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Journal articles on the topic 'Variable bit rate traffic'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Cao, Guohong, Wu-chi Feng, and Mukesh Singhal. "Online variable-bit-rate video traffic smoothing." Computer Communications 26, no. 7 (May 2003): 639–51. http://dx.doi.org/10.1016/s0140-3664(02)00197-4.

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2

Khan, Gul Muhammad, Rabia Arshad, Sahibzada Ali Mahmud, and Fahad Ullah. "Intelligent Bandwidth Estimation for Variable Bit Rate Traffic." IEEE Transactions on Evolutionary Computation 19, no. 1 (February 2015): 151–55. http://dx.doi.org/10.1109/tevc.2013.2285122.

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3

Liew, C. H., C. K. Kodikara, and A. M. Kondoz. "MPEG-encoded variable bit-rate video traffic modelling." IEE Proceedings - Communications 152, no. 5 (2005): 749. http://dx.doi.org/10.1049/ip-com:20045014.

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4

Inoue, Masahiro, Masahisa Kawashima, and Hideyoshi Tominaga. "Variable bit-rate video transmission using traffic shaping." Electronics and Communications in Japan (Part I: Communications) 79, no. 12 (1996): 56–64. http://dx.doi.org/10.1002/ecja.4410791206.

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5

Mao, Guoqiang, and Huabing Liu. "Real time variable bit rate video traffic prediction." International Journal of Communication Systems 20, no. 4 (2007): 491–505. http://dx.doi.org/10.1002/dac.838.

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6

Roberts, J. W. "Variable-bit-rate traffic control in B-ISDN." IEEE Communications Magazine 29, no. 9 (September 1991): 50–56. http://dx.doi.org/10.1109/35.90493.

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7

Beran, J., R. Sherman, M. S. Taqqu, and W. Willinger. "Long-range dependence in variable-bit-rate video traffic." IEEE Transactions on Communications 43, no. 2/3/4 (February 1995): 1566–79. http://dx.doi.org/10.1109/26.380206.

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8

Sato, Shohei, and Minoru Akiyama. "Nonblocking atm switching networks for variable bit rate traffic." Electronics and Communications in Japan (Part I: Communications) 76, no. 5 (1993): 12–22. http://dx.doi.org/10.1002/ecja.4410760502.

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9

Xiaodong, Huang, Zhou Yuanhua, and Zhang Rongfu. "Variable bit rate video traffic modeling by multiplicative multifractal model." Journal of Systems Engineering and Electronics 17, no. 1 (March 2006): 75–79. http://dx.doi.org/10.1016/s1004-4132(06)60014-5.

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10

Sungjoo Kang, Seongjin Lee, Youjip Won, and Byeongchan Seong. "On-Line Prediction of Nonstationary Variable-Bit-Rate Video Traffic." IEEE Transactions on Signal Processing 58, no. 3 (March 2010): 1219–37. http://dx.doi.org/10.1109/tsp.2009.2035983.

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11

Krunz, M. "Bandwidth allocation strategies for transporting variable bit rate video traffic." IEEE Communications Magazine 37, no. 1 (1999): 40–46. http://dx.doi.org/10.1109/35.739277.

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12

Van der Auwera, Geert, Prasanth David, and Martin Reisslein. "Traffic characteristics of H.264/AVC variable bit rate video." IEEE Communications Magazine 46, no. 11 (November 2008): 164–74. http://dx.doi.org/10.1109/mcom.2008.4689260.

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13

Rose, O. "Simple and efficient models for variable bit rate MPEG video traffic." Performance Evaluation 30, no. 1-2 (July 1997): 69–85. http://dx.doi.org/10.1016/s0166-5316(96)00054-5.

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14

Chang, Ray-I., Meng-Chang Chen, Jan-Ming Ho, and Ming-Tat Ko. "Online traffic smoothing for delivery of variable bit rate media streams." Circuits, Systems, and Signal Processing 20, no. 3-4 (May 2001): 341–59. http://dx.doi.org/10.1007/bf01201406.

