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Volumn 159, Issue 1, 2015, Pages 288-297

Navigability analysis of magnetic map with projecting pursuit-based selection method by using firefly algorithm

Author keywords

Firefly algorithm; Geomagnetic aided navigation; Navigability analysis; Projecting pursuit based selection method

Indexed keywords

ALGORITHMS; BIOLUMINESCENCE; COMPUTATIONAL EFFICIENCY; EVOLUTIONARY ALGORITHMS; GEOMAGNETISM; NAVIGATION; OPTIMIZATION; PARAMETER ESTIMATION; PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84933279463     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2015.01.028     Document Type: Article
Times cited : (27)

References (25)
  • 1
    • 77958088478 scopus 로고    scopus 로고
    • Influence of measurement errors from magnetic dipole field upon determination of underwater vehicle position
    • Huang Y., Hao Y.L. Influence of measurement errors from magnetic dipole field upon determination of underwater vehicle position. J. Huazhong Univ. Sci. Technol. (Nat. Sci. Ed.) 2010, 38:76-81.
    • (2010) J. Huazhong Univ. Sci. Technol. (Nat. Sci. Ed.) , vol.38 , pp. 76-81
    • Huang, Y.1    Hao, Y.L.2
  • 2
    • 84933279827 scopus 로고    scopus 로고
    • Selection of geomagnetic adaptable matching area in geomagnetic matching navigation
    • Wang X.L., Su M.D., Ding S. Selection of geomagnetic adaptable matching area in geomagnetic matching navigation. J. Geodesy Geodyn. 2001, 31:79-83.
    • (2001) J. Geodesy Geodyn. , vol.31 , pp. 79-83
    • Wang, X.L.1    Su, M.D.2    Ding, S.3
  • 3
  • 4
    • 78649587965 scopus 로고    scopus 로고
    • Geomagnetic navigation and magnetic maps in sea turtles
    • Lohmann K.J., Lohmann C.M.F. Geomagnetic navigation and magnetic maps in sea turtles. J. Navig. 2008, 55:115-125.
    • (2008) J. Navig. , vol.55 , pp. 115-125
    • Lohmann, K.J.1    Lohmann, C.M.F.2
  • 5
    • 78651394799 scopus 로고    scopus 로고
    • Geomagnetic matching algorithm based on the probabilistic neural network
    • Zhou J., Liu Y., Ge Z.L. Geomagnetic matching algorithm based on the probabilistic neural network. Proc. Inst. Mech. Eng., Part G: J. Aerosp. Eng. 2011, 225:120-126.
    • (2011) Proc. Inst. Mech. Eng., Part G: J. Aerosp. Eng. , vol.225 , pp. 120-126
    • Zhou, J.1    Liu, Y.2    Ge, Z.L.3
  • 6
    • 78751608395 scopus 로고    scopus 로고
    • A projecting pursuit-based selection method for matching region in geomagnetism navigation
    • Liu Y.X., Zhou J., Ge.Z.L. A projecting pursuit-based selection method for matching region in geomagnetism navigation. J. Astronaut. 2010, 31:2677-2682.
    • (2010) J. Astronaut. , vol.31 , pp. 2677-2682
    • Liu, Y.X.1    Zhou, J.2    Ge, Z.L.3
  • 8
    • 84901269423 scopus 로고    scopus 로고
    • An adaptive differential evolution algorithm for global optimization in dynamic environments
    • Das S., Mandal A., Mukherjee.R. An adaptive differential evolution algorithm for global optimization in dynamic environments. IEEE Trans. Cybern. 2014, 44:966-978.
    • (2014) IEEE Trans. Cybern. , vol.44 , pp. 966-978
    • Das, S.1    Mandal, A.2    Mukherjee, R.3
  • 9
    • 84884385865 scopus 로고    scopus 로고
    • A real-integer-discrete-coded differential evolution
    • Datta D., Figueira J.R. A real-integer-discrete-coded differential evolution. Appl. Soft Comput. J. 2013, 13:3884-3893.
    • (2013) Appl. Soft Comput. J. , vol.13 , pp. 3884-3893
    • Datta, D.1    Figueira, J.R.2
  • 10
    • 79952003251 scopus 로고    scopus 로고
    • Differential evolution: a survey of the state-of-the-art
    • Das S., Suganthan P.N. Differential evolution: a survey of the state-of-the-art. IEEE Trans. Evol. Comput. 2011, 15:4-31.
    • (2011) IEEE Trans. Evol. Comput. , vol.15 , pp. 4-31
    • Das, S.1    Suganthan, P.N.2
  • 11
    • 84875367228 scopus 로고    scopus 로고
    • Differential evolution based nearest prototype classifier with optimized distance measures for the features in the data sets
    • Koloseni D., Lampinen J., Luukka P. Differential evolution based nearest prototype classifier with optimized distance measures for the features in the data sets. Expert Syst. Appl. 2013, 40:4075-4082.
