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

Guo et al., 2022 - Google Patents

A combined model based on sparrow search optimized BP neural network and Markov chain for precipitation prediction in Zhengzhou City, China

Guo et al., 2022

View PDF
Document ID
9698444972246992165
Author
Guo N
Wang Z
Publication year
Publication venue
AQUA—Water Infrastructure, Ecosystems and Society

External Links

Snippet

Simulation and prediction of precipitation time series changes are important for revealing global climate change patterns and understanding surface hydrological processes. However, precipitation is influenced by a variety of factors together, showing the …
Continue reading at iwaponline.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/04Architectures, e.g. interconnection topology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA 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
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"

Similar Documents

Publication Publication Date Title
Yang et al. A new air quality monitoring and early warning system: Air quality assessment and air pollutant concentration prediction
Dong et al. Hourly energy consumption prediction of an office building based on ensemble learning and energy consumption pattern classification
Sanikhani et al. Non-tuned data intelligent model for soil temperature estimation: A new approach
Wu et al. Evolving RBF neural networks for rainfall prediction using hybrid particle swarm optimization and genetic algorithm
Chen et al. A short-term flood prediction based on spatial deep learning network: A case study for Xi County, China
Hou et al. Prediction of hourly air temperature based on CNN–LSTM
Kisi et al. Precipitation forecasting using wavelet-genetic programming and wavelet-neuro-fuzzy conjunction models
Ibrahim et al. A novel hybrid model for hourly global solar radiation prediction using random forests technique and firefly algorithm
Guo et al. A combined model based on sparrow search optimized BP neural network and Markov chain for precipitation prediction in Zhengzhou City, China
Troncoso et al. Local models-based regression trees for very short-term wind speed prediction
Sikorska-Senoner et al. A novel ensemble-based conceptual-data-driven approach for improved streamflow simulations
Nikoo et al. Flood-routing modeling with neural network optimized by social-based algorithm
Vamsidhar et al. Prediction of rainfall using backpropagation neural network model
Kan et al. A new hybrid data-driven model for event-based rainfall–runoff simulation
Wang et al. Flood simulation using parallel genetic algorithm integrated wavelet neural networks
Farokhnia et al. Application of global SST and SLP data for drought forecasting on Tehran plain using data mining and ANFIS techniques
Li et al. A novel combined prediction model for monthly mean precipitation with error correction strategy
Bajirao et al. Potential of hybrid wavelet-coupled data-driven-based algorithms for daily runoff prediction in complex river basins
Adeyemo et al. River flow forecasting using an improved artificial neural network
CN108280998A (en) Short-time Traffic Flow Forecasting Methods based on historical data dynamic select
CN117236199B (en) Method and system for improving water quality and guaranteeing water safety of river and lake in urban water network area
Elbeltagi et al. Forecasting monthly pan evaporation using hybrid additive regression and data-driven models in a semi-arid environment
Hosseini et al. Evaluation of data-driven models to downscale rainfall parameters from global climate models outputs: the case study of Latyan watershed
Dayal et al. Drought modelling based on artificial intelligence and neural network algorithms: a case study in Queensland, Australia
Shiri et al. Forecasting daily stream flows using artificial intelligence approaches