Skip to main content
Top

2011 | OriginalPaper | Chapter

2. Automatic Relevance Determination for Identifying Interstate Conflict

Authors : Tshilidzi Marwala, Dr. Monica Lagazio

Published in: Militarized Conflict Modeling Using Computational Intelligence

Publisher: Springer London

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This chapter introduces the Bayesian and the evidence frameworks to construct an automatic relevance determination method. These techniques are described in detail, relevant literature reviews were conducted and their use is justified. The automatic relevance determination technique was then applied to determine the relevance of interstate variables that are essential for modeling interstate conflict. Conclusions are drawn and explained within the context of political science.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
go back to reference Babaie-Kafaki, S., Ghanbari, R., Mahdavi-Amiri, N.: Two new conjugate gradient methods based on modified secant equations. J. Comput. Appl. Math. 234, 1374–1386 (2010)MathSciNetMATHCrossRef Babaie-Kafaki, S., Ghanbari, R., Mahdavi-Amiri, N.: Two new conjugate gradient methods based on modified secant equations. J. Comput. Appl. Math. 234, 1374–1386 (2010)MathSciNetMATHCrossRef
go back to reference Barton, D.N., Saloranta, T., Moe, S.J., Eggestad, H.O., Kuikka, S.: Bayesian belief networks as a meta-modelling tool in integrated river basin management – pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian River Basin. Ecol. Econ. 66, 91–104 (2008)CrossRef Barton, D.N., Saloranta, T., Moe, S.J., Eggestad, H.O., Kuikka, S.: Bayesian belief networks as a meta-modelling tool in integrated river basin management – pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian River Basin. Ecol. Econ. 66, 91–104 (2008)CrossRef
go back to reference Beck, N., King, G., Zeng, L.: Improving quantitative studies of international conflict: a conjecture. Am. Polit. Sci. Rev 94, 21–35 (2000)CrossRef Beck, N., King, G., Zeng, L.: Improving quantitative studies of international conflict: a conjecture. Am. Polit. Sci. Rev 94, 21–35 (2000)CrossRef
go back to reference Bernardo, J.M.: Reference posterior distributions for Bayesian inference. J. R. Stat. Soc. 41, 113–147 (1979)MathSciNetMATH Bernardo, J.M.: Reference posterior distributions for Bayesian inference. J. R. Stat. Soc. 41, 113–147 (1979)MathSciNetMATH
go back to reference Bertsekas, D.P.: Non-linear Programming. Athenas Scientific, Cambridge (1995) Bertsekas, D.P.: Non-linear Programming. Athenas Scientific, Cambridge (1995)
go back to reference Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995) Bishop, C.M.: Neural Networks for Pattern Recognition. Oxford University Press, Oxford (1995)
go back to reference Box, G.E.P., Tiao, G.C.: Bayesian Inference in Statistical Analysis. Wiley, Hoboken (1973)MATH Box, G.E.P., Tiao, G.C.: Bayesian Inference in Statistical Analysis. Wiley, Hoboken (1973)MATH
go back to reference Browne, A.: Using neural networks with automatic relevance determination to identify regions of the thalamus implicated in Schizophrenia. In: Proceedings of the IEEE International Joint Conference on Neural Networks. pp. 97–101, Vancouver (2006) Browne, A.: Using neural networks with automatic relevance determination to identify regions of the thalamus implicated in Schizophrenia. In: Proceedings of the IEEE International Joint Conference on Neural Networks. pp. 97–101, Vancouver (2006)
go back to reference Bryson, A.E., Ho, Y.C.: Applied Optimal Control: Optimization, Estimation, and Control. Xerox College Publishing, Kentucky (1989) Bryson, A.E., Ho, Y.C.: Applied Optimal Control: Optimization, Estimation, and Control. Xerox College Publishing, Kentucky (1989)
go back to reference Chiddarwar, S.S., Babu, N.R.: Comparison of RBF and MLP neural networks to solve inverse kinematic problems for 6R serial robots by a fusion approach. Eng. Appl. Artif. Intel 23, 1083–1092 (2010)CrossRef Chiddarwar, S.S., Babu, N.R.: Comparison of RBF and MLP neural networks to solve inverse kinematic problems for 6R serial robots by a fusion approach. Eng. Appl. Artif. Intel 23, 1083–1092 (2010)CrossRef
