Commenced in January 2007
Paper Count: 30184
A Performance Appraisal of Neural Networks Developed for Response Prediction across Heterogeneous Domains
Abstract:Deciding the numerous parameters involved in designing a competent artificial neural network is a complicated task. The existence of several options for selecting an appropriate architecture for neural network adds to this complexity, especially when different applications of heterogeneous natures are concerned. Two completely different applications in engineering and medical science were selected in the present study including prediction of workpiece's surface roughness in ultrasonic-vibration assisted turning and papilloma viruses oncogenicity. Several neural network architectures with different parameters were developed for each application and the results were compared. It was illustrated in this paper that some applications such as the first one mentioned above are apt to be modeled by a single network with sufficient accuracy, whereas others such as the second application can be best modeled by different expert networks for different ranges of output. Development of knowledge about the essentials of neural networks for different applications is regarded as the cornerstone of multidisciplinary network design programs to be developed as a means of reducing inconsistencies and the burden of the user intervention.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1073040Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1167
 J. M. Fines, and A. Aghah, "Machine tool positioning error compensation using artificial neural networks," Engineering Applications of Artificial Intelligence, vol. 21, pp. 1013-1026, 2008.
 S. Alam, S. C. Kaushik, and S. N. Garg, "Assesment of diffuse solar energy under general sky condition using artificial neural network," Applied Energy, vol. 86, pp. 554-564, 2009.
 Z. Yuhong, and H. Wenxin, "Application of artificial neural network to predict the friction factor of open channel flow," Commun Nonlinear Sci Simulat vol. 14, pp 2373-2378, 2009.
 H. Soleimanimehr, M. J. Nategh, and S. Amini, "Prediction of machining force and surface roughness in ultrasonic vibration-assisted turning using neural networks," in Proc. The Int. Conf. Advances in Materials & processing technologies, Manama, Bahrain, 2-5 Nov. 2008.
 A. R. Yildiz, "A novel hybrid immune algorithm for global optimization in design and manufacturing," Robotics and Computer-Integrated Manufacturing, vol. 25, pp. 261-270, 2009.
 A. L. Huyet, "Optimization and analysis aid via data-mining for simulated production systems," European J. Operational Research, vol. 173, pp. 827-838, 2006.
 C. Arbib, and F. Marinelli, "Integrating process optimization and inventory planning in cutting-stock with skiving option: An optimization model and its application," European J. Operational Research, vol. 163, pp. 617-630, 2005.
 M. Chambers, and C. A. Mount-Campbell, "Process optimization via neural network metamodeling," Int. J. Production Economics, vol. 79, pp. 93-100, 2002.
 Chi-Sheng Tsai, "Evaluation and optimisation of integrated manufacturing system operations using Taguch-s experiment design in computer simulation," Computers & Industrial Engineering, vol. 43, pp. 591-604, 2002.
 L. R. Khan, and R. A. Sarker, "An optimal batch size for a JIT manufacturing system," Computers & Industrial Engineering, vol. 42, pp. 127-136, 2002.
 J. A. Hern├índez, "Optimum operating conditions for heat and mass transfer in foodstuffs drying by means of neural network inverse," Food Control, vol. 20, pp. 435-438, 209.
 F. Marini, "The artificial neural networks in foodstuff analysis: Trends and perspectives. A review, Analytica Chimica Acta, DOI: 10.1016/j.aca.2009.01.009.
 A. M. Viale, J. W. Kolari, and D. R. Fraser, "Common risk factors in bank stocks,"J. Banking & Finance, vol. 33, pp. 464-472, 2009.
 Chun-Lang Chang, and Chih-Hao Chen, "Applying decision tree and neural network to increase quality of dermatologic diagnosis, " Expert Systems with Applications, vol. 36, pp. 4035-4041, 2009.
 I. Babaoglu, O. Kaan Baykan, N. Aygul, K. Ozdemir, and M. Bayrak, "Assessment of exercise stress testing with artificial neural network in determining coronary artery disease and predicting lesion localization," Expert Systems with Applications, vol. 36, pp. 2562-2566, 2009.
 P. Gerlee, and A. R. A. Anderson, "Modelling evolutionary cell behavior using neural networks: Application to tumour growth," BioSystems, vol. 95, pp. 166-174, 2009.
R. Das, I. Turkoglu, and A. Sengur, "Diagnosis of valvular heart disease through neural networks ensembles," Computer Methods and Programs in Biomedicine, vol. 93, pp. 185-191, 2009.
 F.X. Bosch, M. M. Manos, N. Munoz, M. Sherman, A. M. Jansen, J. Peto, M. H. Schiffma, V. Moreno, R. Kurman, and K. V. Shah, "Prevalence of human papillomavirus in cervical cancer: a worldwide perspective," J Natl Cancer Inst , vol.87, pp. 796-802, 1995.
 S. Lu, J. Fang, A. Guo, and Y. Peng, "Impact of network topology on decision-making," Neural Networks, vol. 22, pp. 30-40, 2009.
