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Hybrid Iterative and Tree-Based Machine Learning Algorithms for Lake Water Level Forecasting
Accurate forecasting of lake water level (WL) fluctuations is essential for effective development and management of water resource systems. This...
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Forecasting of lake water level based on a hybrid model of innovative gunner algorithm
The increase in water consumption along with climate change makes freshwater more vulnerable to pollution. Conserving the dwindling freshwater...
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Multi-step Lake Urmia water level forecasting using ensemble of bagging based tree models
Lakes play an important role in hydrologic cycle, and water level forecasting can provide vital information for future management of lakes and their...
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Investigation of recent level changes in Lake Van using water balance, LSTM and ANN approaches
Lake Van, the greatest soda water lake in the world located in the east of Turkey, has always attracted the attention of researchers due to its...
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A Hybrid Data-Driven Deep Learning Prediction Framework for Lake Water Level Based on Fusion of Meteorological and Hydrological Multi-source Data
Accurate prediction of lake water level is of great significance for flood prevention, reservoir scheduling, and ecological protection. However, the...
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Prediction of lake water-level fluctuations using adaptive neuro-fuzzy inference system hybridized with metaheuristic optimization algorithms
Lakes help increase the sustainability of the natural environment and decrease food chain risk, agriculture, ecosystem services, and leisure...
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Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods
Global warming and unprecedented human impacts causing environmental degradation are taking place at an alarming rate. As one of the most valuable...
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Development and skill assessment of a real-time hydrologic-hydrodynamic-wave modeling system for Lake Champlain flood forecasting
In response to record-breaking flooding on Lake Champlain in 2011, the International Joint Commission launched a 5-year study to explore solutions to...
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Towards scientific forecasting of magmatic eruptions
Forecasting eruptions is a fundamental goal of volcanology. However, difficulties in identifying eruptive precursors, fragmented approaches and lack...
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Forecasting of Water Level Fluctuations with Periodic Fuzzy Logic Models for Two Shallow Eastern Mediterranean Lakes
In this study, forecasting of monthly water levels is investigated by using three different Adaptive Neuro-Fuzzy Inference Systems (ANFISs), ANFIS...
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Mesoscale Weather Forecasting
The mesoscale weather systems may cause severe weather, so that the forecasting of the mesoscale systems is very important for preventing and...
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Experiment on Long-Term Forecasting of Geomagnetic Activity Based on Nonlocal Correlations
AbstractAn experiment was performed on using advanced macroscopic nonlocal correlations to forecast slow random oscillations of the Dst index of...
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A Hybrid CNN-LSTM Approach for Monthly Reservoir Inflow Forecasting
Reservoir modeling and inflow forecasting has a vital role in water resource management/controlling. Hydrological systems’ complex nature and...
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A comparative study of the surface level changes of Urmia Lake and Aral Lake during the period of 1988 to 2018 using satellite images
Internal lakes are considered as the ecological environments and the monitoring and evaluation of which can be considered as a matter in the national...
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Advanced water level prediction for a large-scale river–lake system using hybrid soft computing approach: a case study in Dongting Lake, China
Water level prediction is vital in develo** a sustainable conceptual design of water infrastructures, providing flood and drought control measures,...
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Drought Forecasting of Seyhan and Ceyhan Basins Using Machine Learning Methods
AbstractA drought is a prolonged natural disaster with numerous economic, social, and environmental consequences; it occurs when the natural water...
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A comparative study of daily streamflow forecasting using firefly, artificial bee colony, and genetic algorithm-based artificial neural network
The management of water resources and the modeling of river flow have a prominent position within environmental research. They form a critical bridge...
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Forecasting Development of Mine Pit Lake Water Surface Levels Based on Time Series Analysis and Neural Networks
Sustainable mine closure is one of the main priorities of the mining industry. This aim of this research was to predict the spatiotemporal...
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Effect of different detrending approaches on the accuracy of time series forecasting models
Investigating the existence of a trend and reaching a static time series is one of the essential issues in modeling the hydrological time series,...
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The Great Salt Lake Water Level is Becoming Less Resilient to Climate Change
Climate change and water diversions are putting the Great Salt Lake (GSL) at risk. Projections indicate a continued decrease in the GSL water surface...
