How to cite this paper
Pritee, K & Garg, R. (2023). Criticality trend analysis based on highway accident factors using improved data mining algorithms.Journal of Future Sustainability, 3(1), 9-22.
Refrences
Abdel-Aty, M. A. & Radwan, A. E. (2000). Modeling traffic accident occurrence and involvement. Accident Analysis & Prevention, 32(5), 633-642.
Akaike, H. (1987). Factor analysis and AIC. In Selected Papers of Hirotugu Akaike. Springer, New York, NY, 371-386.
Barai, S. K. (2003). Data mining applications in transportation engineering. Transport, 18(5), 216-223.
Chang LY, Chen WC (2005) Data mining of tree-based models to analyze freeway accident frequency. Journal of safety research. 36(4), 365-75.
Chaturvedi, A., Green, P. E., & Caroll, J. D. (2001). K-modes clustering. Journal of classification, 18(1), 35-55.
Chen, W. H., & Jovanis, P. P. (2000). Method for identifying factors contributing to driver-injury severity in traffic crashes. Transportation Research Record, 1717(1), 1-9.
Depaire, B., Wets, G., & Vanhoof, K. (2008). Traffic accident segmentation by means of latent class clustering. Acci-dent Analysis & Prevention, 40(4), 1257-1266.
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI mag-azine, 17(3), 1-37.
Fraley, C., & Raftery, A. E. (1998). How many clusters? Which clustering method? Answers via model-based cluster analysis. The computer journal, 41(8), 578-588.
Han, J., Pei, J., & Yin, Y. (2000). Mining frequent patterns without candidate generation. In ACM sigmod record 29(2), 1-12. ACM.
Islam, S., & Mannering, F. (2006). Driver aging and its effect on male and female single-vehicle accident injuries: some additional evidence. Journal of safety Research, 37(3), 267-276.
Jones, B., Janssen, L., & Mannering, F. (1991) Analysis of the Frequency and Duration of Freeway Accidents in Seattle. Accident Analysis and Prevention 23(4), 239-255
Jones, M. C., & Sheather, S. J. (1991). Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives. Statistics & Probability Letters, 11(6), 511-514.
Joshua, S. C., & Garber, N. J. (1990). Estimating truck accident rate and involvements using linear and Poisson regres-sion models. Transportation planning and Technology, 15(1), 41-58.
Karlaftis M, Tarko A (1998) Heterogeneity considerations in accident modeling. Accident Analysis Preview, 30, 425–433
Kashani, A. T., & Mohaymany, A. S. (2011). Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models. Safety Science, 49(10), 1314-1320.
Kumar, S., & Toshniwal, D. (2015). A data mining framework to analyze road accident data. Journal of Big Data, 2(1), 1-26.
Kumar, S., & Toshniwal, D. (2016). A data mining approach to characterize road accident locations. Journal of Modern Transportation, 24(1), 62-72.
Kumar, S., & Toshniwal, D. (2016). A novel framework to analyze road accident time series data. Journal of Big Data, 3(1), 1-8.
Kumar, S., & Toshniwal, D. (2017). Severity analysis of powered two wheeler traffic accidents in Uttarakhand, India. European Transport Research Review, 9(2), 1-24.
Lee, C., Saccomanno, F., & Hellinga, B. (2002) Analysis of crash precursors on instrumented freeways. Transportation Research Record: Journal of the Transportation Research Board, 1784, 1-8.
Maher, M. J., & Summersgill, I. (1996). A comprehensive methodology for the fitting of predictive accident models. Accident Analysis & Prevention, 28(3), 281-296.
Poch, M., & Mannering, F. (1996). Negative Binomial Analysis of Intersection-Accident Frequencies. Journal of Trans-portation Engineering, 122(2), 105-113.
Prayag, G., Hosany, S., Muskat, B., & Del Chiappa, G. (2017). Understanding the relationships between tourists’ emo-tional experiences, perceived overall image, satisfaction, and intention to recommend. Journal of Travel Research, 56(1), 41-54.
Raftery, A. E. (1986). Choosing models for cross-classifications. American sociological review, 51(1), 145-146.
Sasidharan, R., Mustroph, A., Boonman, A., Akman, M., Ammerlaan, A. M., Breit, T. & van Tienderen, P. H. (2013). Root transcript profiling of two Rorippa species reveals gene clusters associated with extreme submergence toler-ance. Plant physiology, 163(3), 1277-1292.
Savolainen, K., Alenius, H., Norppa, H., Pylkkänen, L., Tuomi, T., & Kasper, G. (2010). Risk assessment of engineered nanomaterials and nanotechnologies—a review. Toxicology, 269(2-3), 92-104.
Tibshirani, R., Walther, G., & Hastie, T. (2001). Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(2), 411-423.
Tiwari, P., Madabhushi, A., & Rosen, M. (2007). A hierarchical unsupervised spectral clustering scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS). In International Conference on Medical Image Computing and Computer-Assisted Intervention, 278-286. Springer, Berlin, Heidelberg.