go back to reference Ebrahimzadeh, A., Khazaee, A.: Detection of premature ventricular contractions using mlp neural networks: a comparative study. Measurement 43, 103–112 (2010)CrossRef Ebrahimzadeh, A., Khazaee, A.: Detection of premature ventricular contractions using mlp neural networks: a comparative study. Measurement 43, 103–112 (2010)CrossRef
go back to reference Edwards, A.W.F.: Likelihood. Cambridge University Press, Cambridge (1972)MATH Edwards, A.W.F.: Likelihood. Cambridge University Press, Cambridge (1972)MATH
go back to reference Fletcher, R.: Practical Methods of Optimization. Wiley, New York (1987)MATH Fletcher, R.: Practical Methods of Optimization. Wiley, New York (1987)MATH
go back to reference Freeman, J., Skapura, D.: Neural Networks: Algorithms, Applications and Programming Techniques. Addison-Wesley, Reading (1991)MATH Freeman, J., Skapura, D.: Neural Networks: Algorithms, Applications and Programming Techniques. Addison-Wesley, Reading (1991)MATH
go back to reference Fu, Y., Browne, A.: Using ensembles of neural networks to improve automatic relevance determination. In: Proceeding of the IEEE International Joint Conference on Neural Networks, pp. 1590–1594, Orlando (2007) Fu, Y., Browne, A.: Using ensembles of neural networks to improve automatic relevance determination. In: Proceeding of the IEEE International Joint Conference on Neural Networks, pp. 1590–1594, Orlando (2007)
go back to reference Gelpi, C., Griesdorf, M.: Winners and losers? Democracies in international crisis, 1918–94. Am. Polit. Sci. Rev 95, 633–647 (2001)CrossRef Gelpi, C., Griesdorf, M.: Winners and losers? Democracies in international crisis, 1918–94. Am. Polit. Sci. Rev 95, 633–647 (2001)CrossRef
go back to reference Ghate, V.N., Dudul, S.V.: Optimal MLP neural network classifier for fault detection of three phase induction motor. Expert Syst. Appl. 37, 3468–3481 (2010)CrossRef Ghate, V.N., Dudul, S.V.: Optimal MLP neural network classifier for fault detection of three phase induction motor. Expert Syst. Appl. 37, 3468–3481 (2010)CrossRef
go back to reference Gleditsch, K.S., Wards, M.D.: Peace and war in time and space: the role of democratization. Int. Stud. Q. 43, 1–29 (2000)CrossRef Gleditsch, K.S., Wards, M.D.: Peace and war in time and space: the role of democratization. Int. Stud. Q. 43, 1–29 (2000)CrossRef
go back to reference Gochman, C., Maoz, Z.: Militarized interstate disputes 1816–1976. In: Singer, D., Diehl, P. (eds.) Measuring the Correlates of War. University of Michigan Press, Ann Arbor (1990) Gochman, C., Maoz, Z.: Militarized interstate disputes 1816–1976. In: Singer, D., Diehl, P. (eds.) Measuring the Correlates of War. University of Michigan Press, Ann Arbor (1990)
go back to reference Habtemariam, E., Marwala, T., Lagazio, M.: Artificial intelligence for conflict management. In: Proceedings of the IEEE International Joint Conference on Neural Networks, pp. 2583–2588, Montreal (2005) Habtemariam, E., Marwala, T., Lagazio, M.: Artificial intelligence for conflict management. In: Proceedings of the IEEE International Joint Conference on Neural Networks, pp. 2583–2588, Montreal (2005)
go back to reference Hassoun, M.H.: Fundamentals of Artificial Neural Networks. MIT Press, Cambridge (1995)MATH Hassoun, M.H.: Fundamentals of Artificial Neural Networks. MIT Press, Cambridge (1995)MATH
go back to reference Haykin, S.: Neural Networks. Prentice-Hall, Englewood Cliffs (1999)MATH Haykin, S.: Neural Networks. Prentice-Hall, Englewood Cliffs (1999)MATH
go back to reference Hestenes, M.R., Stiefel, E.: Methods of conjugate gradients for solving linear systems. J. Res. Nat. Bur. Stand 6, 409–436 (1952)MathSciNet Hestenes, M.R., Stiefel, E.: Methods of conjugate gradients for solving linear systems. J. Res. Nat. Bur. Stand 6, 409–436 (1952)MathSciNet
go back to reference Jaynes, E.T.: Prior probabilities. IEEE Trans. Syst. Sci. Cyb. 4, 227–241 (1968)CrossRef Jaynes, E.T.: Prior probabilities. IEEE Trans. Syst. Sci. Cyb. 4, 227–241 (1968)CrossRef
