Items where Subject is "C45 - Neural Networks and Related Topics"

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ANDREOU, A. S. and PARSOPOULOS, K. E. and VRACHATIS, M. N. and Zombanakis, George A. (2002): Searching for the Optimal Defence Expenditure: An Answer in the Context of the Greek – Turkish Arms Race. Published in: Financial Engineering, E- Commerce and Supply Chain , Vol. 1, No. 1 (14 September 2002): pp. 1-24.

Abounoori, Abbas Ali and Mohammadali, Hanieh and Gandali Alikhani, Nadiya and Naderi, Esmaeil (2012): Comparative study of static and dynamic neural network models for nonlinear time series forecasting.

Abounoori, Abbas Ali and Naderi, Esmaeil and Gandali Alikhani, Nadiya and Amiri, Ashkan (2013): Financial Time Series Forecasting by Developing a Hybrid Intelligent System. Published in: European Journal of Scientific Research , Vol. 98, No. 4 (4 March 2013): pp. 10-20.

Abounoori, Abbas Ali and Naderi, Esmaeil and Gandali Alikhani, Nadiya and Amiri, Ashkan (2013): Financial Time Series Forecasting by Developing a Hybrid Intelligent System. Published in: European Journal of Scientific Research , Vol. 98, No. 4 (4 March 2013): pp. 529-541.

Amavilah, Voxi Heinrich and Otero, Abraham and Andres, Antonio Rodriguez (2021): Knowledge Economy Classification in African Countries: A Model-Based Clustering Approach. Published in: Information Technology for Development No. DOI: 10.1080/02681102.2021.1950597 (16 July 2021)

Andreou, Andreas S. and Zombanakis, George A. (2000): Financial Versus Human Resources in the Greek-Turkish Arms Race: A Forecasting Investigation Using Artificial Neural Networks. Published in: Defence and Peace Economics , Vol. 11, No. 4 (2000): pp. 403-426.

Andreou, Andreas S. and Zombanakis, George A. (2010): Financial vs human resources in the Greek-Turkish arms race 10 years on. Published in: Defence and Peace Economics , Vol. Vol. 2, No. No. 4, 2011 : pp. 1-11.

Andreou, Andreas S. and Zombanakis, George A. (2003): Intelligent information systems for defence problems. Published in: (14 July 2003): pp. 1-163.

Andreou, Andreas S. and Zombanakis, George A. (2001): A Neural Network Measurement of Relative Military Security: The Case of Greece and Cyprus. Published in: Defence and Peace Economics , Vol. 12, No. 4 (2001): pp. 303-324.

Andreou, Andreas S. and Zombanakis, George A. and Georgopoulos, E. F. and Likothanassis, S. D. (1998): Forecasting Exchange-Rates via Local Approximation Methods and Neural Networks. Published in: European Research Studies , Vol. 1, No. 4 (December 1998): pp. 5-33.

Andreou, Andreas S. and Zombanakis, George A. and Georgopoulos, E. F. and Likothanassis, S. D. (2000): In Search of a Warning Strategy Against Exchange-rate Attacks: Forecasting Tactics Using Artificial Neural Networks. Published in: Discrete Dynamics in Nature and Society , Vol. 5, No. 2 : pp. 121-137.

Andres, Antonio Rodriguez and Otero, Abraham and Amavilah, Voxi Heinrich (2021): Evaluation of technology clubs by clustering: A cautionary note. Forthcoming in: Applied Economics (2021)

Andres, Antonio Rodriguez and Otero, Abraham and Amavilah, Voxi Heinrich (2021): Using Deep Learning Neural Networks to Predict the Knowledge Economy Index for Developing and Emerging Economies. Published in: Expert Systems with Applications , Vol. 184, No. https://doi.org/10.1016/j.eswa.2021.115514 (1 December 2021)

Antipov, Evgeny and Pokryshevskaya, Elena (2010): Applying a CART-based approach for the diagnostics of mass appraisal models.

Antipov, Evgeny and Pokryshevskaya, Elena (2010): Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics.

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Basihos, Seda (2016): Nightlights as a Development Indicator: The Estimation of Gross Provincial Product (GPP) in Turkey.

Benkovich, Nikita and Dedenok, Roman and Golubev, Dmitry (2019): Deep Quarantine for Suspicious Mail. Published in: CEUR Workshop Proceedings , Vol. 2479, (26 September 2019): pp. 68-76.

Bildirici, Melike and Ersin, Özgür (2012): Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models.