 D. Gil, M. Johnsson, J. M. G. Chamizo, A. S. Paya, and D. R. Fernandez, "Application of artificial neural networks in the diagnosis of urological dysfunctions," Expert Systems with Applications, vol. 36, pp. 5754-5760, 2009.
 K. Friston, "Learning and inference in the brain," Neural Networks, vol. 16, pp. 1325-1352, 2003.
 J. Lampinen, and A. Vehtari, "Bayesian approach for neural networksreview and case studies, Neural Networks, vol. 14, pp. 257-274, 2001.
 B. Horwitz, K. J. Friston, and J. G. Taylor, "Neural modeling and functional brain imaging: an overview, Neural Networks, vol. 13, pp. 829-846, 2000.
 A.R. McIntosh, "Towards a network theory of cognition," Neural Networks, vol. 13, pp. 861-870, 2000.
 J. G. Taylor, "Towards the networks of the brain: from brain imaging to consciousness," Neural Networks, vol. 12., pp. 943-959, 1999.
 M. Lehtokangas, "Modelling with constructive backpropagation," Neural Networks, vol. 12., pp. 707-716, 1999.
 K. Funahashi, "Multilayer neural networks and Bayes decision theory," Neural Networks, vol. 11., pp. 209-213, 1998.
 J. E.Dayhoff,, Neural Network Architectures. New York, Van Nostrand 1990.
 S. Amini, H. Soleimanimehr, M.J. Nategh, A. Abudollahb, and M. H. Sadeghi, "FEM analysis of ultrasonic-vibration-assisted turning and the vibratory tool," journal of materials processing technology, vol. 2 0 1, pp. 43-47, 2008.
 K. M├╝nger, A. Baldwin, K. M. Edwards, H. Hayakawa, C. L. Nguyen , M. Owens, et al., "Mechanisms of human papillomavirus-induced oncogenesis," J Virol , vol. 78, pp. 11451-11460, 2004.
 R. E. Streeck, "A short introduction to papillomavirus biology," Intervirology, vol. 45, pp. 287-289, 2002.
 K. Kawana, H. Yoshikawa H, Y. Taketani, K., Yoshiike, and T. Kanda, "Common neutralization epitope in minor capsid protein L2 of human papillomavirus types 16 and 6," J Virol, vol. 73, pp. 6188-6190, 1999.
 K. K. Thomas, J. P. Hughes, J. M. Kuypers, N. B. Kiviat, S. K. Lee, D. E. Adam, and L. A. Koutsky, "Concurrent and sequential acquisition of different genital human papillomavirus types," J Infectious Disease, vol. 182, pp. 1097-1102, 2000.
 K. Sotlar, D. Diemer, A. Dethleffs, Y. Hack, A. Stubner, N. Vollmer, et al., "Detection and typing of human papillomavirus by E6 nested multiplex PCR," J Clin Microbiol, vol. 42, pp. 3176-3184, 2004.
 D. K. Heck, C. L. Yee, P. M. Howley, and K. M├╝nger, " Efficiency of binding to the retinoblastoma protein correlates with the transforming capacity of the E7 oncoproteins of the human papillomaviruses," Proc Natl Acad Sci, pp. 4442-4446, 1992.
 J. Doorbar, "The papillomavirus life cycle," J clinical virology, vol. 32, pp. 7-15, 2005.
 L. A. Koutsky, K. A. Ault, C. M. Wheeler, D. R. Brown, E. Barr, F. B. Alvarez, et al, "A controlled trial of human Papillomavirus type 16 vaccine," N Engl j Med, vol. 347, pp. 1645-1651, 2002.
 L. L. Villa, K. Ault, A. R. Giuliano, R. L. Costa, C. A. Petta, R. P. Andrade, et al., "Immunologic responses following administration of a vaccine targeting human papillomavirus types 6, 11, 16, and 18," Vaccine , vol. 24, pp. 5571-5583.
 N. Mu├▒oz N, F. X. Bosch, S. de Sanjosé , R. Herrero, X. Castellsagué , K. V. Shah KV, et al., "Epidemiologic classification of human papillomavirus types associated with cervical cancer," N. Engl. J. Med., vol. 48, pp. 518-27, 2003.
 E. J. Davidson, C. M. Boswell, P. Sehr, M. Pawlita, A. E. Tomlinson , R. J. McVey, et al., "Immunological and Clinical Responses in Women with Vulval Intraepithelial Neoplasia Vaccinated with a Vaccinia Virus Encoding Human Papillomavirus 16/18 Oncoproteins," Cancer Research, vol. 63, pp. 6032-6041, 2003.
 Z. Meshkat, H. Soleimanjahi, Z. M. Hassan, H. Mirshahabi, M. Meshkat, and M. Kheirandish, "CTL Responses to a DNA Vaccine Encoding E7 Gene of Human Papillomavirus Type 16 from an Iranian Isolate," Iran J Immunol, vol. 5, pp. 82-91, 2008.
 29-A. Teimoori, H. Soleimanjahi, F. Fotouhi, and Z. Meshkat, "Isolation and cloning of human papillomavirus 16 L1 gene from Iranian isolate," Saudi Med J., vol. 29, pp. 1105-1108, 2008 .