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15

Lee, Kang Yong, Moonseong Kim, Hee-Seon Jang, and Kee-Seong Cho. "Accurate Prediction of Real-Time MPEG-4 Variable Bit Rate Video Traffic." ETRI Journal 29, no. 6 (December 2007): 823–25. http://dx.doi.org/10.4218/etrij.07.0207.0141.

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16

Coelho, Rosângela, and Samir Tohmé. "A generic smoothing algorithm for real-time variable bit rate video traffic." Computer Networks and ISDN Systems 29, no. 17-18 (February 1998): 2053–66. http://dx.doi.org/10.1016/s0169-7552(97)00123-2.

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17

Kalbkhani, Hashem, Mahrokh G. Shayesteh, and Nasser Haghighat. "Adaptive LSTAR Model for Long-Range Variable Bit Rate Video Traffic Prediction." IEEE Transactions on Multimedia 19, no. 5 (May 2017): 999–1014. http://dx.doi.org/10.1109/tmm.2016.2639379.

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18

Lian, Zuo Zheng, Hai Zhen Wang, and Da Hui Li. "Design of a Novel Variable Bit Rate Video Traffic Prediction Model Based on Neural Networks." Advanced Materials Research 989-994 (July 2014): 4143–46. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4143.

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The video business has gradually become the main business of the network traffic, video traffic is Variable Bit Rate (VBR), which has nonlinear and sudden features, a single prediction model is not fit for describing those features, and prediction accuracy is not high. Because of wavelet analysis has advantages of multi-resolution and dealing with unexpectedness, and the neural network has better nonlinear fitting characteristics, in order to improve the prediction performance, the paper researched on the problem of VBR video traffic prediction based on neural networks, a novel prediction model AMWM is proposed, the model firstly introducing BP neural network to multi-fractal wavelet model, and designing prediction method, which introduced multi-fractal wavelet model to model VBR video traffic, and then applying BP neural network to forecast scale coefficient decomposed, and forecast multiplier using AR model, and predict traffic generated by wavelet reconstruction. Finally, the model is built and simulated. The experimental result shows that prediction performance based AMWM is better compared with multi-fractal wavelet model.

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19

Xiong Tao, Chang Sheng-Jiang, Shen Jin-Yuan, and Zhang Yan-Xin. "Adaptive training and pruning algorithm for variable bit rate video traffic pre diction." Acta Physica Sinica 54, no. 4 (2005): 1931. http://dx.doi.org/10.7498/aps.54.1931.

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20

Dalgic, I., and F. A. Tobagi. "Performance evaluation of ATM networks carrying constant and variable bit-rate video traffic." IEEE Journal on Selected Areas in Communications 15, no. 6 (1997): 1115–31. http://dx.doi.org/10.1109/49.611163.

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21

Haghighat, Nasser, Mehdi Nouri, Mahrokh G. Shayesteh, and Hashem Kalbkhani. "Variable bit rate video traffic prediction based on kernel least mean square method." IET Image Processing 9, no. 9 (September 1, 2015): 777–94. http://dx.doi.org/10.1049/iet-ipr.2014.1035.

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22

Veirø, Biørn. "Traffic measurement on variable bit rate (VBR) sources with application to charging principles." Computer Networks and ISDN Systems 20, no. 1-5 (December 1990): 435–45. http://dx.doi.org/10.1016/0169-7552(90)90054-v.

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23

Frater, M. R., and O. Rose. "Cell loss analysis of broadband switching systems carrying variable bit rate video traffic." Telecommunication Systems 4, no. 1 (December 1995): 319–38. http://dx.doi.org/10.1007/bf02110092.

