Joe Lorkowski
According to our database1,
Joe Lorkowski
authored at least 12 papers
between 1996 and 2016.
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Bibliography
2016
Proceedings of the 2016 IEEE International Conference on Systems, Man, and Cybernetics, 2016
2015
How Design Quality Improves with Increasing Computational Abilities: General Formulas and Case Study of Aircraft Fuel Efficiency.
J. Adv. Comput. Intell. Intell. Informatics, 2015
In Engineering Classes, How to Assign Partial Credit: From Current Subjective Practice to Exact Formulas (Based on Computational Intelligence Ideas).
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015
Proceedings of the 2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC), 2015
Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015
How to take into account a student's degree of certainty when evaluating the test results.
Proceedings of the 2015 IEEE Frontiers in Education Conference, 2015
How success in a task depends on the skills level: two uncertainty-based justifications of a semi-heuristic Rasch model.
Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15), 2015
2014
Fuzzy Logic Ideas Can Help in Explaining Kahneman and Tversky's Empirical Decision Weights.
Proceedings of the Recent Developments and New Direction in Soft-Computing Foundations and Applications, 2014
How Much for an Interval? a Set? a Twin Set? a p-Box? A Kaucher Interval? Towards an Economics-Motivated Approach to Decision Making Under Uncertainty.
Proceedings of the Scientific Computing, Computer Arithmetic, and Validated Numerics, 2014
Towards decision making under interval, set-valued, fuzzy, and Z-number uncertainty: A fair price approach.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2014
2013
Likert-scale fuzzy uncertainty from a traditional decision making viewpoint: It incorporates both subjective probabilities and utility information.
Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting, 2013
1996
If we measure a number, we get an interval. What if we measure a function or an operator?
Reliab. Comput., 1996