go back to reference Kelly, D.L., Smith, C.L.: Bayesian inference in probabilistic risk assessment – the current state of the art. Reliab. Eng. Syst. Saf. 94, 628–643 (2009)CrossRef Kelly, D.L., Smith, C.L.: Bayesian inference in probabilistic risk assessment – the current state of the art. Reliab. Eng. Syst. Saf. 94, 628–643 (2009)CrossRef
go back to reference Kim, G., Kim, Y., Lim, H., Kim, H.: An MLP-based feature subset selection for HIV-1 protease cleavage site analysis. Artif. Intell. Med. 48, 83–89 (2010)CrossRef Kim, G., Kim, Y., Lim, H., Kim, H.: An MLP-based feature subset selection for HIV-1 protease cleavage site analysis. Artif. Intell. Med. 48, 83–89 (2010)CrossRef
go back to reference Lagazio, M., Marwala, T.: Assessing different bayesian neural network models for militarized interstate dispute. Soc. Sci. Comput. Rev. 24, 1–12 (2005) Lagazio, M., Marwala, T.: Assessing different bayesian neural network models for militarized interstate dispute. Soc. Sci. Comput. Rev. 24, 1–12 (2005)
go back to reference Lagazio, M., Russet, B.: A neural network analysis of MIDs, 1885–1992: are the patterns stable? In: Diehl, P. (ed.) Toward a Scientific Understanding of War: Studies in Honor of J. David Singer. University of Michigan Press, Ann Arbor (2002) Lagazio, M., Russet, B.: A neural network analysis of MIDs, 1885–1992: are the patterns stable? In: Diehl, P. (ed.) Toward a Scientific Understanding of War: Studies in Honor of J. David Singer. University of Michigan Press, Ann Arbor (2002)
go back to reference Lazkano, E., Sierra, B., Astigarraga, A., Martínez-Otzeta, J.M.: On the use of Bayesian networks to develop behaviours for mobile robots. Robot. Auton. Syst. 55, 253–265 (2007)CrossRef Lazkano, E., Sierra, B., Astigarraga, A., Martínez-Otzeta, J.M.: On the use of Bayesian networks to develop behaviours for mobile robots. Robot. Auton. Syst. 55, 253–265 (2007)CrossRef
go back to reference Lee, P.M.: Bayesian Statistics, an Introduction. Wiley, Hoboken (2004)MATH Lee, P.M.: Bayesian Statistics, an Introduction. Wiley, Hoboken (2004)MATH
go back to reference Leke, B., Marwala, T., Tettey, T.: Using inverse neural network for HIV adaptive control. Int. J. Comput. Intell. Res. 3, 11–15 (2007) Leke, B., Marwala, T., Tettey, T.: Using inverse neural network for HIV adaptive control. Int. J. Comput. Intell. Res. 3, 11–15 (2007)
go back to reference Lisboa, P.J.G., Etchells, T.A., Jarman, I.H., Arsene, C.T.C., Aung, M.S.H., Eleuteri, A., Taktak, A.F.G., Ambrogi, F., Boracchi, P., Biganzoli, E.: Partial logistic artificial neural network for competing risks regularized with automatic relevance determination. IEEE Trans. Neural. Nets 20, 1403–1416 (2009)CrossRef Lisboa, P.J.G., Etchells, T.A., Jarman, I.H., Arsene, C.T.C., Aung, M.S.H., Eleuteri, A., Taktak, A.F.G., Ambrogi, F., Boracchi, P., Biganzoli, E.: Partial logistic artificial neural network for competing risks regularized with automatic relevance determination. IEEE Trans. Neural. Nets 20, 1403–1416 (2009)CrossRef
go back to reference Luenberger, D.G.: Linear and Non-linear Programming. Addison-Wesley, Reading (1984) Luenberger, D.G.: Linear and Non-linear Programming. Addison-Wesley, Reading (1984)
go back to reference Lunga, D., Marwala, T.: On-line forecasting of stock market movement direction using the improved incremental algorithm. Lecture Notes in Computer Science, vol. 4234, pp. 440–449, Springer Heidelberg (2006) Lunga, D., Marwala, T.: On-line forecasting of stock market movement direction using the improved incremental algorithm. Lecture Notes in Computer Science, vol. 4234, pp. 440–449, Springer Heidelberg (2006)
go back to reference MacKay, D.J.C.: Bayesian methods for adaptive models. PhD thesis, California Institute of Technology (1991) MacKay, D.J.C.: Bayesian methods for adaptive models. PhD thesis, California Institute of Technology (1991)
go back to reference MacKay, D.J.C.: A practical Bayesian framework for back propagation networks. Neural Comput. 4, 448–472 (1992)CrossRef MacKay, D.J.C.: A practical Bayesian framework for back propagation networks. Neural Comput. 4, 448–472 (1992)CrossRef