    • (2013) Expert Syst. Appl. , vol.40 , pp. 4075-4082
    • Koloseni, D.1    Lampinen, J.2    Luukka, P.3
  • 12
    • 84873638127 scopus 로고    scopus 로고
    • Evolutionary algorithm characterization in real parameter optimization problems
    • Pilar C., Francisco B., Becerra J.A., Duro R.J. Evolutionary algorithm characterization in real parameter optimization problems. Appl. Soft Comput. J. 2013, 13:1902-1921.
    • (2013) Appl. Soft Comput. J. , vol.13 , pp. 1902-1921
    • Pilar, C.1    Francisco, B.2    Becerra, J.A.3    Duro, R.J.4
  • 14
    • 77957896671 scopus 로고    scopus 로고
    • A note on the learning automata based algorithms for adaptive parameter selection in PSO
    • Hashemi A.B., Meybodi.M.R. A note on the learning automata based algorithms for adaptive parameter selection in PSO. Appl. Soft Comput. J. 2011, 11:689-705.
    • (2011) Appl. Soft Comput. J. , vol.11 , pp. 689-705
    • Hashemi, A.B.1    Meybodi, M.R.2
  • 15
    • 84876740156 scopus 로고    scopus 로고
    • An improvement in RBF learning algorithm based on PSO for real time applications
    • Fathi V., Montazer.G.A. An improvement in RBF learning algorithm based on PSO for real time applications. Neurocomputing 2013, 111:169-176.
    • (2013) Neurocomputing , vol.111 , pp. 169-176
    • Fathi, V.1    Montazer, G.A.2
  • 16
    • 79960199031 scopus 로고    scopus 로고
    • Nonlinear mappings in problem solving and their PSO-based development
    • Pedrycz A., Dong F.Y., Hirota K. Nonlinear mappings in problem solving and their PSO-based development. Inf. Sci. 2011, 181:4112-4123.
    • (2011) Inf. Sci. , vol.181 , pp. 4112-4123
    • Pedrycz, A.1    Dong, F.Y.2    Hirota, K.3
  • 17
    • 67349276385 scopus 로고    scopus 로고
    • A modified particle swarm optimization via particle visual modeling analysis
    • Zhao Y.X., Zu W., Zeng.H.T. A modified particle swarm optimization via particle visual modeling analysis. Comput. Math. Appl. 2009, 57:2022-2029.
    • (2009) Comput. Math. Appl. , vol.57 , pp. 2022-2029
    • Zhao, Y.X.1    Zu, W.2    Zeng, H.T.3
  • 18
    • 56349106409 scopus 로고    scopus 로고
    • PSO-based single multiplicative neuron model for time series prediction
    • Zhao L., Yang Y.P. PSO-based single multiplicative neuron model for time series prediction. Expert Syst. Appl. 2009, 36:2805-2812.
    • (2009) Expert Syst. Appl. , vol.36 , pp. 2805-2812
    • Zhao, L.1    Yang, Y.P.2
  • 21
    • 84897492572 scopus 로고    scopus 로고
    • A discrete firefly algorithm for the multi-objective hybrid flowshop scheduling problems
    • Marichelvam M.K., Prabaharan T., Yang.X.S. A discrete firefly algorithm for the multi-objective hybrid flowshop scheduling problems. IEEE Trans. Evolut. Comput. 2014, 18:301-305.
    • (2014) IEEE Trans. Evolut. Comput. , vol.18 , pp. 301-305
    • Marichelvam, M.K.1    Prabaharan, T.2    Yang, X.S.3
  • 22
    • 80052020906 scopus 로고    scopus 로고
    • Multilevel minimum cross entropy threshold selection based on the firefly algorithm
    • Horng M.H., Liou R.J. Multilevel minimum cross entropy threshold selection based on the firefly algorithm. Expert Syst. Appl. 2011, 38:14805-14811.
    • (2011) Expert Syst. Appl. , vol.38 , pp. 14805-14811
    • Horng, M.H.1    Liou, R.J.2
  • 23
    • 79953818807 scopus 로고    scopus 로고
    • Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter
    • Bavdekar V.A., Deshpande A.P., Patwardhan S.C. Identification of process and measurement noise covariance for state and parameter estimation using extended Kalman filter. J. Process Control 2011, 21:585-601.
    • (2011) J. Process Control , vol.21 , pp. 585-601
    • Bavdekar, V.A.1    Deshpande, A.P.2    Patwardhan, S.C.3
  • 25
    • 84855949070 scopus 로고    scopus 로고
    • Some relations between extended and unscented Kalman filters
    • Gustafsson F., Hendeby G. Some relations between extended and unscented Kalman filters. IEEE Trans. Signal Process. 2012, 60:545-555.
    • (2012) IEEE Trans. Signal Process. , vol.60 , pp. 545-555
    • Gustafsson, F.1    Hendeby, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.