Past week
All results
- All results
- Verbatim
4 days ago · [12] devised a simplified nonlinear dynamic model based on mechanism analysis, data scrutiny, and genetic algorithm identification, yielding good fidelity. Hou ...
Missing: Series Forecasting.
7 days ago · This paper focuses on the design of an adaptive fuzzy filter for discrete-time multi-area power systems, considering the presence of sojourn probabilities ...
Missing: Variant Series Forecasting.
5 days ago · Taxonomy: We present a novel taxonomy of deep anomaly detection models for time series data. These models are broadly classified into four categories: ...
4 days ago · This study aimed to overcome this limitation by improving the accuracy of daily air pollution forecasting by analyzing time-series data using ANFIS modeling.
6 days ago · A novel fuzzy real-time adaptive optimizer (FRTAO) is developed based on the proposed real-time traffic condition fuzzy-based model. FRTAO aims to overcome the ...
5 days ago · This work uses a hybrid technique based on deep learning and a fine-tuned BERT model, i.e., Bert-Base, Bert-Large, Bert-LSTM, Bert-GRU, and Bert-CNN presented ...
Missing: Series Forecasting.
2 days ago · This work proposes hybrid adaptive neuro-fuzzy inference system (ANFIS) with the Kalman filter (KF) and a neuro-wavelet (WNN) for tidal current speed, direction ...
7 days ago · Robot skill learning and execution in uncertain and dynamic environments is a challenging task. This paper proposes an adaptive framework that combines Learning ...
Missing: Variant Series Forecasting.
4 days ago · Our results show that the proposed framework produces robust and stable adaptive ... Time series is used to forecast the base motion using historical state ...
Missing: Variant | Show results with:Variant
12 hours ago · This paper aims at conducting a comparative analysis between two control strategies, namely the finite-control-set model predictive control (FCS-MPC) and the ...
Missing: Variant | Show results with:Variant