go back to reference Marwala, T.: On damage identification using a committee of neural networks. J. Eng. Mech. 126, 43–50 (2000)CrossRef Marwala, T.: On damage identification using a committee of neural networks. J. Eng. Mech. 126, 43–50 (2000)CrossRef
go back to reference Marwala, T.: Probabilistic fault identification using a committee of neural networks and vibration data. J. Aircraft 38, 138–146 (2001)CrossRef Marwala, T.: Probabilistic fault identification using a committee of neural networks and vibration data. J. Aircraft 38, 138–146 (2001)CrossRef
go back to reference Marwala, T.: Fault classification using pseudo modal energies and neural networks. Am. Inst. Aeronaut. Astronaut. J. 41, 82–89 (2003) Marwala, T.: Fault classification using pseudo modal energies and neural networks. Am. Inst. Aeronaut. Astronaut. J. 41, 82–89 (2003)
go back to reference Marwala, T.: Computational Intelligence for Missing Data Imputation, Estimation and Management: Knowledge Optimization Techniques. IGI Global Publications, New York (2009)CrossRef Marwala, T.: Computational Intelligence for Missing Data Imputation, Estimation and Management: Knowledge Optimization Techniques. IGI Global Publications, New York (2009)CrossRef
go back to reference Marwala, T.: Finite Element Model Updating Using Computational Intelligence Techniques: Applications to Structural Dynamics. Springer, Heidelberg (2010)MATHCrossRef Marwala, T.: Finite Element Model Updating Using Computational Intelligence Techniques: Applications to Structural Dynamics. Springer, Heidelberg (2010)MATHCrossRef
go back to reference Marwala, T., Hunt, H.E.M.: Fault identification using finite element models and neural networks. Mech. Syst. Signal. Process 13, 475–490 (1999)CrossRef Marwala, T., Hunt, H.E.M.: Fault identification using finite element models and neural networks. Mech. Syst. Signal. Process 13, 475–490 (1999)CrossRef
go back to reference Marwala, T., Lagazio, M.: Modelling and controlling interstate conflict. In: Proceedings of the IEEE International Joint Conference on Neural Networks, pp. 1233–1238, Budapest (2004) Marwala, T., Lagazio, M.: Modelling and controlling interstate conflict. In: Proceedings of the IEEE International Joint Conference on Neural Networks, pp. 1233–1238, Budapest (2004)
go back to reference Marwala, T., Sibisi, S.: Finite element model updating using bayesian framework and modal properties. J. Aircraft 42, 275–278 (2005)CrossRef Marwala, T., Sibisi, S.: Finite element model updating using bayesian framework and modal properties. J. Aircraft 42, 275–278 (2005)CrossRef
go back to reference Mohamed, N., Rubin, D., Marwala, T.: Detection of epileptiform activity in human EEG signals using bayesian neural networks. Neural Info. Process Lett. Rev. 10, 1–10 (2006) Mohamed, N., Rubin, D., Marwala, T.: Detection of epileptiform activity in human EEG signals using bayesian neural networks. Neural Info. Process Lett. Rev. 10, 1–10 (2006)
go back to reference Møller, A.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Nets 6, 525–533 (1993)CrossRef Møller, A.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Nets 6, 525–533 (1993)CrossRef
go back to reference Mordecai, A.: Non-linear Programming: Analysis and Methods. Dover Publishing, New York (2003) Mordecai, A.: Non-linear Programming: Analysis and Methods. Dover Publishing, New York (2003)
go back to reference Neal, R.M.: Bayesian learning for neural networks. PhD thesis, University of Toronto (1994) Neal, R.M.: Bayesian learning for neural networks. PhD thesis, University of Toronto (1994)
go back to reference Neal, R.M.: Assessing the relevance determination methods using DELVE. In: Bishop, C.M. (ed.) Neural Nets and Machine Learn. Springer, Berlin (1998) Neal, R.M.: Assessing the relevance determination methods using DELVE. In: Bishop, C.M. (ed.) Neural Nets and Machine Learn. Springer, Berlin (1998)
