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Fuzzy inference system
Master's thesis of Engineering: Tram track degradation predictionThe broad aim of this research project is to optimize planned and emergency maintenance tasks and timings for tram tracks. Consistent with that broad aim, the following specific objectives are identified: Understand the factors affecting the degradation of tram tracks; develop a degradation prediction model for tracks as a function of the influencing factors; evaluate the time and type of maintenance required for deteriorated rail tracks.
Estimation of the bond strength between FRP and concrete using ANFIS and hybridized ANFIS machine learning modelsAdaptive Neuro-Based Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) algorithms were utilized to produce numerical tools for predicting the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets.
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Optimising torque for three-disc AFPMSM in electric vehicles using BP_ANN and anfis algorithmsThis paper presents a system that combines torque control algorithms based on a back-propagation neural network (BP-ANN) and an Adaptive Neuro-Fuzzy Inference System (ANFIS). The BP-ANN uses a multi-layer structure where the input layer processes factors such as load torque, rotational speed, and stator current, hidden layers model complex nonlinear interactions, and the output layer predicts optimal torque for AFPMSM operation.
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Forecasting Vietnamese stock index: A comparison of hierarchical ANFIS and LSTMForecasting stock index has been received great interest because an accurate prediction of stock index may yield benefits and profits for investors, economists and practitioners. The objective of this study is to develop two efficient forecasting models and compare their performances in one day-ahead forecasting the daily Vietnamese stock index.
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Summary of Computer doctoral thesis: Some extensions of the complex fuzzy inference system for decision support problemResearch objectives of the thesis: Research the theories of complex fuzzy sets, complex fuzzy logic and measures based on complex fuzzy sets; research and development of fuzzy inference system based on complex fuzzy sets; research applied techniques to reduce rules, optimize fuzzy rules in complex fuzzy inference system; research on how to represent rules based on fuzzy knowledge graphs to reduce inference computation time for the test set and deal with the cases where the new dataset is not present in the training data set.
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Giấy phép Mạng Xã Hội số: 670/GP-BTTTT cấp ngày 30/11/2015