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24

Ruscelli, Anna Lina, and Gabriele Cecchetti. "A IEEE 802.11e HCCA Scheduler with a Reclaiming Mechanism for Multimedia Applications." Advances in Multimedia 2014 (2014): 1–22. http://dx.doi.org/10.1155/2014/372693.

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The QoS offered by the IEEE 802.11e reference scheduler is satisfactory in the case of Constant Bit Rate traffic streams, but not yet in the case of Variable Bit Rate traffic streams, whose variations stress its scheduling behavior. Despite the numerous proposed alternative schedulers with QoS, multimedia applications are looking for refined methods suitable to ensure service differentiation and dynamic update of protocol parameters. In this paper a scheduling algorithm,Unused Time Shifting Scheduler(UTSS), is deeply analyzed. It is designed to cooperate with a HCCA centralized real-time scheduler through the integration of a bandwidth reclaiming scheme, suitable to recover nonexhausted transmission time and assign that to the next polled stations. UTSS dynamically computes with anO(1)complexity transmission time providing an instantaneous resource overprovisioning. The theoretical analysis and the simulation results highlight that this injection of resources does not affect the admission control nor the centralized scheduler but is suitable to improve the performance of the centralized scheduler in terms of mean access delay, transmission queues length, bursts of traffic management, and packets drop rate. These positive effects are more relevant for highly variable bit rate traffic.

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25

Shriramoju, Suman Kumar, and Dr N. Satyanarayana. "Survey of Routing Protocols under Realistic Mobility and Traffic." International Journal Of Engineering And Computer Science 7, no. 03 (March 16, 2018): 23737–41. http://dx.doi.org/10.18535/ijecs/v7i3.14.

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Mobile ad hoc networks are a dynamic and unpredictable community topology. There are numerous routing protocols that have been proposed for MANETs. Maximum pervious research centered on improving the present routing protocols or designing new routing algorithms. In our work, we investigated and compared the effect of mobility models on routing protocols for various site visitors instructions in MANETs. There have been many factors that affected the overall performance of routing protocols which include mobility and visitors styles. We designed several simulation models that added these factors together and measured the software performance in terms of end -to-end throughput (bit rate), latency, and jitter. three instructions of MANET routing algorithms (Proactive, Reactive, and Hybrid), mobility models (Random Waypoint and group), and three instructions of visitors styles (constant bit rate, variable bit rate, and random) have been used.

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26

Shih-Chia Huang and Bo-Hao Chen. "Highly Accurate Moving Object Detection in Variable Bit Rate Video-Based Traffic Monitoring Systems." IEEE Transactions on Neural Networks and Learning Systems 24, no. 12 (December 2013): 1920–31. http://dx.doi.org/10.1109/tnnls.2013.2270314.

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27

Rege, Kiran M. "An algorithm for sizing trunks carrying mixtures of constant and variable bit rate traffic." International Journal of Communication Systems 8, no. 5 (September 1995): 313–23. http://dx.doi.org/10.1002/dac.4500080504.

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28

Chen, Yeong-Sheng, Der-Jiunn Deng, Yu-Ming Hsu, and Sheng-De Wang. "Efficient uplink scheduling policy for variable bit rate traffic in IEEE 802.16 BWA systems." International Journal of Communication Systems 25, no. 6 (January 13, 2011): 734–48. http://dx.doi.org/10.1002/dac.1206.

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29

Sahu, Sambit, Victor Firoiu, Don Towsley, and Jim Kurose. "Traffic models and admission control for variable bit rate continuous media transmission with deterministic service." Performance Evaluation 40, no. 1-3 (March 2000): 115–33. http://dx.doi.org/10.1016/s0166-5316(99)00072-3.

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30

Weilian Su and I. F. Akyildiz. "The jitter time-stamp approach for clock recovery of real-time variable bit-rate traffic." IEEE/ACM Transactions on Networking 9, no. 6 (2001): 746–54. http://dx.doi.org/10.1109/90.974528.

