Nothing Special   »   [go: up one dir, main page]

Singh et al., 2022 - Google Patents

Artificial intelligence and machine learning in earth system sciences with special reference to climate science and meteorology in South Asia.

Singh et al., 2022

View PDF
Document ID
11958952646468420051
Author
Singh M
Kumar B
Chattopadhyay R
Amarjyothi K
Sutar A
Roy S
Rao S
Nanjundiah R
Publication year
Publication venue
Current Science (00113891)

External Links

Snippet

This study focuses on the current problems in earth system science (ESS), where machine learning (ML) algorithms can be applied. It provides an overview of previous studies, ongoing work at the Ministry of Earth Sciences, Government of India, and future applications …
Continue reading at scholar.archive.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30241—Information retrieval; Database structures therefor; File system structures therefor in geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01W—METEOROLOGY
    • G01W1/00—Meteorology
    • G01W1/10—Devices for predicting weather conditions
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01W—METEOROLOGY
    • G01W1/00—Meteorology
    • G01W1/08—Adaptations of balloons, missiles, or aircraft for meteorological purposes; Radiosondes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V9/00—Prospecting or detecting by methods not provided for in groups G01V1/00 - G01V8/00
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V99/00—Subject matter not provided for in other groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G01S13/90—Radar or analogous systems specially adapted for specific applications for mapping or imaging using synthetic aperture techniques, e.g. correcting range migration errors
    • G01S13/9035—Particular SAR processing techniques not provided for elsewhere, e.g. squint mode, doppler beam-sharpening mode, spotlight mode, bistatic SAR, inverse SAR
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing

Similar Documents

Publication Publication Date Title
Sinha et al. Assessing the spatial sensitivity of a random forest model: Application in gridded population modeling
Bihlo A generative adversarial network approach to (ensemble) weather prediction
Steger et al. The influence of systematically incomplete shallow landslide inventories on statistical susceptibility models and suggestions for improvements
Zhang et al. Estimating daily air temperatures over the Tibetan Plateau by dynamically integrating MODIS LST data
Wang et al. Accuracy assessments of land use change simulation based on Markov-cellular automata model
Jing et al. An environment‐dependent probabilistic tropical cyclone model
Benoit et al. Stochastic rainfall modeling at sub‐kilometer scale
Sellars et al. Computational Earth science: Big data transformed into insight
Kumar et al. Land surface Verification Toolkit (LVT)–a generalized framework for land surface model evaluation
Moeslund et al. Light detection and ranging explains diversity of plants, fungi, lichens, and bryophytes across multiple habitats and large geographic extent
Pincus et al. Overlap assumptions for assumed probability distribution function cloud schemes in large‐scale models
Prein et al. US extreme precipitation weather types increased in frequency during the 20th century
Chen et al. Correcting systematic and state‐dependent errors in the NOAA FV3‐GFS using neural networks
Chen et al. Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms
Singh et al. Artificial intelligence and machine learning in earth system sciences with special reference to climate science and meteorology in South Asia.
Yo et al. A deep learning approach to radar‐based QPE
Song et al. A review of artificial intelligence in marine science
Rader et al. Detection of forced change within combined climate fields using explainable neural networks
Prein et al. Km‐scale simulations of mesoscale convective systems over South America—A feature tracker intercomparison
Ghajarnia et al. Evaluating the evolution of ECMWF precipitation products using observational data for Iran: From ERA40 to ERA5
Zhou et al. Deep learning spatiotemporal air pollution data in China using data fusion
Montillet et al. How big data can help to monitor the environment and to mitigate risks due to climate change: a review
Weiland et al. Intransitive Atmosphere Dynamics Leading to Persistent Hot–Dry or Cold–Wet European Summers
Karpatne et al. A guide to earth science data: Summary and research challenges
Collado‐Villaverde et al. A framework for evaluating geomagnetic indices forecasting models