References
[1]. Abdelaziz, A. Y., Elkhattam, W., Ezzat, M., & Sobhy, M. A.
(2016, December). Fault section estimation in power
systems Based on improved honey-bee mating
optimization. In Power Systems Conference (MEPCON),
2016 Eighteenth International Middle East (pp. 246-252).
IEEE.
[2]. Apostolopoulos, C. A. & Korres, G. N. (2010). A novel
algorithm for locating faults on transposed/untransposed
transmission lines without utilizing line parameters. IEEE Transactions on Power Delivery, 25(4), 2328-2338.
[3]. Ayyagari, S. B. (2011). Artificial neural network based
fault location for transmission lines (Master's Theses,
University of Kentucky).
[4]. Babu, M. S. P. & Rao, N. T. (2010). Implementation of
Artificial Bee Colony (ABC) algorithm on garlic expert
advisory system. Int. J. Comput. Sci. Res., 1(1), 69-74.
[5]. Baykasoglu, A, Özbakir, L., & Tapkan, P. (2004). Artificial
Bee Colony Algorithm and Its Application to Generalized
Assignment Problem. Computer and Information Science,
5, 113-144.
[6]. Bedi, M. K. & Singh, S. (2013). Comparative study of two
natural phenomena based optimization techniques.
International Journal of Scientific & Engineering Research,
4(3), 1-4.
[7]. Bianchi, L., Gambardella, L. M., & Dorigo, M. (2002,
September). An ant colony optimization approach to the
probabilistic traveling salesman problem. In PPSN (pp. 883-
892).
[8]. Bilchev, G. & Parmee, I. C. (1995, April). The ant colony
metaphor for searching continuous design spaces. In AISB
Workshop on Evolutionary Computing (pp. 25-39). Springer,
Berlin, Heidelberg.
[9]. Blesa, M. & Blum, C. (2004, March). Ant colony
optimization for the maximum edge-disjoint paths
problem. In Evo Workshops (pp. 160-169).
[10]. Blum, C. & Dorigo, M. (2005). Search bias in ant
colony optimization: On the role of competition-balanced systems. IEEE Transactions on Evolutionary Computation,
9(2), 159-174.
[11]. Blum, C. (2005). Ant colony optimization: Introduction
and recent trends. Physics of Life Reviews, 2(4), 353-373.
[12]. Blum, C. (2005). Beam-ACO-Hybridizing ant colony
optimization with beam search: An application to open
shop scheduling. Computers & Operations Research,
32(6), 1565-1591.
[13]. Blum, C. & Blesa, M. J. (2005, June). Combining Ant
Colony Optimization with Dynamic Programming for
Solving the k-Cardinality Tree Problem. In IWANN (pp. 25-
33).
[14]. Blum, C. & Dorigo, M. (2004). The hyper-cube
framework for ant colony optimization. IEEE Transactions on
Systems, Man, and Cybernetics, Part B (Cybernetics), 34(2),
1161-1172.
[15]. Bouthiba, T. (2004). Fault location in EHV transmission
lines using artificial neural networks. International Journal of
Applied Mathematics and Computer Science, 14(1), 69-
78.
[16]. Chanda, D., Kishore, N. K., & Sinha, A. K. (2004).
Identification and classification of faults on transmission
lines using wavelet multiresolution analysis. Electric Power
Components and Systems, 32(4), 391-405.
[17]. Chen, W. H., Liu, C. W., & Tsai, M. S. (2001). Fast fault
section estimation in distribution substations using matrixbased
cause-effect networks. IEEE Transactions on Power
Delivery, 16(4), 522-527.
[18]. Chen, W. H., Tsai, S. H., & Lin, H. I. (2011). Fault section
estimation for power networks using logic cause-effect
models. IEEE Transactions on Power Delivery, 26(2), 963-
971.
[19]. Chin, H. C. (2003). Fault section diagnosis of power
system using fuzzy logic. IEEE Transactions on Power
Systems, 18(1), 245-250.
[20]. Chong, C. S., Low, M. Y. H., Sivakumar, A. I., & Gay, K. L.
(2006, December). A bee colony optimization algorithm to
job shop scheduling. In Simulation Conference, 2006.
WSC'06. Proceedings of the Winter (pp. 1954-1961). IEEE.
[21]. Cochocki, A. & Unbehauen, R. (1993). Neural
Networks for Optimization and Signal Processing. John
[22 ]. Corry, P. & Kozan, E. (2004). Ant colony optimisation for
machine layout problems. Computational Optimization
and Applications, 28(3), 287-310.
[23]. Coury, D. V., Oleskovicz, M., & Aggarwal, R. K. (2002).
An ANN routine for fault detection, classification, and
location in transmission lines. Electric Power Components
and Systems, 30(11), 1137-1149.
[24]. Dalstein, T. & Kulicke, B. (1995). Neural network
approach to fault classification for high speed protective
relaying. IEEE Transactions on Power Delivery, 10(2), 1002-
1011.
