Ahmed Alostaz and Basil Hamed
 H.M. Deeand S.A. Velastin, How close are we to solving theproblem of automated visual surveillance? Machine Visionand Applications, 19, 2008, 329–343.
 J. Klein, C. Lecomte, and P. Miche, Preceding car tracking usingbelief functions and a particle ﬁlter 2008 19th InternationalConf. on Pattern Recognition (2008 ICPR), IEEE, Tampa,FL, 2008, 1–4.
 L. Mejias, P. Campoy, S. Saripalli, and G. Sukhatme, A visualservoing approach for tracking features in urban areas usingan autonomous helicopter, Proc. of 2006 IEEE InternationalConf. on Robotics and Automation (2006 ICRA), Orlando,FL, 2503–2508.
 L. Mihaylova, P. Brasnett, N. Canagarajah, and D. Bull, Objecttracking by particle ﬁltering techniques in video sequences,Advances and challenges in multisensor data and information,(IOS Press Ebooks, 2007), 260–268.
 Z. Hao, X. Zhang, H. Li, and J. Li, Video object tracking basedon swarm optimized particle ﬁlter, 2010 2nd InternationalConf. on Industrial Mechatronics and Automation (ICIMA2010), IEEE, Chengdu, China, 2010, 702–706.
 Z. Xiaowei, L. Hong, and S. Xiaohong, Object tracking with anevolutionary particle ﬁlter based on self-adaptive multi-featuresfusion, International Journal of Advanced Robotic Systems,10, 2013.
 Z. Hao, X. Zhang, P. Yu, and H. Li, Video object tracingbased on particle ﬁlter with ant colony optimization, 2ndInternational Conf. on Advanced Computer Control (ICACC2010), IEEE, Shenyang, China, 2010, 232–236.
 M. Alhanjouri and A. Al-Ostaz, BFO vs. BSO for video objecttracking using particle ﬁlter (PF), Journal of Emerging Trendsin Computing and Information Sciences, 4, 2013, 8.
 M. El-Bardini, E. Elsheikh, and M. Fkirin, Real time objecttracking using image based visual servo technique, Interna-tional Journal of Computer Science & Emerging Technologies2, 2011, 6.
 A. Qadir, W. Semke, and J. Neubert, Vision based neuro-fuzzy controller for a two axes gimbal system with small UAV,Journal of Intelligent & Robotic Systems, 74(3), 2013, 1–19.
 H. Zhongliang and W. Xingsong, Position control of servopress system based on fuzzy PID, 2012 24th Chinese Controland Decision Conf. (CCDC), IEEE, Taiyuan, China, 2012,4068–4073.
 Z. Chen, Bayesian ﬁltering: From Kalman ﬁlters to particleﬁlters, and beyond, Statistics 182 2003, 1–69.
 J.V. Candy, Bayesian signal processing: Classical, modernand particle ﬁltering methods (United Kingdom: John Wiley& Sons, 2011).
 Z. Al-Hamouz, S.F. Faisal, and S. Al-Sharif, Application ofparticle swarm optimization algorithm for optimal reactivepower planning, (201) Control and Intelligent Systems, 2007.
 M.T. Das and L.C. D¨ulger, Control of a scara robot: PSO-PIDapproach, (201) Control and Intelligent Systems, 2010.
 J. Kennedy and R. Eberhart, Particle swarm optimization,Proc. of IEEE International Conf. on Neural Networks, Perth,Australia, 1995, 1942–1948.
 S.S. Rao and S. Rao, Engineering optimization: theory andpractice (United Kingdom: John Wiley & Sons, 2009).
 A. Alostaz and M. Alhanjouri, A new adaptive BFO basedON PSO for learning neural network. i-manager ’s Journal ofComputer Science, 1, 2013, 8.
 K.M. Passino, Biomimicry for optimization, control, and au-tomation (United Kingdom: Springer; 2005).
 K.-Y. Liu, S.-Q. Li, L. Tang, L. Wang, and W. Liu, Fast facetracking using parallel particle ﬁlter algorithm, 2009 IEEEInternational Conf. on Multimedia and Expo (2009 ICME),IEEE, New York, NY, 2009, 1302–1305.
 R. Chen, Z. Zhang, H. Lu, H. Cui, and Y. Yan, Particle-ﬁlter-based object tracking with color and texture information fusion,Sixth International Symp. on Multispectral Image Processingand Pattern Recognition, International Society for Optics andPhotonics, Yichang, China, 2009, 74952F-74952F-74958.
 J. Ma, C. Han, and Y. Chen, Eﬃcient visual tracking usingparticle ﬁlter, 2007 10th International Conf. on InformationFusion, IEEE, Quebec, Canada, 2007, 1–6.
 T.R. Rangaswamy, J. Shanmugam, and K.P. Mohammed,Adaptive fuzzy tuned PID controller for combustion of utilityboiler, (201) Control and Intelligent Systems, 2005.
 Z.-L. Huo and X.-S. Wang, Position control of servo presssystem based on Fuzzy-PID, Forging & Stamping Technology,5, 2011, 026.