Brummelhuis, Raymond and Luo, Zhongmin (2018): Arbitrage Opportunities in CDS Term Structure: Theory and Implications for OTC Derivatives.

Brummelhuis, Raymond and Luo, Zhongmin (2019): Bank Net Interest Margin Forecasting and Capital Adequacy Stress Testing by Machine Learning Techniques.

Brummelhuis, Raymond and Luo, Zhongmin (2017): CDS Rate Construction Methods by Machine Learning Techniques.

Bucci, Andrea (2019): Cholesky-ANN models for predicting multivariate realized volatility.

Bucci, Andrea (2019): Realized Volatility Forecasting with Neural Networks.

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Cakir, Murat (2005): Firma Başarısızlığının Dinamiklerinin Belirlenmesinde Makina Öğrenmesi Teknikleri: Ampirik Uygulamalar ve Karşılaştırmalı Analiz.

Chan, Tze-Haw and Lye, Chun Teck and Hooy, Chee-Wooi (2010): Forecasting Malaysian Exchange Rate: Do Artificial Neural Networks Work?

Chen, Ying and Grith, Maria and Lai, Hannah L. H. (2023): Neural Tangent Kernel in Implied Volatility Forecasting: A Nonlinear Functional Autoregression Approach.

Cifter, Atilla and Ozun, Alper (2007): The Effects of International F/X Markets on Domestic Currencies Using Wavelet Networks: Evidence from Emerging Markets.

Cifter, Atilla and Ozun, Alper (2007): Estimating the Effects of Interest Rates on Share Prices Using Multi-scale Causality Test in Emerging Markets: Evidence from Turkey.

Ciuiu, Daniel (2008): Pattern classification using polynomial and linear regression. Published in: Proceedings of International Conference Trends and Challenges in Applied Mathematics (2008): pp. 153-156.

Ciuiu, Daniel (2008): Pattern classification using principal components regression. Published in: Proceedings of International Conference Trends and Challenges in Applied Mathematics (2008): pp. 149-152.

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Deetz, Marcus and Poddig, Thorsten and Varmaz, Armin (2009): Klassifizierung von Hedge-Fonds durch das k-means Clustering von Self-Organizing Maps: eine renditebasierte Analyse zur Selbsteinstufungsgüte und Stiländerungsproblematik.

Delavari, Majid and Gandali Alikhani, Nadiya and Naderi, Esmaeil (2012): Do Dynamic Neural Networks Stand a Better Chance in Fractionally Integrated Process Forecasting? Published in: International Journal of Economics and Financial Issues , Vol. 3, No. 2 (10 April 2013): pp. 447-465.

Dev, Pritha (2010): Identity and Fragmentation in Networks.

Diunugala, Hemantha Premakumara and Mombeuil, Claudel (2020): Modeling and predicting foreign tourist arrivals to Sri Lanka: A comparison of three different methods. Published in: Journal of Tourism, Heritage & Services Marketing , Vol. 6, No. 3 (30 October 2020): pp. 3-13.

Djennas, Meriem and Benbouziane, Mohamed and Djennas, Mustapha (2012): Agent-Based Modeling in Supply Chain Management:A Genetic Algorithm and Fuzzy Logic Approach. Published in: International Journal of Artificial Intelligence & Applications (IJAIA) , Vol. Vol.3,, No. No.5 (September 2012): pp. 13-30.

de Rigo, Daniele (2013): Software uncertainty in integrated environmental modelling: the role of semantics and open science. Forthcoming in: Geophysical Research Abstracts , Vol. 15, (2013)

de Rigo, Daniele (2013): Software uncertainty in integrated environmental modelling: the role of semantics and open science. Forthcoming in: Geophysical Research Abstracts , Vol. 15, (2013)

de Rigo, Daniele and Caudullo, Giovanni and San-Miguel-Ayanz, Jesús and Barredo, José I. (2017): Robust modelling of the impacts of climate change on the habitat suitability of forest tree species. Published in: (March 2017)

de Rigo, Daniele and Corti, Paolo and Caudullo, Giovanni and McInerney, Daniel and Di Leo, Margherita and San-Miguel-Ayanz, Jesús (2013): Toward open science at the European scale: geospatial semantic array programming for integrated environmental modelling. Forthcoming in: Geophysical Research Abstracts , Vol. 15, (2013)

de Rigo, Daniele and Rizzoli, Andrea Emilio and Soncini-Sessa, Rodolfo and Weber, Enrico and Zenesi, Pietro (2001): Neuro-dynamic programming for the efficient management of reservoir networks. Published in: Proceedings of MODSIM 2001, International Congress on Modelling and Simulation , Vol. 4, (December 2001): pp. 1949-1954.

