Project « Research and Development of Technique for The Fuzzy Models Identification Using Derivativebased and Metaheuristics Methods » supported by Grant of Russian Foundation for Basic Research (09-07-99008)

1. The following algorithms for fuzzy systems identification are developed and implemented:

• continuous ant colony algorithm, 
• direct algorithm ant colony, 
• annealing algorithm with two schemes of temperature change, 
• fuzzy clustering algorithms and calculation of indices that characterize the clusters, 
• modified genetic algorithm, 
• parameter identification algorithm using Kalman filter, 
• parameter identification algorithm using gradient method.

2. Efficiency of proposed algorithms is investigated during more than 5000 experiments for observation tables, formed on various mathematical functions and different parameters of the algorithms.