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Performance Enhancement of MEMS-Based INS/GPS Integration for Low-Cost Navigation Applications
TLDR
A two-tier approach is proposed for improving the stochastic modeling of MEMS-based inertial sensor errors using autoregressive processes at the raw measurement level and enhancing the positioning accuracy during GPS outages by nonlinear modeling of INS position errors at the information fusion level using neuro-fuzzy modules, which are augmented in the Kalman filtering INS/GPS integration.
Reservoir Optimization in Water Resources: a Review
This paper reviews current optimization technique developed to solve reservoir operation problems in water resources. The application of conventional, especially evolutionary computation, combination
Daily Forecasting of Dam Water Levels: Comparing a Support Vector Machine (SVM) Model With Adaptive Neuro Fuzzy Inference System (ANFIS)
TLDR
A new solution to the expert system, using SVM to forecast the daily dam water level of the Klang gate, and all the RMSE, MAE and MAPE values prove that SVM is a superior model to ANFIS.
A Survey on Meta-Heuristic Global Optimization Algorithms
TLDR
In the present study, an attempt is made to review the most popular and well known metaheuristic global optimization algorithms introduced during the past decades.
Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review
TLDR
In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined and recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies.
Performance of artificial neural network and regression techniques for rainfall-runoff prediction
TLDR
The results showed that the feed forward back propagation Neural Network can describe the behaviour of rainfall-runoff relation more accurately than the classical regression model.
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