2023 - Research.com Computer Science in Australia Leader Award
Holger R. Maier spends much of his time researching Artificial neural network, Data mining, Artificial intelligence, Water resources and Mathematical optimization. Specifically, his work in Artificial neural network is concerned with the study of Backpropagation. His work is dedicated to discovering how Data mining, Operations research are connected with Genetic algorithm, Uncertainty analysis and Decision analysis and other disciplines.
His studies in Artificial intelligence integrate themes in fields like Machine learning and Process. The concepts of his Process study are interwoven with issues in Quality and Relation. Holger R. Maier interconnects Surface runoff, Bayesian probability, Environmental resource management and Flood forecasting in the investigation of issues within Water resources.
His scientific interests lie mostly in Artificial neural network, Artificial intelligence, Mathematical optimization, Data mining and Water resources. Holger R. Maier has researched Artificial neural network in several fields, including Geotechnical engineering, Water quality, Metamodeling, Process and Operations research. His Artificial intelligence study frequently draws parallels with other fields, such as Machine learning.
When carried out as part of a general Mathematical optimization research project, his work on Genetic algorithm, Optimization problem, Evolutionary algorithm and Ant colony optimization algorithms is frequently linked to work in Distribution system, therefore connecting diverse disciplines of study. Holger R. Maier has included themes like Calibration, Mutual information, Feature selection and Robustness in his Data mining study. In his study, Environmental engineering is strongly linked to Multi-objective optimization, which falls under the umbrella field of Water resources.
Holger R. Maier mostly deals with Mathematical optimization, Data mining, Evolutionary algorithm, Water resources and Robustness. Holger R. Maier works mostly in the field of Mathematical optimization, limiting it down to topics relating to Domain knowledge and, in certain cases, Crop, Rate of convergence and Irrigation water. His work in Data mining tackles topics such as Calibration which are related to areas like Selection.
His Evolutionary algorithm study combines topics from a wide range of disciplines, such as Optimization problem, Management science and Metaheuristic. His biological study spans a wide range of topics, including Water quality, Climate change, Meteorology and Environmental economics. His biological study focuses on Artificial neural network.
Holger R. Maier focuses on Mathematical optimization, Water resources, Evolutionary algorithm, Multi-objective optimization and Climate change. His work deals with themes such as Land use, Machine learning, Selection, Artificial intelligence and Process, which intersect with Mathematical optimization. His Water resources study integrates concerns from other disciplines, such as Calibration, Meteorology, Surface runoff and Robustness.
His Evolutionary algorithm study incorporates themes from Optimization problem, Ant colony optimization algorithms, Metaheuristic and Resilience. His Streamflow research focuses on subjects like Flood forecasting, which are linked to Artificial neural network. Many of his research projects under Artificial neural network are closely connected to A priori and a posteriori with A priori and a posteriori, tying the diverse disciplines of science together.
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Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications
Holger R. Maier;Graeme C. Dandy.
Review: Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
Holger R. Maier;Ashu Jain;Graeme C. Dandy;K. P. Sudheer.
The Use of Artificial Neural Networks for the Prediction of Water Quality Parameters
Holger R. Maier;Graeme C. Dandy.
Selecting among five common modelling approaches for integrated environmental assessment and management
Rebecca A. Kelly;Anthony J. Jakeman;Olivier Barreteau;Mark E. Borsuk.
Ant Colony Optimization for Design of Water Distribution Systems
Holger R. Maier;Angus R. Simpson;Aaron C. Zecchin;Wai Kuan Foong.
Input determination for neural network models in water resources applications. Part 1—background and methodology
Gavin J. Bowden;Graeme C. Dandy;Holger R. Maier.
Evolutionary algorithms and other metaheuristics in water resources
H.R. Maier;Z. Kapelan;J. Kasprzyk;J. Kollat.
Future research challenges for incorporation of uncertainty in environmental and ecological decision-making
J. C. Ascough;H. R. Maier;J. K. Ravalico;M. W. Strudley.
Artificial neural network applications in geotechnical engineering
Mohamed A. Shahin;Mark B. Jaksa;Holger R. Maier.
PREDICTING SETTLEMENT OF SHALLOW FOUNDATIONS USING NEURAL NETWORKS
Mohamed A. Shahin;Holger R. Maier;Mark B. Jaksa.
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