di Iasio, Giovanni and Battiston, Stefano and Infante, Luigi and Pierobon, Federico (2013): Capital and Contagion in Financial Networks.

du Jardin, Philippe (2008): Bankruptcy prediction and neural networks: The contribution of variable selection methods. Published in: Proceedings of the Second European Symposium on Time Series Prediction (Estsp 2008), Helsinki University of Technology, Porvoo, Finland, (2008): pp. 271-284.

du Jardin, Philippe (2009): Bankruptcy prediction models: How to choose the most relevant variables? Published in: Bankers, Markets & Investors No. 98 (January 2009): pp. 39-46.

du Jardin, Philippe (2010): Predicting bankruptcy using neural networks and other classification methods: the influence of variable selection techniques on model accuracy. Published in: Neurocomputing , Vol. 73, No. 10-12 (2010): pp. 2047-2060.

du Jardin, Philippe (2012): The influence of variable selection methods on the accuracy of bankruptcy prediction models. Published in: Bankers, Markets & Investors No. 116 (January 2012): pp. 20-39.

du Jardin, Philippe and Séverin, Eric (2010): Dynamic analysis of the business failure process: A study of bankruptcy trajectories. Published in: Proceedings of the 6th Portuguese Finance Network Conference, Ponta Delgada, Azores , Vol. 2010, (1 July 2010)

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Fajar, Muhammad (2019): An application of hybrid forecasting singular spectrum analysis – extreme learning machine method in foreign tourists forecasting. Published in: Jurnal Matematika MANTIK , Vol. 5, No. 2 (31 October 2019): pp. 60-68.

Fajar, Muhammad and Hartini, Sri (2020): Comparison of ARIMA, SSA, and ARIMA – SSA hybrid model performance in Indonesian economic growth forecasting. Published in: The 2020 Asia-Pacific Statistics Week (16 June 2020)

Fajar, Muhammad and Hartini, Sri (2017): Inflation forecasting by hybrid singular spectrum analysis – multilayer perceptrons neural network method, case of Indonesia. Forthcoming in:

Filippou, Miltiades and Zervopoulos, Panagiotis (2011): Developing a hybrid comparative optimization model for short-term forecasting: an ‘idle time interval’ roadmap for operational units’ strategic planning.

Filippou, Miltiades and Zervopoulos, Panagiotis (2011): Developing a short-term comparative optimization forecasting model for operational units’ strategic planning.

Fischer, Manfred M. (1992): Expert Systems and Artificial Neural Networks for Spatial Analysis and Modelling. Essential Components for Knowledge-Based Geographical Information Systems. Published in: Geographical Systems , Vol. 1, No. 3 (1994): pp. 221-235.

Fischer, Manfred M. (2002): Learning in Neural Spatial Interaction Models: A Statistical Perspective. Published in: Journal of Geographical Systems , Vol. 4, No. 3 (2002): pp. 287-299.

Fischer, Manfred M. (2006): Neural Networks. A General Framework for Non-Linear Function Approximation. Published in: Transactions in GIS , Vol. 10, No. 4 (2006)

Fischer, Manfred M. and Gopal, Sucharita (1994): Artificial Neural Networks. A New Approach to Modelling Interregional Telecommunication Flows. Published in: Journal of Regional Science , Vol. 34, No. 4 (1994): pp. 503-527.

Fischer, Manfred M. and Gopal, Sucharita and Staufer, Petra and Steinnocher, Klaus (1995): Evaluation of Neural Pattern Classifiers for a Remote Sensing Application. Published in: Geographical Systems , Vol. 4, No. 2 (1997): pp. 195-226.

Fischer, Manfred M. and Reismann, Martin (2000): Evaluating Neural Spatial Interaction Modelling by Bootstrapping. Published in: Networks and Spatial Economics , Vol. 2, No. 3 (2002): pp. 255-268.

Fischer, Manfred M. and Reismann, Martin (2002): A Methodology for Neural Spatial Interaction Modeling. Published in: Geographical Analysis , Vol. 34, No. 3 (2002): pp. 207-228.

