IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v111y2016icp297-304.html

Equationless and equation-based trend models of prohibitively complex technological and related forecasts

Author

Listed:
  • Dohnal, Mirko
  • Doubravsky, Karel

Abstract

PCF (Prohibitively Complex Forecast) models integrate several aspects, e.g. macroeconomic, ecology, sociology, engineering and politics. They are unique, partially subjective, inconsistent, vague and multidimensional. PCFs development suffers from IS (Information Shortage). IS eliminates straightforward application of traditional statistical methods. Oversimplified or highly specific PCFs are sometimes obtained. Artificial Intelligence has developed different tools to solve such problems. Qualitative reasoning is one of them. It is based on the least information intensive quantifiers i.e. trends. There are four different trends i.e. qualitative values and their derivatives: plus/increasing; zero/constant; negative/decreasing; any value/any trend. The paper studies PCF models represented by a set of NODE (nonlinear ordinary differential equations) and models based on EHE (equationless heuristics). An example of EHE is - if GDP is increasing then Research and Development investment is increasing more and more rapidly. Such verbal knowledge item cannot be incorporated into a traditional numerical model and a qualitative model must be used. The following qualitative equation eliminates all positive multiplicative constants A from PCF NODE models: AX=(+)X=X. Numerical values of NODEs constants are therefore qualitatively irrelevant. A solution of a qualitative model is represented by a set of scenarios and a set of time transitions among these scenarios. A qualitative model can be developed under conditions when the relevant quantitative PCF must be heavily simplified. The key information input into PCF EHE model is expert knowledge. A consensus among experts is often not reached because of substantial subjectivity of experts' knowledge. The case study analyses interactions of three technologies using modified predator/prey model. It is based on three NODEs and three EHEs. NODEs have 463 scenarios and EHEs has 79 scenarios. The results are given in details. No a prior knowledge of the qualitative model theory is required.