go back to reference Nummenmaa, A., Auranen, T., Hämäläinen, M.S., Jääskeläinen, I.P., Sams, M., Vehtari, A., Lampinen, J.: Automatic relevance determination based hierarchical Bayesian MEG inversion in practice. NeuroImage 37, 876–889 (2007)CrossRef Nummenmaa, A., Auranen, T., Hämäläinen, M.S., Jääskeläinen, I.P., Sams, M., Vehtari, A., Lampinen, J.: Automatic relevance determination based hierarchical Bayesian MEG inversion in practice. NeuroImage 37, 876–889 (2007)CrossRef
go back to reference Oneal, J.R., Russett, B.: Clear and clean: the fixed effects of democracy and economic interdependence. Int. Organ 3, 469–486 (2001)CrossRef Oneal, J.R., Russett, B.: Clear and clean: the fixed effects of democracy and economic interdependence. Int. Organ 3, 469–486 (2001)CrossRef
go back to reference Patel, P., Marwala, T.: Neural networks, fuzzy inference systems and adaptive-neuro fuzzy inference systems for financial decision making. Lecture Notes in Computer Science, vol. 4234, pp. 430–439, Springer Heidelberg (2006) Patel, P., Marwala, T.: Neural networks, fuzzy inference systems and adaptive-neuro fuzzy inference systems for financial decision making. Lecture Notes in Computer Science, vol. 4234, pp. 430–439, Springer Heidelberg (2006)
go back to reference Rosenblatt, F.: Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms. Spartan, Washington, DC (1961) Rosenblatt, F.: Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms. Spartan, Washington, DC (1961)
go back to reference Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Parallel Distributed Processing: Explorations in the Microstructure of Cognition. MIT Press, Cambridge (1986) Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Parallel Distributed Processing: Explorations in the Microstructure of Cognition. MIT Press, Cambridge (1986)
go back to reference Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs (1995)MATH Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs (1995)MATH
go back to reference Sahin, F., Yavuz, M.Ç., Arnavut, Z., Uluyol, Ö.: Fault diagnosis for airplane engines using Bayesian networks and distributed particle swarm optimization. Parallel Comput. 33, 124–143 (2007)MathSciNetCrossRef Sahin, F., Yavuz, M.Ç., Arnavut, Z., Uluyol, Ö.: Fault diagnosis for airplane engines using Bayesian networks and distributed particle swarm optimization. Parallel Comput. 33, 124–143 (2007)MathSciNetCrossRef
go back to reference Smyrnakis, M.G., Evans, D.J.: Classifying ischemic events using a Bayesian inference multilayer perceptron and input variable evaluation using automatic relevance determination. Comput. Cardiol. 34, 305–308 (2007)CrossRef Smyrnakis, M.G., Evans, D.J.: Classifying ischemic events using a Bayesian inference multilayer perceptron and input variable evaluation using automatic relevance determination. Comput. Cardiol. 34, 305–308 (2007)CrossRef
go back to reference Stigler, S.M.: The History of Statistics. Harvard University Press, Cambridge (1986)MATH Stigler, S.M.: The History of Statistics. Harvard University Press, Cambridge (1986)MATH
go back to reference Tibshirani, R.: Regression shrinkage and selection via the lasso. J. R. Stat. Soc. 58, 267–288 (1996)MathSciNetMATH Tibshirani, R.: Regression shrinkage and selection via the lasso. J. R. Stat. Soc. 58, 267–288 (1996)MathSciNetMATH
go back to reference Ulusoy, I., Bishop, C.M.: Automatic relevance determination for the estimation of relevant features for object recognition. In: Proceedings of the IEEE 14th Signal Processing and Communication Applications, pp. 1–4, Antalya (2006) Ulusoy, I., Bishop, C.M.: Automatic relevance determination for the estimation of relevant features for object recognition. In: Proceedings of the IEEE 14th Signal Processing and Communication Applications, pp. 1–4, Antalya (2006)
go back to reference Uusitalo, L.: Advantages and challenges of Bayesian networks in environmental modelling. Ecol. Model. 203, 312–318 (2007)CrossRef Uusitalo, L.: Advantages and challenges of Bayesian networks in environmental modelling. Ecol. Model. 203, 312–318 (2007)CrossRef