Fischer, Manfred M. and Staufer, Petra (1998): Optimization in an Error Backpropagation Neural Network Environment with a Performance Test on a Pattern Classification Problem. Published in: Geographical Analysis , Vol. 31, No. 3 (1999): pp. 89-108.

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Gawlik, Remigiusz (2014): Application of Artificial Intelligence Methods for Analysis of Material and Non-material Determinants of Functioning of Young Europeans in Times of Crisis in the Eurozone. Published in: Global and Regional Implications of the Euro Area Crisis No. E. Molendowski, P. Stanek (Eds.), Warszawa: PWN (2014): pp. 64-80.

Gawlik, Remigiusz (2013): Material and Non-material Determinants of European Youth's Life Quality. Published in: Globalizing Businesses for the Next Century: Visualizing and Developing Contemporary Approaches to Harness Future Opportunities (22 June 2013): pp. 339-346.

Gawlik, Remigiusz (2016): Methodological Aspects of Qualitative-Quantitative Analysis of Decision-Making Processes. Published in: Management and Production Engineering Review , Vol. 7, No. 2 (June 2016): pp. 3-11.

Gawlik, Remigiusz and Gołębiowski, Kamil (2014): Incorporating Qualitative Indicators of Well - Being into Quantitative Economic Research. Published in: Managing in an Interconnected World: Pioneering Business and Technology Excellence (2014): pp. 673-682.

Gelhausen, Marc Christopher (2007): A Generalized Neural Logit Model for Airport and Access Mode Choice in Germany. Published in: Proceedings of the 11th Air Transport Research Society World Conference (2007): pp. 1-42.

Gelhausen, Marc Christopher and Wilken, Dieter (2006): Airport and Access Mode Choice : A Generalized Nested Logit Model Approach. Published in: Proceedings of the 10th Air Transport Research Society World Conference (2006): pp. 1-30.

Giovanis, Eleftherios (2008): Additional Smoothing Transition Autoregressive Models.

Giovanis, Eleftherios (2008): Applications of Least Mean Square (LMS) Algorithm Regression in Time-Series Analysis.

Giovanis, Eleftherios (2009): Bootstrapping Fuzzy-GARCH Regressions on the Day of the Week Effect in Stock Returns: Applications in MATLAB.

Giovanis, Eleftherios (2008): Neuro-Fuzzy approach for the predictions of economic crisis.

Giovanis, Eleftherios (2008): Smoothing Transition Autoregressive (STAR) Models with Ordinary Least Squares and Genetic Algorithms Optimization.

Giovanis, Eleftherios (2012): Study of Discrete Choice Models and Adaptive Neuro-Fuzzy Inference System in the Prediction of Economic Crisis Periods in USA. Published in: Economic Analysis & Policy , Vol. 42, No. 1 (March 2012): pp. 79-95.

Giovanis, Eleftherios (2008): An algorithm using GARCH process , Monte-Carlo simulation and wavelets analysis for stock prediction.

Giovanis, Eleftherios (2008): A panel data analysis for the greenhouse effects in fifteen countries of European Union.

Giovanis, eleftheios (2008): A Neuro-Fuzzy Approach in the Prediction of Financial Stability and Distress Periods.

Gomez-Ruano, Gerardo (2020): Data Science: A Primer for Economists.

Grilli, Luca and Santoro, Domenico (2020): Generative Adversarial Network for Market Hourly Discrimination.

Grilli, Luca and Santoro, Domenico (2020): How Boltzmann Entropy Improves Prediction with LSTM.

Gutierrez-Lythgoe, Antonio (2023): Autoempleo y Machine Learning: Una aplicación para España.

Gutierrez-Lythgoe, Antonio (2023): Movilidad urbana sostenible: Predicción de demanda con Inteligencia Artificial.

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Hollenbeck, Brett and Taylor, Wayne (2021): Leveraging Loyalty Programs Using Competitor Based Targeting. Published in: Quantitative Marketing and Economics

Hossain, Md. Mobarak and Chowdhury, Md Niaz Murshed (2019): Econometric Ways to Estimate the Age and Price of Abalone.

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Jackwerth, Jens Carsten (1997): Artificial Stupidity: A Reply. Published in: Journal of Portfolio Management , Vol. 27, No. 1 : pp. 120-121.

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K. K., Suresh and K., Pradeepa Veerakumari (2007): Construction and Evaluation of Performance Measures for Bayesian Chain Sampling Plan (BChSP-1). Published in: Acta Ciencia Indica , Vol. 33, No. 4 (2007): pp. 16-35.

