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Performance Enhancement of MEMS-Based INS/GPS Integration for Low-Cost Navigation Applications
TLDR
The relatively high cost of inertial navigation systems (INSs) has been preventing their integration with global positioning systems (GPSs) for land-vehicle applications. Expand
GPS/INS integration utilizing dynamic neural networks for vehicular navigation
TLDR
This study, therefore, suggests the use of Input-Delayed Neural Networks (IDNN) to model both the INS position and velocity errors based on current and some past samples of INS position. Expand
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, combinationExpand
A Survey on Meta-Heuristic Global Optimization Algorithms
TLDR
Metaheuristic global optimization algorithms have become a popular choice for solving complex and intricate problems. Expand
Performance of artificial neural network and regression techniques for rainfall-runoff prediction
TLDR
We use an Artificial Neural Network (ANN) to predict the rainfall-runoff relationship in a catchment area located in a Tanakami region of Japan. Expand
A modified gravitational search algorithm for slope stability analysis
TLDR
This paper first proposes an effective modification for the gravitational search algorithm. Expand
Daily Forecasting of Dam Water Levels: Comparing a Support Vector Machine (SVM) Model With Adaptive Neuro Fuzzy Inference System (ANFIS)
Reservoir planning and management are critical to the development of the hydrological field and necessary to Integrated Water Resources Management. The growth of forecasting models has resulted in anExpand
Artificial intelligence based models for stream-flow forecasting: 2000-2015
TLDR
This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream- flow. Expand
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Abstract Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of waterExpand
Water quality prediction model utilizing integrated wavelet-ANFIS model with cross-validation
TLDR
This paper discusses the accuracy performance of training, validation and prediction of monthly water quality parameters utilizing Adaptive Neuro-Fuzzy Inference System (ANFIS) based on the data fusion module for WQP. Expand
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