Deep learning in environmental remote sensing: Achievements and challenges
Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …
environmental remote sensing research. With an increasing amount of “big data” from earth …
Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates …
Accurate estimation of reference evapotranspiration (ET 0) is of great importance for the
regional water resources planning and irrigation scheduling design. The FAO-56 Penman …
regional water resources planning and irrigation scheduling design. The FAO-56 Penman …
Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms
Evaporation is the primary aspect causing water loss in the hydrological cycle; therefore,
water loss must be precisely measured. Evaporation is an intricate nonlinear process …
water loss must be precisely measured. Evaporation is an intricate nonlinear process …
Daily pan evaporation modeling from local and cross-station data using three tree-based machine learning models
Accurate estimation of pan evaporation (E p) is required for many applications, eg, water
resources management, irrigation system design and hydrological modeling. However, the …
resources management, irrigation system design and hydrological modeling. However, the …
Soil water content and actual evapotranspiration predictions using regression algorithms and remote sensing data
R Filgueiras, TS Almeida, EC Mantovani… - Agricultural Water …, 2020 - Elsevier
The application of technology and the development of data analysis, such as remote
sensing and regression algorithms, are an easy and inexpensive way to estimate …
sensing and regression algorithms, are an easy and inexpensive way to estimate …
[PDF][PDF] Numerical and experimental investigation of meteorological data using adaptive linear M5 model tree for the prediction of rainfall
Real-time predictions are always important for accurate and systematic thinking in planning
future processes. The failure in the availability of current machine learning approaches is a …
future processes. The failure in the availability of current machine learning approaches is a …
Modeling the optimal dosage of coagulants in water treatment plants using various machine learning models
One of the main methods for determining coagulant dosage (CD) is the jar test. However,
this method is expensive, time-consuming, and requires laboratory equipment. In this …
this method is expensive, time-consuming, and requires laboratory equipment. In this …
Estimation of reference evapotranspiration using spatial and temporal machine learning approaches
Evapotranspiration (ET) is widely employed to measure amounts of total water loss between
land and atmosphere due to its major contribution to water balance on both regional and …
land and atmosphere due to its major contribution to water balance on both regional and …
Reference evapotranspiration modeling using new heuristic methods
R Muhammad Adnan, Z Chen, X Yuan, O Kisi… - Entropy, 2020 - mdpi.com
The study investigates the potential of two new machine learning methods, least-square
support vector regression with a gravitational search algorithm (LSSVR-GSA) and the …
support vector regression with a gravitational search algorithm (LSSVR-GSA) and the …
Accessible remote sensing data based reference evapotranspiration estimation modelling
Z Zhang, Y Gong, Z Wang - Agricultural Water Management, 2018 - Elsevier
Estimating reference evapotranspiration (ET 0) is a fundamental requirement of agricultural
water management. The FAO Penman–Monteith (FAO-PM) equation has been used as the …
water management. The FAO Penman–Monteith (FAO-PM) equation has been used as the …