Kadyrov, Timur and Ignatov, Dmitry I. (2019): Attribution of Customers’ Actions Based on Machine Learning Approach. Published in: CEUR Workshop Proceedings , Vol. 2479, (26 September 2019): pp. 77-88.

Kahloul, Ines and Ben Mabrouk, Anouar and Hallara, Salah-Eddine (2009): Wavelet-Based Prediction for Governance, Diversi cation and Value Creation Variables.

Kaizoji, Taisei (2012): A Note on Stability of Self-Consistent Equilibrium in an Asynchronous Model of Discrete-Choice with Social Interaction.

Katsafados, Apostolos G. and Leledakis, George N. and Pyrgiotakis, Emmanouil G. and Androutsopoulos, Ion and Fergadiotis, Manos (2021): Machine Learning in U.S. Bank Merger Prediction: A Text-Based Approach.

Kitova, Olga and Dyakonova, Ludmila and Savinova, Victoria and Fomin, Kiril (2023): Forecasting the main economic indicators for industry in the analytical system "Horizon".

Kitova, Olga and Dyakonova, Ludmila and Savinova, Victoria (2020): Prediction of Socio-Economic Indicators of the Megapolis Development on the Basis of the Intellectual Forecasting Information System “SHM Horizon”.

Kitova, Olga and Savinova, Victoria (2021): Development of an Ensemble of Models for Predicting Socio-Economic Indicators of the Russian Federation using IRT-Theory and Bagging Methods.

Klein, Achim and Urbig, Diemo and Kirn, Stefan (2008): Who drives the Market? Estimating a heterogeneous Agent-based Financial Market Model using a Neural Network Approach.

Korobilis, Dimitris and Shimizu, Kenichi (2021): Bayesian Approaches to Shrinkage and Sparse Estimation.

Kulaksizoglu, Tamer (2015): Measuring the Core Inflation in Turkey with the SM-AR Model.

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Leiva-Leon, Danilo (2013): A New Approach to Infer Changes in the Synchronization of Business Cycle Phases.

Leonidas, Spiliopoulos (2009): Learning backward induction: a neural network agent approach. Published in: Agent-Based Approaches in Economic and Social Complex Systems VI, edn. 2011, Springer, Japan (2011)

Liu, Mengxiao and Wang, Luhang and Yi, Yimin (2022): Quality Innovation, Cost Innovation, Export, and Firm Productivity Evolution: Evidence from the Chinese Electronics Industry.

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Malliaris, A.G. and Malliaris, Mary (2011): Are foreign currency markets interdependent? evidence from data mining technologies. Forthcoming in: Stochastics: Finance and Risk No. 2012

Mateou, Nicos H. and Zombanakis, George A. (2009): Fuzzy cognitive maps face the question of the Greek current account deficit sustainability.

Matkovskyy, Roman (2012): Forecasting the Index of Financial Safety (IFS) of South Africa using neural networks.

Matkovskyy, Roman and Bouraoui, Taoufik and Hammami, Helmi (2015): Estimation and prediction of an Index of Financial Safety of Tunisia. Published in: Research in International Business and Finance , Vol. 38, (September 2016): pp. 485-493.

Medel-Ramírez, Carlos and Medel-López, Hilario and Lara-Mérida, Jennifer (2021): (SARS-CoV-2) COVID 19: Vigilancia genómica y evaluación del impacto en la población hablante de lengua indígena en México.

Mengov, George and Egbert, Henrik and Pulov, Stefan and Georgiev, Kalin (2008): Emotional Balances in Experimental Consumer Choice. Published in: Neural Networks , Vol. 21, No. 9 (1 September 2008): pp. 1213-1219.

Mestiri, Sami (2024): Financial applications of machine learning using R software.

Mestiri, Sami (2023): How to use machine learning in finance.

Mishra, SK (2009): The most representative composite rank ordering of multi-attribute objects by the particle swarm optimization.

Mishra, SK (2014): A note on Poincaré recurrence in Anosov diffeomorphic transformation of discretized outline of some plant leaves.

Mishra, Sudhanshu K (2014): What happens if in the principal component analysis the Pearsonian is replaced by the Brownian coefficient of correlation?

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Nazarian, Rafik and Gandali Alikhani, Nadiya and Naderi, Esmaeil and Amiri, Ashkan (2013): Forecasting Stock Market Volatility: A Forecast Combination Approach.

Nguefack-Tsague, Georges and Zucchini, Walter (2011): Modeling hierarchical relationships in epidemiological studies: a Bayesian networks approach.

