Handbook of Computer Vision Algorithms in Image Algebra
Handbook of Computer Vision Algorithms in Image Algebra
Fuzzy Relational Systems: Foundations and Principles
Fuzzy Relational Systems: Foundations and Principles
Towards a Unified Modeling and Knowledge-Representation based on Lattice Theory: Computational Intelligence and Soft Computing Applications (Studies in Computational Intelligence)
Information Sciences: an International Journal
Handbook of Granular Computing
Handbook of Granular Computing
Information Sciences: an International Journal
Designing fuzzy inference systems from data: An interpretability-oriented review
IEEE Transactions on Fuzzy Systems
2-D shape representation and recognition by lattice computing techniques
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
| Hi-index | 0.00 |
Information granules are partially/lattice-ordered Therefore, lattice computing (LC) is proposed for dealing with them The granules here are Intervals' Numbers (INs), which can represent real numbers, intervals, fuzzy numbers, probability distributions, and logic values Based on two novel theoretical propositions introduced here, it is demonstrated how LC may enhance popular fuzzy inference system (FIS) design by the rigorous fusion of granular input data, the sensible employment of sparse rules, and the introduction of tunable nonlinearities.