[25]. Das, B. & Das, D. (2014). Dynamic performances of
split-shaft microturbine generator (MTG) system in standalone
mode and when connected to a rural distribution
network. Distributed Generation and Alternative Energy
Journal, 29(4), 25-48.
[26]. Davis, W. P. (2013). Analysis of faults in overhead
transmission lines (Master's Thesis, California State
University).
[27]. Davoudi, M., Sadeh, J., & Kamyab, E. (2015).
Parameter-free fault location for transmission lines based
on optimisation. IET Generation, Transmission & Distribution,
9(11), 1061-1068.
[28]. de Oliveira, I. M. S., Schirru, R., & de Medeiros, J. A. C.
C. (2009). On the performance of an Artificial Bee Colony
optimization algorithm applied to the accident diagnosis in
a PWR nuclear power plant. In 2009 International Nuclear
Atlantic Conference (INAC 2009).
[29]. Dorigo, M. & Blum, C. (2005). Ant colony optimization
theory: A survey. Theoretical Computer Science, 344(2-3),
243-278.
[30]. Dorigo, M. & Stützle, T. (2003). The Ant Colony
Optimization Metaheuristic: Algorithms, Applications, and
Advances. In: Glover F., Kochenberger G.A. (eds)
Handbook of Metaheuristics. International Series in
Operations Research & Management Science (Vol 57, pp.
251-286). Springer, Boston, MA.
[31]. Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant
system: optimization by a colony of cooperating agents.
IEEE Transactions on Systems, Man, and Cybernetics, Part (Cybernetics), 26(1), 29-41.
[32]. Elkalashy, N. I., Kawady, T. A., Khater, W. M., & Taalab,
A. M. I. (2016). Unsynchronized fault-location technique for
double-circuit transmission systems independent of line
parameters. IEEE Transactions on Power Delivery, 31(4),
1591-1600.
[33]. Elmubark, O. A. E. A. E. (2011). Fault Detection,
Classification and Location in Power Transmission Line
System using Artificial Neural Networks (Doctoral
Dissertation, Sudan University of Science and Technology).
[34]. Fausett, L. & Fausett, L. (1994). Fundamentals of
Neural Networks: Architectures, Algorithms, and
Applications (No. 006.3). Prentice-Hall,.
[35]. Fidanova, S. & Durchova, M. (2005, June). Ant
algorithm for grid scheduling problem. In International
Conference on Large-Scale Scientific Computing (pp.
405-412). Springer, Berlin, Heidelberg.
[36]. Gale, P. F., Crossley, P. A., Bingyin, X., Ge, Y., Cory, B. J.,
& Barker, J. R. G. (1993). Fault location based on travelling
waves. In Proc. Fifth International Conference on
Developments in Power System Protection (pp. 54-59).
[37]. Gurney, K. (1997). An Introduction to Neural Networks.
CRC Press.
[38]. Hagan, M. T., Demuth, H. B., & Beale, M. H. (1996).
Neural Network Design. Boston Massachusetts PWS, 2, 734.
[39]. Haykin, S. (1994). Neural Networks. A Comprehensive
Foundation. Macmillan Collage Publishing Company, Inc.,
New York.
[40]. Karaboga, D. & Akay, B. (2009, March). Artificial Bee
Colony (ABC), harmony search and bees algorithms on
numerical optimization. In Innovative Production Machines
and Systems Virtual Conference.
[41]. Kaur, A., & Goyal, S. (2011). A bee colony optimization
algorithm for fault coverage based regression test suite
prioritization. International Journal of Advanced Science
and Technology, 29, 17-30.
[42]. Kaur, A., & Goyal, S. (2011). A survey on the
applications of bee colony optimization techniques.
International Journal on Computer Science and
Engineering, 3(8), 3037-3046.
[43]. Kennedy, J. & Eberhart, R. C. (1995). Particle swarm
optimization. In Proceedings of the IEEE International Joint
Conference on Neural Networks, (Vol. 4, pp. 1942-1948).
[44]. Kezunovic, M. (1997). A survey of neural net
applications to protective relaying and fault analysis.
Engineering Intelligent Systems for Electrical Engineering
and Communications, 5, 185-192.
[45]. Koley, E., Jain, A., Thoke, A. S., Jain, A., & Ghosh, S.
(2011, September). Detection and classification of faults
on six phase transmission line using ANN. In Computer and
n d Communication Technology (ICCCT), 2011 2
International Conference on (pp. 100-103). IEEE.
[46]. Kuok, K. K., Harun, S., & Shamsuddin, S. M. (2010).
Particle swarm optimization feed forward neural network for
hourly rainfall-runoff modeling in Bedup Basin, Malaysia.
International Journal of Civil & Environmental Engineering,
9(10), 9-18.
[47]. Lee, C. Y., Shen, Y. X., Cheng, J. C., Li, Y. Y., & Chang,
C. W. (2009). Neural networks and particle swarm
optimization based MPPT for small wind power generator.
World Academy of Science, Engineering and Technology,
60(2009), 17-23.