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31

Tu, Yung-Cheng, Meng Chang Chen, and Yeali S. Sun. "A Two-Stage Link Scheduling Scheme for Variable-Bit-Rate Traffic Flows in Wireless Mesh Networks." IEEE Transactions on Wireless Communications 13, no. 11 (November 2014): 6232–44. http://dx.doi.org/10.1109/twc.2014.2358591.

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32

Ahmadpour, Sima, Zohreh Toghrayee, and Tat-Chee Wan. "An extended discrete autoregressive model for variable bit rate video traffic encoded by scalable video codec." International Journal of Communication Systems 28, no. 18 (July 15, 2015): 2239–54. http://dx.doi.org/10.1002/dac.3011.

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33

Jin, Meihua, Ji-Young Jung, and Jung-Ryun Lee. "Dynamic Power-Saving Method for Wi-Fi Direct Based IoT Networks Considering Variable-Bit-Rate Video Traffic." Sensors 16, no. 10 (October 12, 2016): 1680. http://dx.doi.org/10.3390/s16101680.

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34

Fei Yu, V. Krishnamurthy, and V. C. M. Leung. "Cross-Layer optimal connection admission control for variable bit rate multimedia traffic in packet wireless CDMA networks." IEEE Transactions on Signal Processing 54, no. 2 (February 2006): 542–55. http://dx.doi.org/10.1109/tsp.2005.861785.

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35

Lee, T. H., and Y. W. Huang. "Effective transmission opportunity allocation scheme for real-time variable bit rate traffic flows with different delay bounds." IET Communications 2, no. 4 (2008): 598. http://dx.doi.org/10.1049/iet-com:20070488.

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36

Zhang, S., J. Chen, L. H. She, and X. R. Bao. "Use of optimal wavelet packet decomposition for the long-term prediction of variable-bit-rate video traffic." IET Communications 4, no. 11 (2010): 1277. http://dx.doi.org/10.1049/iet-com.2009.0405.

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37

Fantacci, R., and S. Nannicini. "Multiple access protocol for integration of variable bit rate multimedia traffic in UMTS/IMT-2000 based on wideband CDMA." IEEE Journal on Selected Areas in Communications 18, no. 8 (August 2000): 1441–54. http://dx.doi.org/10.1109/49.864009.

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38

Chan, H. C. B., and V. C. M. Leung. "Evaluation of reservation-arbitrated access schemes for statistical multiplexing of variable-bit-rate video traffic over dual-bus metropolitan area networks." IEE Proceedings - Communications 145, no. 3 (1998): 159. http://dx.doi.org/10.1049/ip-com:19981960.

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39

Chan, Henry C. B., and Victor C. M. Leung. "Reservation arbitrated access — a bandwidth on demand protocol for multiplexing variable bit rate isochronous traffic over dual bus metropolitan area networks." Computer Networks and ISDN Systems 29, no. 16 (December 1997): 1969–90. http://dx.doi.org/10.1016/s0169-7552(97)00104-9.

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40

Koumaras, Harilaos, Charalampos Skianis, and Anastasios Kourtis. "Analysis and Modeling of H.264 Unconstrained VBR Video Traffic." International Journal of Mobile Computing and Multimedia Communications 1, no. 4 (October 2009): 14–31. http://dx.doi.org/10.4018/jmcmc.2009072802.

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In future communication networks, video is expected to represent a large portion of the total traffic, given thatespecially variable bit rate (VBR) coded video streams, are becoming increasingly popular. Consequently, traffic modeling and characterization of such video services is essential for the efficient traffic control and resource management. Besides, providing an insight of video coding mechanisms, traffic models can be used as a tool for the allocation of network resources, the design of efficient networks for streaming services and the reassurance of specific QoS characteristics to the end users. The new H.264/AVC standard, proposed by the ITU-T Video Coding Expert Group (VCEG) and ISO/IEC Moving Pictures Expert Group (MPEG), is expected to dominate in upcoming multimedia services, due to the fact that it outperforms in many fields the previous encoded standards. This article presents both a frame and a layer (i.e. I, P and B frames) level analysis of H.264 encoded sources. Analysis of the data suggests that the video traffic can be considered as a stationary stochastic process with an autocorrelation function of exponentially fast decay and a marginal frame size distribution of approximately Gamma form. Finally, based on the statistical analysis, an efficient model of H.264 video traffic is proposed.

