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Habib Benbouhenni,Zinelaabidine Boudjema,Abdelkader Belaidi
Pág. 17 - 28
In this paper, we propose an advanced control scheme using neural second order sliding mode (NSOSMC) and adaptive neuro-fuzzy inference system space vector modulation (ANFIS-SVM) strategy for a doubly fed induction generator (DFIG) integrated into a wind...
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Hai-Bang Ly, Lu Minh Le, Huan Thanh Duong, Thong Chung Nguyen, Tuan Anh Pham, Tien-Thinh Le, Vuong Minh Le, Long Nguyen-Ngoc and Binh Thai Pham
The main aim of this study is to develop different hybrid artificial intelligence (AI) approaches, such as an adaptive neuro-fuzzy inference system (ANFIS) and two ANFISs optimized by metaheuristic techniques, namely simulated annealing (SA) and biogeogr...
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Yicheng Gong, Zhongjing Wang, Guoyin Xu and Zixiong Zhang
The reliable and accurate prediction of groundwater levels is important to improve water-use efficiency in the development and management of water resources. Three nonlinear time-series intelligence hybrid models were proposed to predict groundwater leve...
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Sowjanya Dhulipala, Ashu S. Kedia, P.S. Salini, B.K. Katti
Pág. 3203 - 3219
The study presents the route choice behaviour among three alternative routes for a set of origin and destination points of Surat, a metropolitan city of India. Travel time, traffic congestion level and environmental effects along the routes are considere...
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Mohammad Zounemat-Kermani and Miklas Scholz
An adaptive neuro-fuzzy inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet works. The ANFIS model was employed to calculate vent air discharge in different gate openings for an em...
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