AIMC Topic: Rain

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Interpretable machine learning guided by physical mechanisms reveals drivers of runoff under dynamic land use changes.

Journal of environmental management Jul 26, 2024
Human activities continuously impact water balances and cycling in watersheds, making it essential to accurately identify the responses of runoff to dynamic changes in land use types. Although machine learning models demonstrate promise in capturing ...
Hydrology Agriculture Humans Models, Theoretical Machine Learning Rivers Environmental Monitoring Rain
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Designing energy-efficient buildings in urban centers through machine learning and enhanced clean water managements.

Environmental research Jul 5, 2024
Rainwater Harvesting (RWH) is increasingly recognized as a vital sustainable practice in urban environments, aimed at enhancing water conservation and reducing energy consumption. This study introduces an innovative integration of nano-composite mate...
Water Purification Cities Machine Learning Silver Rain Conservation of Water Resources Support Vector Machine Metal Nanoparticles
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Machine learning ensembles, neural network, hybrid and sparse regression approaches for weather based rainfed cotton yield forecast.

International journal of biometeorology Apr 27, 2024
Cotton is a major economic crop predominantly cultivated under rainfed situations. The accurate prediction of cotton yield invariably helps farmers, industries, and policy makers. The final cotton yield is mostly determined by the weather patterns th...
Neural Networks, Computer Models, Theoretical Regression Analysis Weather Machine Learning Forecasting Gossypium Rain
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Use of one-dimensional CNN for input data size reduction in LSTM for improved computational efficiency and accuracy in hourly rainfall-runoff modeling.

Journal of environmental management Apr 27, 2024
A deep learning architecture, denoted as CNNsLSTM, is proposed for hourly rainfall-runoff modeling in this study. The architecture involves a serial coupling of the one-dimensional convolutional neural network (1D-CNN) and the long short-term memory ...
Japan Rain Hydrology Deep Learning Models, Theoretical Neural Networks, Computer
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Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Water science and technology : a journal of the International Association on Water Pollution Research Apr 9, 2024
Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer ...
Water Movements Sewage Rain Machine Learning Models, Theoretical
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Integrating conceptual and machine learning models to enhance daily-Scale streamflow simulation and assessing climate change impact in the watersheds of the Godavari basin, India.

Environmental research Feb 14, 2024
This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Departm...
Hydrology Environmental Monitoring Rivers Rain Water Movements Climate Change India Models, Theoretical Machine Learning Temperature
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Anthropogenic fingerprints in daily precipitation revealed by deep learning.

Nature Aug 30, 2023
According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe. However, verifying this prediction using observations has remained a substantial challenge owing to lar...
Neural Networks, Computer Rain Temperature Global Warming Tropical Climate Hydrology Deep Learning Pacific Ocean Climate Models Human Activities Weather
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A new rainfall prediction model based on ICEEMDAN-WSD-BiLSTM and ESN.

Environmental science and pollution research international Mar 1, 2023
Precipitation, as an important indicator describing the evolution of the regional climate system, plays an important role in understanding the spatial and temporal distribution characteristics of regional precipitation. Scientific and accurate predic...
Weather Climate Neural Networks, Computer Forecasting Rain Floods Droughts
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Imputation of missing monthly rainfall data using machine learning and spatial interpolation approaches in Thale Sap Songkhla River Basin, Thailand.

Environmental science and pollution research international Sep 29, 2022
Missing rainfall data has been a prevalent issue and primarily interested in hydrology and meteorology. This research aimed to examine the capability of machine learning (ML) and spatial interpolation (SI) methods to estimate missing monthly rainfall...
Algorithms Thailand Machine Learning Environmental Monitoring Rivers Rain
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Progressive Rain Removal Based on the Combination Network of CNN and Transformer.

Computational intelligence and neuroscience Sep 24, 2022
The rain removal method based on CNN develops rapidly. However, convolution operation has the disadvantages of limited receptive field and inadaptability to the input content. Recently, another neural network structure Transformer has shown excellent...
Rain Neural Networks, Computer Natural Language Processing
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