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41

Ruscelli, Anna Lina, Gabriele Cecchetti, and Piero Castoldi. "Elastic QoS Scheduling with Step-by-Step Propagation in IEEE 802.11e Networks with Multimedia Traffic." Wireless Communications and Mobile Computing 2019 (April 18, 2019): 1–23. http://dx.doi.org/10.1155/2019/2925891.

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The spreading diffusion of wireless devices and the crowded coexistence of multimedia applications greedy of bandwidth and with strict requirements stress the service provisioning offered by wireless technologies. WiFi is a reference for wireless connectivity and it requires a continuous evolution of its mechanism in order to follow increasingly demanding service needs. In particular, despite the evolution of physical layer, some critical contexts, such as industrial networks, telemedicine, telerehabilitation, and virtual training, require further refined improvements in order to ensure the respect of strict real-time service requirements. In this paper an in-depth analysis of Dynamic TXOP HCCA (DTH) MAC enhanced centralized scheduler is illustrated and it is further refined introducing a new improvement, DTH with threshold. DTH and DTH with threshold can be integrated with preexisting centralized schedulers in order to improve their performances, without any overprovisioning that can negatively impact on the admission control feasibility test. Indeed, without modifying the centralized scheduler policy, they combine together the concepts of reclaiming transmission time and statistical estimation of the traffic profile in order to provide, at each polling, an instantaneous transmission time tailored to the variable traffic requirements, increasing, when necessary, the service data rate. These mechanisms can coexist with advanced physical layer-based solutions, providing the required service differentiation. Experimental results and theoretical analysis, based on elastic scheduler theory, show that they are effective especially in the case of Variable Bit Rate traffic streams in terms of transmission queues length, packets loss, delay, and throughput.

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42

Shu'aibu, D. S., S. K. Syed Yusof, N. Fisal, S. H. S. Ariffin, R. A. Rashid, N. M. Abdul Latiff, and Y. S. Baguda. "Fuzzy Logic Partition-Based Call Admission Control for Mobile WiMAX." ISRN Communications and Networking 2011 (June 1, 2011): 1–9. http://dx.doi.org/10.5402/2011/171760.

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The unpredictable nature of the wireless network and exponential growth in traffics with different quality of service requirements has led hardware complexity to escalate. In order to effectively control and manage the network traffics, there is a need for intelligent call admission control (CAC) in admitting traffics into the wireless network that provides necessary quality of service. In this paper, we propose a fuzzy logic partition-based call admission control (FZ CAC). The scheme primarily partitions the total link bandwidth into three which corresponds to constant bit rate (CBR), variable bit rate (VBR) and handover (HO) services. The fuzzy logic admission control scheme was implemented in the HO portion to intelligently keep dropping probability as low as possible based on the available bandwidth. Simulation results showed that the proposed approach outperformed both partition-based CAC (PB CAC) and conventional bandwidth allocation CAC (CB CAC).

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43

Shijer, Sameera Sadey, and Ahmad H. Sabry. "Analysis of performance parameters for wireless network using switching multiple access control method." Eastern-European Journal of Enterprise Technologies 4, no. 9(112) (August 31, 2021): 6–14. http://dx.doi.org/10.15587/1729-4061.2021.238457.

