[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Pelikán, 2014 - Google Patents

FORECASTING OF PROCESSES IN COMPLEX SYSTEMS FOR REAL-WORLD PROBLEMS.

Pelikán, 2014

View PDF
Document ID
3784127915031460354
Author
Pelikán E
Publication year
Publication venue
Neural Network World

External Links

Snippet

This tutorial is based on modification of the professor nomination lecture presented two years ago in front of the Scientific Council of the Czech Technical University in Prague [16]. It is devoted to the techniques for the models developing suitable for processes forecasting in …
Continue reading at www.nnw.cz (PDF) (other versions)

Classifications

    • 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
    • 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
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • 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
    • 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"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • 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
    • 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
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202Market predictions or demand forecasting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • 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
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/20Education

Similar Documents

Publication Publication Date Title
Zhang et al. A gradient boosting method to improve travel time prediction
Grover et al. A deep hybrid model for weather forecasting
Russo et al. Air quality prediction using optimal neural networks with stochastic variables
Chou et al. Multistep energy consumption forecasting by metaheuristic optimization of time‐series analysis and machine learning
Luo et al. Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings
Horenko Nonstationarity in multifactor models of discrete jump processes, memory, and application to cloud modeling
Ponnoprat Short-term daily precipitation forecasting with seasonally-integrated autoencoder
WO2019069865A1 (en) Parameter estimation system, parameter estimation method, and parameter estimation program recording medium
Mbuvha et al. Separable shadow Hamiltonian hybrid Monte Carlo for Bayesian neural network inference in wind speed forecasting
Wesonga On multivariate imputation and forecasting of decadal wind speed missing data
Taheri et al. A novel probabilistic regression model for electrical peak demand estimate of commercial and manufacturing buildings
Atıcı et al. Prediction of the Ionospheric foF2 parameter using R language forecasthybrid model library convenient time series functions
Caroprese et al. DL2F: A Deep Learning model for the Local Forecasting of renewable sources
Santos de Jesus et al. Machine learning models for forecasting water demand for the Metropolitan Region of Salvador, Bahia
Pelikán FORECASTING OF PROCESSES IN COMPLEX SYSTEMS FOR REAL-WORLD PROBLEMS.
Abdallah et al. A vector autoregressive methodology for short-term weather forecasting: tests for Lebanon
Melinc et al. 3D‐Var data assimilation using a variational autoencoder
Galphade et al. Intelligent multiperiod wind power forecast model using statistical and machine learning model
JP7257276B2 (en) Data prediction system and method
Cabrera et al. Rainfall Forecasting using a Bayesian framework and Long Short-Term Memory Multi-model Estimation based on an hourly meteorological monitoring network. Case of study: Andean Ecuadorian Tropical City
Pallage et al. Wasserstein Distributionally Robust Shallow Convex Neural Networks
David et al. Solar radiation probabilistic forecasting
Rantonen et al. Prediction of spot prices in nord pool’s day-ahead market using machine learning and deep learning
Kalashak Prediction of Water Consumption Using Machine Learning: Using machine learning techniques to predict hourly water consumption in sustainable smart city
Piatkowski et al. How to Trust Generative Probabilistic Models for Time-Series Data?