Suggested Citation

  • Dohnal, Mirko & Doubravsky, Karel, 2016. "Equationless and equation-based trend models of prohibitively complex technological and related forecasts," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 297-304.
    • Handle: RePEc:eee:tefoso:v:111:y:2016:i:c:p:297-304
    DOI: 10.1016/j.techfore.2016.07.031
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162516301883
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2016.07.031?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Mellit, A. & Kalogirou, S.A. & Hontoria, L. & Shaari, S., 2009. "Artificial intelligence techniques for sizing photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 406-419, February.
    2. Cornelis Gardebroek & Manuel A. Hernandez & Miguel Robles, 2016. "Market interdependence and volatility transmission among major crops," Agricultural Economics, International Association of Agricultural Economists, vol. 47(2), pages 141-155, March.
    3. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
    4. Fiordaliso, Antonio, 1998. "A nonlinear forecasts combination method based on Takagi-Sugeno fuzzy systems," International Journal of Forecasting, Elsevier, vol. 14(3), pages 367-379, September.
    5. Wang, Benjamin & Hsieh, Chih-Hung, 2015. "Measuring the value of patents with fuzzy multiple criteria decision making: insight into the practices of the Industrial Technology Research Institute," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 263-275.
    6. Karel Doubravsky & Mirko Dohnal, 2015. "Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-18, July.
    7. Chatterjee, Snehamoy & Sethi, Manas Ranjan & Asad, Mohammad Waqar Ali, 2016. "Production phase and ultimate pit limit design under commodity price uncertainty," European Journal of Operational Research, Elsevier, vol. 248(2), pages 658-667.
    8. Axel Leijonhufvud, 2000. "Macroeconomic Instability and Coordination," Books, Edward Elgar Publishing, number 750, August.
    9. Dohnal, M. & Starzak, M. & Kerkovsky, M. & Dohnalova, J. & Vystrcil, J. & Koivisto, R. & Pokorny, M. & Vanis, M. & Parsons, S., 1993. "A fuzzy upgrading of integrated vague managerial and engineering knowledge," International Journal of Production Economics, Elsevier, vol. 32(2), pages 209-228, September.
    10. Dohnal, M. & Fraser, D. M. & Kerkovsky, M., 1996. "A fuzzy pooling of investment cost knowledge," International Journal of Production Economics, Elsevier, vol. 43(2-3), pages 91-106, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. David Schüller & Karel Doubravský, 2019. "Fuzzy Similarity Used by Micro-Enterprises in Marketing Communication for Sustainable Development," Sustainability, MDPI, vol. 11(19), pages 1-15, September.
    2. Loureiro, Sandra Maria Correia & Guerreiro, João & Tussyadiah, Iis, 2021. "Artificial intelligence in business: State of the art and future research agenda," Journal of Business Research, Elsevier, vol. 129(C), pages 911-926.
    3. Nina Bov{c}kov'a & Karel Doubravsk'y & Barbora Voln'a & Mirko Dohnal, 2025. "Information-Nonintensive Models of Rumour Impacts on Complex Investment Decisions," Papers 2509.00588, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dohnal, Mirko, 2016. "Complex biofuels related scenarios generated by qualitative reasoning under severe information shortages: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 676-684.
    2. D. Colander & H. Follmer & A. Haas & M. Goldberg & K. Juselius & A. Kirman & T. Lux & B. Sloth, 2010. "The Financial Crisis and the Systemic Failure of Academic Economics," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 6.
    3. Ghosh, Soumya Kanti & Nath, Hiranya K., 2023. "What determines private and household savings in India?," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 639-651.
    4. repec:eid:wpaper:4/09 is not listed on IDEAS
    5. Josh Ryan-Collins, 2015. "Is Monetary Financing Inflationary? A Case Study of the Canadian Economy, 1935-75," Economics Working Paper Archive wp_848, Levy Economics Institute.
    6. Tsang, Shu-ki & Ma, Yue, 1997. "Simulating the impact of foreign capital in an open-economy macroeconomic model of China," Economic Modelling, Elsevier, vol. 14(3), pages 435-478, July.
    7. repec:spo:wpmain:info:hdl:2441/2pguj421ms98or9o9plc5q0m62 is not listed on IDEAS
    8. Alvar Kangur, 2016. "What Rules in the ‘Deep’ Determinants of Comparative Development?," Research in Economics and Business: Central and Eastern Europe, Tallinn School of Economics and Business Administration, Tallinn University of Technology, vol. 8(1).
    9. Kevin S. Nell & A.P. Thirlwall, 2017. "Why does the productivity of investment vary across countries?," PSL Quarterly Review, Economia civile, vol. 70(282), pages 213-245.
    10. Karimova, Amira & Simsek, Esra & Orhan, Mehmet, 2020. "Policy implications of the Lucas Critique empirically tested along the global financial crisis," Journal of Policy Modeling, Elsevier, vol. 42(1), pages 153-172.
    11. Ernest Simeon Odior Ph.D & AFOLASHADE ABIBAT SHODEINDE, 2013. "Currency Restructuring Exercise in Nigeria: overview and Potential Implications," International Journal of Business and Social Research, LAR Center Press, vol. 3(6), pages 8-16, June.
    12. Radek DOSKOČIL & Karel DOUBRAVSKÝ, 2017. "Qualitative Evaluation of Knowledge Based Model of Project Time-Cost as Decision Making Support," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(1), pages 263-280.
    13. Tadesse, Tasew, 2011. "Foreign aid and economic growth in Ethiopia," MPRA Paper 33953, University Library of Munich, Germany, revised 20 Sep 2011.
    14. Wang, H.X. & Muñoz-García, M.A. & Moreda, G.P. & Alonso-García, M.C., 2018. "Optimum inverter sizing of grid-connected photovoltaic systems based on energetic and economic considerations," Renewable Energy, Elsevier, vol. 118(C), pages 709-717.
    15. Kapetanios, George & Marcellino, Massimiliano & Papailias, Fotis, 2016. "Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 369-382.
    16. Rómulo Chumacero & Rodrigo Fuentes, 2005. "On the Determinants of Chilean Economic Growth," Central Banking, Analysis, and Economic Policies Book Series, in: Rómulo A. Chumacero & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (S (ed.),General Equilibrium Models for the Chilean Economy, edition 1, volume 9, chapter 5, pages 163-188, Central Bank of Chile.
    17. Peter Warr, 2023. "Productivity in Indonesian agriculture: Impacts of domestic and international research," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(3), pages 835-856, September.
    18. Øyvind Eitrheim & Bjarne Gulbrandsen, 2001. "A model based approach to analysing financial stability," BIS Papers chapters, in: Bank for International Settlements (ed.), Marrying the macro- and micro-prudential dimensions of financial stability, volume 1, pages 311-330, Bank for International Settlements.
    19. Duo QIN & Xinhua HE & Pilipinas QUISING & Shiguo LIU, 2010. "Modeling Monetary Policies in China (PRC)," EcoMod2004 330600115, EcoMod.
    20. Reto Föllmi & Angela Fuest & Philipp an de Meulen & Martin Micheli & Torsten Schmidt & Lina Zwick, 2018. "Openness and productivity of the Swiss economy," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-21, December.
    21. Valpy FitzGerald & Derya Krolzig, 2003. "Modeling the Demand for Emerging Market Assets," OFRC Working Papers Series 2003fe10, Oxford Financial Research Centre.
    22. Mehrabankhomartash, Mahmoud & Rayati, Mohammad & Sheikhi, Aras & Ranjbar, Ali Mohammad, 2017. "Practical battery size optimization of a PV system by considering individual customer damage function," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 36-50.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:111:y:2016:i:c:p:297-304. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.