Engineering optimisation by heterogeneous cuckoo search algorithm: Application to an irrigation station

摘要

Data-driven design of accurate Takagi-Sugeno (TS) fuzzy models has attracted the attention of many researchers in the last decade, where the model structures and parameters are important and often solved in an optimization problems. The Cuckoo Search (CS) method represents a powerful search approach and an effective optimization technique. However, the classical CS algorithm is not always optimal to find the potential solution to a special problem, and it can be trap the individuals into local regions leading to premature convergence which will significantly affect the model accuracy. To overcome these drawbacks, we have presented a powerful TS fuzzy system parameters searching strategy named intelligent Takagi-Sugeno Modeling (iTaSuM), with heterogeneous cuckoo search (HeCoS) strategies based on the quantum mechanism to enhance the searching performance. Finally, the searching strategy (iTaSuM) applied to an irrigation station process in order to get an optimal T-S fuzzy model.