerits etc. Comparison based on parameters is also done to prove the efficiency of the various road detection techniques and approaches. The comparison result shows the best road accident detection method.

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Section: Methodsmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

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A Review on Road Accident Detection Using Data Mining Techniques

N¹,

Punithavalli²

2018

ijarcs

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“…For afflicted artery region, atypical acumen [16] was proposed. The ballsy action amaranthine accumulation of abuse cars from the calm blur from accuracy cameras.…”

Section: Trafficmentioning

confidence: 99%

A Cognitive Contemplation of Road Accident Predicton Through Deep Learning

Priya*,

Priya

2019

IJITEE

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The research based on the vehicle accidents step to collect and structure a progressive secure transportation unfortunately vehicle crashes were unavoidable. The accident prediction related with the risky environment data collection and arrangements based on the high priority of reality of accidents. The social activity and roadway structures are useful in the progression of traffic security control approach. We believe that to secure the best possible setback decline impacts with limited budgetary resources, it is basic that measures be established on coherent and objective studies of the explanations behind mishaps and seriousness of wounds. A survey based on the different algorithms able to predict the road accidents prevention methods. This paper demonstrates a couple of models to predict the reality of harm that occurred in the midst of car accidents using three artificial intelligent approaches (AI). The proposed scheme contributes a neural systems prepared utilizing choice trees and fluffy c implies bunching strategy for division.

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“…The false alarms of preliminary real-time autonomous detection system are considerably high. [Jain et al (2016)] proposed a data mining approach to analyze road accidents in India. K-means clustering algorithm was used in the proposed data mining approach to group the similar area.…”

Section: Introductionmentioning

confidence: 99%

Bounded Memory Based Frequent Pattern Growth Approach With Deep Neural Network and Decision Tree for Road Accident Prediction

N¹,

Punithavalli²

2020

INDJCSE

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Frequent Pattern-growth (FP-growth) was introduced to categorize the accident locations. After the categorization of accident locations, accidents were classified by using J48. FP-growth has poor spatial and temporal locality issues. This is because of the construction process of FP-tree and its access behaviour of the mining algorithm. In this article, the issues of FP-growth are solved by introducing Bounded FPgrowth. It uses only a bounded portion of the primary memory using specialized memory management. When the tree grows out of the allocated memory, it is forced to be partially saved on secondary memory. The secondary memory is accessed in a block-by-block basis so that both temporal and spatial localities of FP-growth are optimized. After the memory management process, FP-growth is applied to categorize the accident locations. The attributes which have high support values are processed in Deep Neural Network J48 (DNNJ48) for classification of accident type. The analysis of experimental results proved that the proposed Bounded FP-growth-Deep Neural Network with J48 classifier (BFP-growth-DNNJ48) achieved higher accuracy (94%) when compared with existing methods like AdaBoost-SO and TASP-CNN.

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Data mining approach to analyse the road accidents in India

Cited by 23 publications

References 4 publications

A Review on Road Accident Detection Using Data Mining Techniques

A Review on Road Accident Detection Using Data Mining Techniques

A Cognitive Contemplation of Road Accident Predicton Through Deep Learning

Bounded Memory Based Frequent Pattern Growth Approach With Deep Neural Network and Decision Tree for Road Accident Prediction

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