Kulik et al., 2022 - Google Patents
Lagrangian characteristics in the western North Pacific help to explain variability in Pacific saury fisheryKulik et al., 2022
- Document ID
- 3224111615582678947
- Author
- Kulik V
- Prants S
- Uleysky M
- Budyansky M
- Publication year
- Publication venue
- Fisheries Research
External Links
Snippet
A new model for estimation of daily probability for the Pacific saury (Cololabis saira) encounter was proposed. The model performance was tested for the period of 2004–2018 (August–November) using the data from the Russian vessel monitoring system. The …
- 241000624562 Cololabis saira 0 title abstract description 20
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
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- 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
-
- 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
- G01S13/95—Radar or analogous systems specially adapted for specific applications for meteorological use
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01W—METEOROLOGY
- G01W1/00—Meteorology
- G01W1/10—Devices for predicting weather conditions
-
- 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
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
-
- 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
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Valavanis et al. | Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS | |
Sumata et al. | An intercomparison of A rctic ice drift products to deduce uncertainty estimates | |
Sellars et al. | Computational Earth science: Big data transformed into insight | |
Kannan et al. | A nonparametric kernel regression model for downscaling multisite daily precipitation in the Mahanadi basin | |
AghaKouchak et al. | Geometrical characterization of precipitation patterns | |
Latif et al. | Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches | |
Portilla et al. | Spectral wave conditions in the Colombian Pacific Ocean | |
Cetina‐Heredia et al. | Retention and leakage of water by mesoscale eddies in the East Australian Current system | |
Stachelek et al. | Application of inverse path distance weighting for high-density spatial mapping of coastal water quality patterns | |
Li et al. | An object-based approach for verification of precipitation estimation | |
Bond et al. | Prediction of hydrologic characteristics for ungauged catchments to support hydroecological modeling | |
Song et al. | A review of artificial intelligence in marine science | |
Chen et al. | Modeling landslide susceptibility based on convolutional neural network coupling with metaheuristic optimization algorithms | |
Meng et al. | Remote Sensing for Subsurface and Deeper Oceans: An overview and a future outlook | |
Yo et al. | A deep learning approach to radar‐based QPE | |
Martínez-Minaya et al. | Dealing with physical barriers in bottlenose dolphin (Tursiops truncatus) distribution | |
Kumar et al. | A comprehensive study of different feature selection methods and machine-learning techniques for SODAR structure classification | |
Karabulut et al. | Wave height prediction with single input parameter by using regression methods | |
Stensrud et al. | The correspondence ratio in forecast evaluation | |
Singh et al. | Artificial intelligence and machine learning in earth system sciences with special reference to climate science and meteorology in South Asia. | |
Montillet et al. | How big data can help to monitor the environment and to mitigate risks due to climate change: a review | |
Kulik et al. | Lagrangian characteristics in the western North Pacific help to explain variability in Pacific saury fishery | |
Robertson | Wave energy assessments: quantifying the resource and understanding the uncertainty | |
Storie et al. | Evaluation of Loop Current/Loop Current Eddy Fronts to guide offshore oil & gas operations | |
Wimmer et al. | Sensitivity analysis of the convective‐scale AROME model to physical and dynamical parameters |