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Advances in Sustainable and Environmental Hydrology, Hydrogeology, Hydrochemistry and Water Resources : Proceedings of the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Tunisia 2018 / / edited by Helder I. Chaminé, Maurizio Barbieri, Ozgur Kisi, Mingjie Chen, Broder J. Merkel
| Advances in Sustainable and Environmental Hydrology, Hydrogeology, Hydrochemistry and Water Resources : Proceedings of the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Tunisia 2018 / / edited by Helder I. Chaminé, Maurizio Barbieri, Ozgur Kisi, Mingjie Chen, Broder J. Merkel |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (416 pages) |
| Disciplina | 363.6 |
| Collana | Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development |
| Soggetto topico |
Earth sciences
Water Hydrology Environment Earth Sciences Environmental Sciences |
| ISBN | 3-030-01572-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Hydrology, Climatology and Water-Related Ecosystems -- Hydrochemistry Quality and Isotopic Hydrology -- Groundwater Assessment, Management, and Modelling -- Water Resources Sustainability and Climate Change -- Hydrologic Engineering and Urban Groundwater. |
| Record Nr. | UNINA-9910337922303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation : Theory and Practice of Hazard Mitigation / / edited by Ravinesh C. Deo, Pijush Samui, Ozgur Kisi, Zaher Mundher Yaseen
| Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation : Theory and Practice of Hazard Mitigation / / edited by Ravinesh C. Deo, Pijush Samui, Ozgur Kisi, Zaher Mundher Yaseen |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (477 pages) : illustrations |
| Disciplina | 346.73046917 |
| Collana | Springer Transactions in Civil and Environmental Engineering |
| Soggetto topico |
Computational intelligence
Fire prevention Environmental sciences Machine learning Hydrology Big data Computational Intelligence Fire Science, Hazard Control, Building Safety Environmental Science and Engineering Machine Learning Hydrology/Water Resources Big Data |
| ISBN | 981-15-5772-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1: Drought Index Prediction using Data Intelligent Analytic Models: A Review -- Chapter 2: Bayesian Markov Chain Monte Carlo based copulas: Factoring the Role of Large-scale Climate Indices in Monthly Flood Prediction -- Chapter 3: Gaussian Naive Bayes Classification Algorithm for Drought and Flood Risk Reduction -- Chapter 4: Hydrological Drought Investigation using Streamflow Drought Index -- Chapter 5: Intelligent Data Analytics Approaches for Predicting Dissolved Oxygen Concentration in River: Extremely Randomized Tree Vs Random Forest, MLPNN and MLR -- Chapter 6: Evolving Connectionist Systems versus Neuro-Fuzzy System for Estimating Total Dissolved Gas at Forebay and Tailwater of Dams Reservoirs -- Chapter 7: Modulation of Tropical Cyclone Genesis by Madden-Julian Oscillation in the Southern Hemisphere -- Chapter 8: Intelligent Data Analytics for Time-series, Trend Analysis and Drought Indices Comparison -- Chapter 9: Conjunction Model Design for Intermittent Streamflow Forecasts: Extreme Learning Machine with Discrete Wavelet Transform -- Chapter 10: Systematic Integration of Artificial Intelligence Towards Evaluating Response of Materials and Structures in Extreme Conditions. . |
| Record Nr. | UNINA-9910483360203321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management
| Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management |
| Autore | Kisi Ozgur |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (238 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
groundwater
artificial intelligence hydrologic model groundwater level prediction machine learning principal component analysis spatiotemporal variation uncertainty analysis hydroinformatics support vector machine big data artificial neural network nitrogen compound nitrogen prediction prediction models neural network non-linear modeling PACF WANN SVM-LF SVM-RF Govindpur streamflow forecasting Bayesian model averaging multivariate adaptive regression spline M5 model tree Kernel extreme learning machines South Korea uncertainty sustainability prediction intervals ungauged basin streamflow simulation satellite precipitation atmospheric reanalysis ensemble modeling additive regression bagging dagging random subspace rotation forest flood routing Muskingum method extension principle calibration fuzzy sets and systems particle swarm optimization EEFlux irrigation performance CWP water conservation NDVI water resources Daymet V3 Google Earth Engine improved extreme learning machine (IELM) sensitivity analysis shortwave radiation flux density sustainable development |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557448103321 |
Kisi Ozgur
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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