go back to reference Van Calster, B., Timmerman, D., Nabney, I.T., Valentin, L., Van Holsbeke, C., Van Huffel, S.: Classifying ovarian tumors using Bayesian multi-layer perceptrons and automatic relevance determination: a multi-center study. In: Proceedings of the Engineering in Medicine and Biology Society, pp. 5342–5345, New York (2006) Van Calster, B., Timmerman, D., Nabney, I.T., Valentin, L., Van Holsbeke, C., Van Huffel, S.: Classifying ovarian tumors using Bayesian multi-layer perceptrons and automatic relevance determination: a multi-center study. In: Proceedings of the Engineering in Medicine and Biology Society, pp. 5342–5345, New York (2006)
go back to reference Vilakazi, B.C., Marwala, T.: Condition monitoring using computational intelligence. In: Laha, D., Mandal, P. (eds.) Handbook on Computational Intelligence in Manufacturing and Production Management, illustrated edn. IGI Publishers, New York (2007) Vilakazi, B.C., Marwala, T.: Condition monitoring using computational intelligence. In: Laha, D., Mandal, P. (eds.) Handbook on Computational Intelligence in Manufacturing and Production Management, illustrated edn. IGI Publishers, New York (2007)
go back to reference Wang, D., Lu, W.Z.: Interval estimation of urban ozone level and selection of influential factors by employing automatic relevance determination. Model. Chemosphere 62, 1600–1611 (2006) Wang, D., Lu, W.Z.: Interval estimation of urban ozone level and selection of influential factors by employing automatic relevance determination. Model. Chemosphere 62, 1600–1611 (2006)
go back to reference Werbos, P.J.: Beyond regression: new tool for prediction and analysis in the behavioral sciences. Ph.D. thesis, Harvard University (1974) Werbos, P.J.: Beyond regression: new tool for prediction and analysis in the behavioral sciences. Ph.D. thesis, Harvard University (1974)
go back to reference Wu, W., Chen, Z., Gao, S., Brown, E.N.: Hierarchical Bayesian modeling of inter-trial variability and variational Bayesian learning of common spatial patterns from multichannel EEG. In: Proceedings of the 2010 IEEE International Conference on Acoustics Speech and Signal Processing, pp. 501–504, Montreal (2010) Wu, W., Chen, Z., Gao, S., Brown, E.N.: Hierarchical Bayesian modeling of inter-trial variability and variational Bayesian learning of common spatial patterns from multichannel EEG. In: Proceedings of the 2010 IEEE International Conference on Acoustics Speech and Signal Processing, pp. 501–504, Montreal (2010)
go back to reference Yoon, Y., Peterson, L.L.: Artificial neural networks: An emerging new technique. In: Proceedings of the ACM SIGBDP Conference on Trends and Directions in Expert Systems, pp. 417–422, Orlando (1990) Yoon, Y., Peterson, L.L.: Artificial neural networks: An emerging new technique. In: Proceedings of the ACM SIGBDP Conference on Trends and Directions in Expert Systems, pp. 417–422, Orlando (1990)
go back to reference Zeng, L.: Prediction and classification with neural network models. Soc. Method Res. 27, 499–524 (1999)CrossRef Zeng, L.: Prediction and classification with neural network models. Soc. Method Res. 27, 499–524 (1999)CrossRef
go back to reference Zhang, J., Liu, S., Wang, Y.: Gene association study with SVM, MLP, and cross-validation for the diagnosis of diseases. Prog. Nat. Sci. 18, 741–750 (2008)MathSciNetCrossRef Zhang, J., Liu, S., Wang, Y.: Gene association study with SVM, MLP, and cross-validation for the diagnosis of diseases. Prog. Nat. Sci. 18, 741–750 (2008)MathSciNetCrossRef
go back to reference Zhao, Z., Xin, H., Ren, Y., Guo, X.: Application and comparison of BP neural network algorithm in MATLAB. In: Proceedings of the International Conference on Measurement Technology and Mechatron Automat, pp. 590–593, New York (2010) Zhao, Z., Xin, H., Ren, Y., Guo, X.: Application and comparison of BP neural network algorithm in MATLAB. In: Proceedings of the International Conference on Measurement Technology and Mechatron Automat, pp. 590–593, New York (2010)
Metadata
Title
Automatic Relevance Determination for Identifying Interstate Conflict
Authors
Tshilidzi Marwala
Dr. Monica Lagazio
Copyright Year
2011
Publisher
Springer London
DOI
https://doi.org/10.1007/978-0-85729-790-7_2

Premium Partner