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The developments of wireless networks have directed to search for opportunities of a broad diversity of improved and new networking contributions. Wireless Asynchronous Transfer Mode (ATM) is a non-synchronous or random mode of transferring information. The advantages of circuit switching include dedicated connections and guaranteed traffic parameters and the benefits of packet switching are the efficiency at the physical layer and a more cost-effective design. ATM is the only protocol that offers the best of both communication methods. Although the Variable Bit-Rate (VBR) transmission presents a promising prospective of stable data quality, it is usually accompanied by network traffic overload and cell packet loss, which extensively weakens that potential. This work overcomes these concerns by developing a switching-based multiple access control model to improve the data transmission performance of wireless ATM. Therefore, this work discusses the effectiveness of the developed approach to minimize the cell packet losses and network traffic overload in wireless ATM. Three control access is processed; polling, token passing, and reservation algorithms for collision avoidance. The reservation stage reserves the data before sending, which includes two timeline intervals; a fixed-time reservation period, and variable data transmission interval. Using OPNET 10.5, the results show that the presented switching-based multiple access control model can achieve a throughput value of 98.3 %, data transmission delay of about 40.2 ms, and 0.024 % of packet losses during data transmission between the source and destination. It is demonstrated that the introduced method effectively transmits information without creating any network complexity and delay

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44

Mandjes, Michel, and Jeong-Han Kim. "Analysis of a phase transition phenomenon in packet networks." Advances in Applied Probability 33, no. 1 (March 2001): 260–80. http://dx.doi.org/10.1017/s0001867800010739.

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The multiplexing of variable bit rate traffic streams in a packet network gives rise to two types of queueing. On a small time-scale, the rates at which the sources send is more or less constant, but there is queueing due to simultaneous packet arrivals (packet-level effect). On a somewhat larger time-scale, queueing is the result of a relatively high number of sources sending at a rate that is higher than their average rate (burst-level effect). This paper explores these effects. In particular, we give asymptotics of the overflow probability in the combined packet/burst scale model. It is shown that there is a specific size of the buffer (i.e. the ‘critical buffer size’) below which packet-scale effects are dominant, and above which burst-scale effects essentially determine the performance—strikingly, there is a sharp demarcation: theso-called ‘phase transition’. The results are asymptotic in the number of sources n. We scale buffer space B and link rate C by n, to nb and nc, respectively; then we let n grow large. Applying large deviations theory we show that in this regime the overflow probability decays exponentially in the number of sources n. For small buffers the corresponding decay rate can be calculated explicitly, for large buffers we derive an asymptote (linear in b). The results for small and large buffers give rise to an approximation for the decay rate (with general b), as well as for the critical buffer size. A numerical example (multiplexing of voice streams) confirms the accuracy of these approximations.

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45

Alabady, Salah Abdulghani, and Mohd Fadzli Mohd Salleh. "Binary Joint Network-Channel Coding for Reliable Multi-Hop Wireless Networks." ECTI Transactions on Electrical Engineering, Electronics, and Communications 19, no. 1 (February 28, 2021): 23–33. http://dx.doi.org/10.37936/ecti-eec.2021191.222590.

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The high and variable packet loss in wireless networks due to the unreliable nature of wireless channels, interference, link or router failure, fading, and shadowing wireless link are the main problems and challenges in implementing a reliable wireless network. Packet loss probability is the most important performance measure for real-time applications. Packet loss is due to errors, congestion in the queue because of high traffic, collision, hidden nodes, and link failures. In this paper, we focus on the links failure problem. To address this problem, improve the performance of wireless networks, and enhance and make the network survivability and availability more reliable, a new efficient binary joint network and channel coding (B-JNCC) technique is proposed. B-JNCC combines low-complexity parity-check (LCPC) channel coding and the wireless network erasure correcting with router code to detect lost packets to reduce the bit error rate and increase the packet delivery ratio over a wireless multi-access channel. B-JNCC is applied at the receiver node. Simulation results show that the proposed B-JNCC outperforms the binary symbol-wise JNCC, non-binary JNCC (NB-JNCC), and NB separate network-channel coding.