Ulfarsson, G. F., & Mannering, F. L. (2004). Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents. Accident Analysis & Prevention, 36(2), 135-147.
Akaike, H. (1987). Factor analysis and AIC. In Selected Papers of Hirotugu Akaike. Springer, New York, NY, 371-386.
Barai, S. K. (2003). Data mining applications in transportation engineering. Transport, 18(5), 216-223.
Chang LY, Chen WC (2005) Data mining of tree-based models to analyze freeway accident frequency. Journal of safety research. 36(4), 365-75.
Chaturvedi, A., Green, P. E., & Caroll, J. D. (2001). K-modes clustering. Journal of classification, 18(1), 35-55.
Chen, W. H., & Jovanis, P. P. (2000). Method for identifying factors contributing to driver-injury severity in traffic crashes. Transportation Research Record, 1717(1), 1-9.
Depaire, B., Wets, G., & Vanhoof, K. (2008). Traffic accident segmentation by means of latent class clustering. Acci-dent Analysis & Prevention, 40(4), 1257-1266.
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI mag-azine, 17(3), 1-37.
Fraley, C., & Raftery, A. E. (1998). How many clusters? Which clustering method? Answers via model-based cluster analysis. The computer journal, 41(8), 578-588.
Han, J., Pei, J., & Yin, Y. (2000). Mining frequent patterns without candidate generation. In ACM sigmod record 29(2), 1-12. ACM.
Islam, S., & Mannering, F. (2006). Driver aging and its effect on male and female single-vehicle accident injuries: some additional evidence. Journal of safety Research, 37(3), 267-276.
Jones, B., Janssen, L., & Mannering, F. (1991) Analysis of the Frequency and Duration of Freeway Accidents in Seattle. Accident Analysis and Prevention 23(4), 239-255
Jones, M. C., & Sheather, S. J. (1991). Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives. Statistics & Probability Letters, 11(6), 511-514.
Joshua, S. C., & Garber, N. J. (1990). Estimating truck accident rate and involvements using linear and Poisson regres-sion models. Transportation planning and Technology, 15(1), 41-58.
Karlaftis M, Tarko A (1998) Heterogeneity considerations in accident modeling. Accident Analysis Preview, 30, 425–433
Kashani, A. T., & Mohaymany, A. S. (2011). Analysis of the traffic injury severity on two-lane, two-way rural roads based on classification tree models. Safety Science, 49(10), 1314-1320.
Kumar, S., & Toshniwal, D. (2015). A data mining framework to analyze road accident data. Journal of Big Data, 2(1), 1-26.
Kumar, S., & Toshniwal, D. (2016). A data mining approach to characterize road accident locations. Journal of Modern Transportation, 24(1), 62-72.
Kumar, S., & Toshniwal, D. (2016). A novel framework to analyze road accident time series data. Journal of Big Data, 3(1), 1-8.
Kumar, S., & Toshniwal, D. (2017). Severity analysis of powered two wheeler traffic accidents in Uttarakhand, India. European Transport Research Review, 9(2), 1-24.
Lee, C., Saccomanno, F., & Hellinga, B. (2002) Analysis of crash precursors on instrumented freeways. Transportation Research Record: Journal of the Transportation Research Board, 1784, 1-8.
Maher, M. J., & Summersgill, I. (1996). A comprehensive methodology for the fitting of predictive accident models. Accident Analysis & Prevention, 28(3), 281-296.
Poch, M., & Mannering, F. (1996). Negative Binomial Analysis of Intersection-Accident Frequencies. Journal of Trans-portation Engineering, 122(2), 105-113.
Prayag, G., Hosany, S., Muskat, B., & Del Chiappa, G. (2017). Understanding the relationships between tourists’ emo-tional experiences, perceived overall image, satisfaction, and intention to recommend. Journal of Travel Research, 56(1), 41-54.
Raftery, A. E. (1986). Choosing models for cross-classifications. American sociological review, 51(1), 145-146.
Sasidharan, R., Mustroph, A., Boonman, A., Akman, M., Ammerlaan, A. M., Breit, T. & van Tienderen, P. H. (2013). Root transcript profiling of two Rorippa species reveals gene clusters associated with extreme submergence toler-ance. Plant physiology, 163(3), 1277-1292.
Savolainen, K., Alenius, H., Norppa, H., Pylkkänen, L., Tuomi, T., & Kasper, G. (2010). Risk assessment of engineered nanomaterials and nanotechnologies—a review. Toxicology, 269(2-3), 92-104.
Tibshirani, R., Walther, G., & Hastie, T. (2001). Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(2), 411-423.
Tiwari, P., Madabhushi, A., & Rosen, M. (2007). A hierarchical unsupervised spectral clustering scheme for detection of prostate cancer from magnetic resonance spectroscopy (MRS). In International Conference on Medical Image Computing and Computer-Assisted Intervention, 278-286. Springer, Berlin, Heidelberg.
Ulfarsson, G. F., & Mannering, F. L. (2004). Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents. Accident Analysis & Prevention, 36(2), 135-147.