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Chechurin, L. and Collan, M., (2018), Preface, v-x, in Chechurin, L. and Collan, M., Eds., (2018), Advances in Systematic Creativity – Creating and Managing Innovations, Palgrave McMillan, Cham, Switzerland

Collan, M. and Luukka, P., (2018), Multiple criteria multiple peer-assessment for and eLearning environment using a linguistic scorecard for on-line peer assessment, Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 21 (2),  93-109

Collan, M. and Luukka, P., (2018), Using Innovation Scorecards and Lossless Fuzzy Weighted Averaging in Multiple-criteria Multi-expert Innovation Evaluation, 323-340, in Chechurin, L. and Collan, M., Eds., (2018), Advances in Systematic Creativity – Creating and Managing Innovations, Palgrave McMillan, Cham, Switzerland

Kozlova, M., Collan, M., & Luukka, P. (2018). New investment decision-making tool that combines a fuzzy inference system with real option analysis. Fuzzy Economic Review, 23 (1), 63-92

Kozlova, M., Chechurin, L., and Efimov-Soini, N., (2018), Levelized Function Cost: Economic Consideration for Design Concept Evaluation, 267-298, in Chechurin, L. and Collan, M., Eds., (2018), Advances in Systematic Creativity – Creating and Managing Innovations, Palgrave McMillan, Cham, Switzerland

Kozlova, M., Collan, M., and Luukka, P., (2018), Simulation Decomposition: New Approach For Better Simulation Analysis Of Multi-Variable Investment Projects, Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 21 (2),  3-18

Lohrmann, C., & Luukka, P. (2018). A novel similarity classifier with multiple ideal vectors based on k-means clustering. Decision Support Systems, 111, 27–37.

Lohrmann, C., Luukka, P., Jablonska-Sabuka, M., & Kauranne, T. (2018). Supervised feature selection with a combination of fuzzy similarity measures and fuzzy entropy measures. Expert Systems with Applications, 110, 216–236.

Luukka, P., Collan, M., Tam, F. and Lawryshyn, Y., 2018. Estimating one-off operational risk events with the lossless fuzzy weighted average method. In Soft Computing Applications for Group Decision-making and Consensus Modeling (pp. 227-236). Springer, Cham.

Luukka, P., Stoklasa, J. and Collan, M., 2018. Transformations between the center of gravity and the possibilistic mean for triangular and trapezoidal fuzzy numbers. Soft Computing, pp.1-7.

Morreale, A., Stoklasa, J., and Talášek, T., (2018), Fuzzy Grouping Variables In Economic Analysis. A Pilot Study Of A Verification Of A Normative Model For R&D Alliances, Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), vol. 21 (2), 19-46

Stoklasa, J., Talášek, T. and Luukka, P., 2018. Fuzzified Likert Scales in Group Multiple-Criteria Evaluation. In Soft Computing Applications for Group Decision-making and Consensus Modeling (pp. 165-185). Springer, Cham.

Stoklasa, J., Talasek, T., and Stoklasova, J., (2018), Reflecting Emotional Aspects and Uncertainty in Multi-expert Evaluation: One Step Closer to a Soft Design-Alternative Evaluation Methodology, 299 – 322, in Chechurin, L. and Collan, M., Eds., (2018), Advances in Systematic Creativity – Creating and Managing Innovations, Palgrave McMillan, Cham, Switzerland

 

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