[48]. Lewis, L. J. (1951). Traveling wave relations applicable
to power-system fault locators. Transactions of the
American Institute of Electrical Engineers, 70(2), 1671-
1680.
[49]. Lopes, F. V., Silva, K. M., Costa, F. B., Neves, W. L. A., &
Fernandes, D. (2015). Real-time traveling-wave-based
fault location using two-terminal unsynchronized data. IEEE
Transactions on Power Delivery, 30(3), 1067-1076.
[50]. Moghadas, R. K. & Gholizadeh, S. (2008). A New
Wavelet Back Propagation Neural Networks for Structural
Dynamic Analysis. Engineering Letters, 16(1).
[51]. Navrat, P., Jelinek, T., & Jastrzembska, L. (2009,
December). Bee hive at work: A problem solving,
optimizing mechanism. In Nature & Biologically Inspired
Computing, 2009. NaBIC 2009. World Congress on (pp.
122-127). IEEE.
[52]. Nhicolaievna, P. N. & Thanh, L. V. (2008). Bee Colony
Algorithm for the Multidimensional Knapsack Problem.
Proceedings of the International Multi Conference of
[53]. Niebur, D. & El-Sharkawi, M. (1996). Tutorial course on
artificial neural networks with applications to power systems.
In IEEE Power Engineering Society (pp. 117-125).
[54]. Saab, S. M., El-Omari, N. K. T., & Hussein, H. O. (2009).
Developing optimization algorithm using artificial bee colony
system. Ubiquitous Computing and Communication
Journal, 4(5), 15-19.
[55]. Sahel, S. S. D. & Boudour, M. Application of particle
swarm optimization based neural network to fault
th classification. In Electrical Engineering (ICEE), 2015 4
International Conference on (pp. 1-4). IEEE.
[56]. Sahel, S. S. D. & Boudour, M. (2013). Fault Location in
Transmission Lines using BP Neural Network Trained with PSO
Algorithm. Journal of Energy and Power Engineering, 7(3),
603-611.
[57]. Sallim, J., Hussin, W., Syahrir, W. M., Abdullah, R.,
Khader, A. & Tajudin, A. (2007). A Background Study on Ant
Colony Optimization Metaheuristic and its Application
Principles in Resolving Three Combinatorial Optimization
Problem. In National Conference on Software Engineering
and Computer Systems, Legend Resort Kuantan.
[58]. Sanaye-Pasand, M. & Khorashadi-Zadeh, H. (2006).
An extended ANN-based high speed accurate distance
protection algorithm. International Journal of Electrical
Power & Energy Systems, 28(6), 387-395.
[59]. Sekine, Y., Akimoto, Y., Kunugi, M., Fukui, C., & Fukui, S.
(1992). Fault diagnosis of power systems. Proceedings of
the IEEE, 80(5), 673-683.
[60]. Sekine, Y., Okamoto, H., & Shibamoto, T. (1989, July).
Fault section estimation using cause-effect network. In
nd Proceedings of 2 Symposium on Expert System
Application to Power Systems (pp. 277-282).
[61]. Shi, Y. (2001). Particle swarm optimization: developments, applications and resources. In Evolutionary Computation, 2001. Proceedings of the 2001 Congress on (Vol. 1, pp. 81-86). IEEE.
[62]. Stanarevic, N., Tuba, M., & Bacanin, N. (2011).
Modified Artificial Bee Colony algorithm for constrained
problems optimization. International Journal of
Mathematical Models and Methods in Applied Sciences,
5(3), 644-651.
[63]. Tang, Y., Wang, H. F., Aggarwal, R. K., & Johns, A. T.
(2000). Fault indicators in transmission and distribution
systems. In Electric Utility Deregulation and Restructuring
and Power Technologies, 2000. Proceedings. DRPT 2000.
International Conference on (pp. 238-243). IEEE.
[64]. Tayeb, E. B. M. & Rhim, O. A. A. A. (2011, September).
Transmission line faults detection, classification and
location using artificial neural network. In Utility Exhibition on
Power and Energy Systems: Issues & Prospects for Asia
(ICUE), 2011 International Conference and (pp. 1-5). IEEE.
[65]. Teodorovic, D. & Dell'Orco, M. (2005). Bee colony
optimization–a cooperative learning approach to
complex transportation problems. Advanced OR and AI
Methods in Transportation, 51-60.
[66]. Tsai, P. W., Pan, J. S., Liao, B. Y., & Chu, S. C. (2009).
Enhanced artificial bee colony optimization. International
Journal of Innovative Computing, Information and Control,
5(12), 5081-5092.
[67]. Wong, L. P., Low, M. Y. H., & Chong, C. S. (2010). Bee
colony optimization with local search for traveling
salesman problem. International Journal on Artificial
Intelligence Tools, 19(03), 305-334.
[68]. Yang, X. S. (2005). Engineering optimizations via
nature-inspired virtual bee algorithms. Artificial Intelligence
and Knowledge Engineering Applications: A Bioinspired
Approach, 317-323
