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Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques

This book describes the use of machine learning techniques to build predictive models of uncertainty with application to hydrological;

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Uncertainty Analysis in Rainfall-Runoff Modelling - Application of Machine Learning Techniques

This book describes the use of machine learning techniques to build predictive models of uncertainty with application to hydrological;

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Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling

Use of Meta-Heuristic Techniques in Rainfall-Runoff Modelling is een boek van Mdpi Ag;

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Distributed Rainfall Runoff Modeling Using Wms and Hec-HMS

The rainfall runoff model is one of the most frequently used events in hydrology. It determines the runoff signal which leaves the;

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GIS based HEC-HMS and HEC-RAS modeling

rainfall and runoff processes is necessary.GIS based model systems are increasingly becoming popular tools due to its capability to handle the;

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Watershed Management and Applications of AI

, soil conservation, rainfall-runoff processes, and groundwater hydrology. Watershed Management and Applications of AI provides the necessary;

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Integrated Uncertainty in Knowledge Modelling and Decision Making

and decision support; econometrics; machine learning; machine learning applications; and statistical methods.;

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Integrated Uncertainty in Knowledge Modelling and Decision Making

uncertainty management and decision support; machine learning; machine learning applications; econometric applications; and statistical methods;

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis

This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning;

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Rainfall-Runoff Relationship in a Local Small Watershed Area

. Overall about 9 MAF net rainfall's volume is estimated to reach the irrigation system annually. The rainfall zones, where runoff data is not;

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning;

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Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

MLUE (Machine Learning for Uncertainty Estimation) approach is further explored and extended; in it the machine learning techniques (e.g;

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Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

MLUE (Machine Learning for Uncertainty Estimation) approach is further explored and extended; in it the machine learning techniques (e.g;

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Rainfall

, simulation and disaggregation, ensemble approach for radar rainfall uncertainty, and uncertainty analysis of satellite rainfall products

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Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

promising machine learning techniques for biomedical signals analysis. Provides comprehensive knowledge in the application of machine;

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Computational Methods For Reliability And Risk Analysis

and risk analysis, like dependent failures and importance measures; and iv) a presentation of the issue of uncertainty and of the techniques;

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Surface Runoff and Soil Loss Under Varying Rainfall Intensity

deposits so much sediments into Lake Nakuru. The study investigated the effect of rainfall intensity on soil erosion and surface runoff on;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems

, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems

, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems

, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine;

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Fuzzy Hybrid Computing in Construction Engineering and Management

practical application of these techniques to solve real-world problems across a wide range of construction engineering and management issues is also;

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Foundations of Data Science

algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including;

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Hydroinformatics

(rainfall-runoff). Some common modelling techniques are mentioned, and applied examples clarifies some cases. In chapter 7 the modelling of dams;

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Machine Learning and Medical Imaging

undergraduate and graduate students, and clinicians. Demonstrates the application of cutting-edge machine learning techniques to medical;

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Practical Machine Learning for Data Analysis Using Python

learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to;

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Modeling Methods and Practices in Soil and Water Engineering

methods, including groundwater recharge estimation, rainfall-runoff modeling using artificial neural networks, development and application of a;

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Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations

; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe;

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