Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Flood Forecasting Using Machine Learning Methods
| Flood Forecasting Using Machine Learning Methods |
| Autore | Chang Fi-John |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (376 p.) |
| Soggetto non controllato |
natural hazards &
artificial neural network flood routing the Three Gorges Dam backtracking search optimization algorithm (BSA) lag analysis artificial intelligence classification and regression trees (CART) decision tree real-time optimization ensemble empirical mode decomposition (EEMD) improved bat algorithm convolutional neural networks ANFIS method of tracking energy differences (MTED) adaptive neuro-fuzzy inference system (ANFIS) recurrent nonlinear autoregressive with exogenous inputs (RNARX) disasters flood prediction ANN-based models flood inundation map ensemble machine learning flood forecast sensitivity hydrologic models phase space reconstruction water level forecast data forward prediction early flood warning systems bees algorithm random forest uncertainty soft computing data science hydrometeorology LSTM rating curve method forecasting superpixel particle swarm optimization high-resolution remote-sensing images machine learning support vector machine Lower Yellow River extreme event management runoff series empirical wavelet transform Muskingum model hydrograph predictions bat algorithm data scarce basins Wilson flood self-organizing map big data extreme learning machine (ELM) hydroinformatics nonlinear Muskingum model invasive weed optimization rainfall–runoff flood forecasting artificial neural networks flash-flood streamflow predictions precipitation-runoff the upper Yangtze River survey parameters Haraz watershed ANN time series prediction postprocessing flood susceptibility modeling rainfall-runoff deep learning database LSTM network ensemble technique hybrid neural network self-organizing map (SOM) data assimilation particle filter algorithm monthly streamflow forecasting Dongting Lake machine learning methods micro-model stopping criteria Google Maps cultural algorithm wolf pack algorithm flood events urban water bodies Karahan flood St. Venant equations hybrid & hydrologic model |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910346688303321 |
Chang Fi-John
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantitative Methods for Economics and Finance
| Quantitative Methods for Economics and Finance |
| Autore | Trinidad-Segovia J.E |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 electronic resource (418 p.) |
| Soggetto topico | Coins, banknotes, medals, seals (numismatics) |
| Soggetto non controllato |
academic cheating
tax evasion informality pairs trading hurst exponent financial markets long memory co-movement cointegration risk delay decision-making process probability discount detection mean square error multicollinearity raise regression variance inflation factor derivation intertemporal choice decreasing impatience elasticity GARCH EGARCH VaR historical simulation approach peaks-over-threshold EVT student t-copula generalized Pareto distribution centered model noncentered model intercept essential multicollinearity nonessential multicollinearity commodity prices futures prices number of factors eigenvalues volatility cluster Hurst exponent FD4 approach volatility series probability of volatility cluster S& P500 Bitcoin Ethereum Ripple bitcoin deep learning deep recurrent convolutional neural networks forecasting asset pricing financial distress prediction unconstrained distributed lag model multiple periods Chinese listed companies cash flow management corporate prudential risk the financial accelerator financial distress induced risk aversion liquidity constraints liquidity risk macroeconomic propagation multiperiod financial management non-linear macroeconomic modelling Tobin’s q precautionary savings pharmaceutical industry scale economies profitability biotechnological firms non-parametric efficiency productivity DEA dispersion trading option arbitrage volatility trading correlation risk premium econometrics computational finance ensemble empirical mode decomposition (EEMD) autoregressive integrated moving average (ARIMA) support vector regression (SVR) genetic algorithm (GA) energy consumption cryptocurrency gold P 500 DCC copula copulas Markov Chain Monte Carlo simulation local optima vs. local minima SRA approach foreign direct investment bilateral investment treaties regional trade agreements structural gravity model policy uncertainty stock prices dynamically simulated autoregressive distributed lag (DYS-ARDL) threshold regression United States |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557564003321 |
|
Trinidad-Segovia J.E
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||