Nowotarski, Jakub and Tomczyk, Jakub and Weron, Rafal (2012): Robust estimation and forecasting of the long-term seasonal component of electricity spot prices.

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Oancea, Bogdan and Dragoescu, Raluca and Ciucu, Stefan (2013): Predicting students’ results in higher education using a neural network. Published in: International Conference on Applied Information and Communication Technologies (AICT2013 ) (April 2013): pp. 190-193.

Osipov, Vasiliy and Zhukova, Nataly and Miloserdov, Dmitriy (2019): Neural Network Associative Forecasting of Demand for Goods. Published in: CEUR Workshop Proceedings , Vol. 2479, (26 September 2019): pp. 100-108.

Ozun, Alper and Cifter, Atilla (2007): Modeling Long-Term Memory Effect in Stock Prices: A Comparative Analysis with GPH Test and Daubechies Wavelets.

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Pena Centeno, Tonatiuh and Martinez Jaramillo, Serafin and Abudu, Bolanle (2009): Predicción de bancarrota: Una comparación de técnicas estadísticas y de aprendizaje supervisado para computadora.

Pereira, Robert (1999): Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-optimised Technical Trading Rules.

Pereira, Robert (2000): Genetic Algorithm Optimisation for Finance and Investments.

Photis, Yorgos N. and Grekoussis, George (2003): Assesing demand in stochastic locational planning problems: An Artificial Intelligence approach for emergency service systems. Published in: Conference Proceedings of the 2005 Conference on Computers in Urban Planning and Urban Management (CUPUM 05) , Vol. 373, No. 05 (2003): pp. 1-16.

Photis, Yorgos N. and Manetos, Panos and Grekoussis, George (2003): Modeling urban evolution by identifying spatiotemporal patterns and applying methods of artificial intelligence.Case study: Athens, Greece. Published in: Proceedings of the 3rd Euroconference: The European City in Transition , Vol. 1, No. 1 (29 November 2003): pp. 96-108.

Pugalendhi, Subburethina Bharathi and Nakkeeran, Senthil kumar (2011): Mind mapping management. Published in: The observer of Management Education , Vol. Volume, No. Issue 9 (1 September 2011): pp. 10-13.

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Saltoglu, Burak and Yenilmez, Taylan (2010): Analyzing Systemic Risk with Financial Networks An Application During a Financial Crash.

Spiliopoulos, Leonidas (2009): Neural networks as a learning paradigm for general normal form games.

Su, EnDer and Fen, Yu-Gin (2011): Applying the structural equation model rule-based fuzzy system with genetic algorithm for trading in currency market.

Sumi, P. Sobana and Delhibabu, Radhakrishnan (2019): Glioblastoma Multiforme Classification On High Resolution Histology Image Using Deep Spatial Fusion Network. Published in: CEUR Workshop Proceedings , Vol. 2479, (26 September 2019): pp. 109-120.

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Temel, Tugrul and Phumpiu, Paul (2023): Policy Design from a Network Perspective: Targeting a Sector, Cascade of Links, Network Resilience.

Temel, Tugrul and Phumpiu, Paul (2023): Policy Design from a Network Perspective: Targeting a Sector, Cascade of Links, Network Resilience.

Tsionas, Efthymios G. and Michaelides, Panayotis G. and Vouldis, Angelos (2008): Neural Networks for Approximating the Cost and Production Functions.

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Wilken, Dieter and Berster, Peter and Gelhausen, Marc Christopher (2005): Airport Choice in Germany - New Empirical Evidence of the German Air Traveller Survey 2003. Published in: Proceedings of the 9th Air Transport Research Society World Congress (2005): pp. 1-29.

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Yang, Bill Huajian (2022): Modeling Path-Dependent State Transition by a Recurrent Neural Network. Forthcoming in: Big Data and Information Analytics

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Zolnikov, Pavel and Zubov, Maxim and Nikitinsky, Nikita and Makarov, Ilya (2019): Efficient Algorithms for Constructing Multiplex Networks Embedding. Published in: CEUR Workshop Proceedings , Vol. 2479, (26 September 2019): pp. 57-67.

Zombanakis, George A. and Andreou, Andreas A. (2010): Financial versus human Resources in the Greek - Turkish Arms Race 10 Years on: A forecasting Investigation using Artificial Neural Networks. Published in: Defence and Peace Economics , Vol. 22, No. 4 : pp. 1-11.