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46

Darwesh, Laialy, and Natan Kopeika. "Improved Performance in the Detection of ACO-OFDM Modulated Signals Using Deep Learning Modules." Applied Sciences 10, no. 23 (November 25, 2020): 8380. http://dx.doi.org/10.3390/app10238380.

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Free space optical communication (FSO) is widely deployed to transmit high data rates for rapid communication traffic increase. Asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) modulation is a very efficient FSO communication technique in terms of transmitted optical power. However, its performance is limited by atmospheric turbulence. When the channel includes strong turbulence or is non-deterministic, the bit error rate (BER) increases. To reach optimal performance, the ACO-OFDM decoder needs to know accurate channel state information (CSI). We propose novel detection using different deep learning (DL) algorithms. Our DL models are compared with minimum mean square error (MMSE) detection methods in different turbulent channels and improve performance especially for non-stationary and non-deterministic channels. Our models yield performance very close to that of the MMSE estimator when the channel is characterized by weak or strong turbulence and is stationary. However, when the channel is non-stationary and variable, our DL model succeeds in improving the performance of the system and decreasing the signal to noise ratio (SNR) by more than 8 dB compared to that of the MMSE estimator, and it succeeds in recovering the received data without needing to know accurate CSI. Our DL decoders also show notable speed and energy efficiency improvement.

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47

Wang, Xiaofei, HuaQiao Pu, Xinwei Li, Ying Yan, and Jiangbei Yao. "A New GNB Model of Crash Frequency for Freeway Sharp Horizontal Curve Based on Interactive Influence of Explanatory Variables." Journal of Advanced Transportation 2018 (November 14, 2018): 1–9. http://dx.doi.org/10.1155/2018/8973581.

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Crash prediction of the sharp horizontal curve segment of freeway is a key method in analyzing safety situation of freeway horizontal alignment. The target of this paper is to improve predicting accuracy after considering the elastic influence of explanatory variables and interaction of explanatory variables on crash rate prediction. In the paper, flexibility and elasticity are defined to express the elastic influence of explanatory variables and interaction of explanatory variables on crash rate prediction. Thus, we proposed 6 types of models to predict crash frequency. These 6 types of models include 2 NB models (models 1 and 2), 2 GNB models (models 3 and 4), one NB model (model 5), and one GNB model (model 6) with flexibility and variable elasticity considered. The alignment and crash report data of 88 sharp horizontal curve segments from different institutions were surveyed to build the crash models. Traffic volume, highway horizontal radius, and curve length have been assigned as explanatory variables. Subsequently, statistical analysis is performed to determine the model parameters and conducted sensitivity analysis by AIC, BIC, and Pseudo R2. The results demonstrated the effective use of flexibility and elasticity in analyzing explanatory variables and in predicting freeway sharp horizontal curve segments. In six models, the result of model 6 is much better than those of the other models by fitting rules. We also compared the actual results from crashes of 88 sharp horizontal curve segments with those predicted by models 1, 3, and 6. Results demonstrate that model 6 is much more reasonable than the others.

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48

Beshai, M. E., L. A. Garrett, and I. R. Stewart. "Transposed switching of multi-bit-rate traffic." Computer Networks and ISDN Systems 20, no. 1-5 (December 1990): 333–41. http://dx.doi.org/10.1016/0169-7552(90)90042-q.

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49

Olano, M., D. Baker, W. Griffin, and J. Barczak. "Variable Bit Rate GPU Texture Decompression." Computer Graphics Forum 30, no. 4 (June 2011): 1299–308. http://dx.doi.org/10.1111/j.1467-8659.2011.01989.x.

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50

Dedes, I. S., D. R. Vaman, and C. V. Chakravarthy. "Variable bit rate adaptive predictive coder." IEEE Transactions on Signal Processing 40, no. 3 (March 1992): 511–17. http://dx.doi.org/10.1109/78.120794.

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