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

Salah et al., 2022 - Google Patents

Exploring wind speed for energy considerations in eastern Jerusalem-Palestine using machine-learning algorithms

Salah et al., 2022

View HTML
Document ID
1943485046281293895
Author
Salah S
Alsamamra H
Shoqeir J
Publication year
Publication venue
Energies

External Links

Snippet

Wind energy is one of the fastest growing sources of energy worldwide. This is clear from the high volume of wind power applications that have been increased in recent years. However, the uncertain nature of wind speed induces several challenges towards the development of …
Continue reading at www.mdpi.com (HTML) (other versions)

Classifications

    • 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
    • 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
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • 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
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • 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
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • 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
    • G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • 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
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications

Similar Documents

Publication Publication Date Title
Li et al. A hierarchical approach using machine learning methods in solar photovoltaic energy production forecasting
Gutiérrez et al. A comparison of the performance of supervised learning algorithms for solar power prediction
Adnan et al. Comparison of LSSVR, M5RT, NF-GP, and NF-SC models for predictions of hourly wind speed and wind power based on cross-validation
Bochenek et al. Day-ahead wind power forecasting in Poland based on numerical weather prediction
Qin et al. Direct multistep wind speed forecasting using LSTM neural network combining EEMD and fuzzy entropy
Yan et al. A prediction model based on deep belief network and least squares SVR applied to cross-section water quality
Solano et al. Solar radiation forecasting using machine learning and ensemble feature selection
Lateko et al. Stacking ensemble method with the RNN meta-learner for short-term PV power forecasting
Salah et al. Exploring wind speed for energy considerations in eastern Jerusalem-Palestine using machine-learning algorithms
Qin et al. Day-ahead wind power forecasting based on wind load data using hybrid optimization algorithm
Pei et al. Wind turbine power curve modeling with a hybrid machine learning technique
Lateko et al. Short-term PV power forecasting using a regression-based ensemble method
Zhou et al. Classification and prediction of typhoon levels by satellite cloud pictures through GC–LSTM deep learning model
Morshed-Bozorgdel et al. A novel framework based on the stacking ensemble machine learning (SEML) method: application in wind speed modeling
Acharya et al. Day-ahead forecasting for small-scale photovoltaic power based on similar day detection with selective weather variables
Sacie et al. Use of state-of-art machine learning technologies for forecasting offshore wind speed, wave and misalignment to improve wind turbine performance
Wei Nearshore wave predictions using data mining techniques during typhoons: a case study near Taiwan’s northeastern coast
Du et al. A hybrid multi-step rolling forecasting model based on ssa and simulated annealing—adaptive particle swarm optimization for wind speed
Huang et al. Short-term wind speed forecasting based on low redundancy feature selection
Cenek et al. Climate change and power security: Power load prediction for rural electrical microgrids using long short term memory and artificial neural networks
Solano et al. Solar irradiation forecasting using ensemble voting based on machine learning algorithms
Lee et al. Improvement of short-term BIPV power predictions using feature engineering and a recurrent neural network
Wang et al. The short-term forecasting of asymmetry photovoltaic power based on the feature extraction of PV power and SVM algorithm
Ma et al. PV power forecasting based on relevance vector machine with sparrow search algorithm considering seasonal distribution and weather type
Malozyomov et al. Analysis of a Predictive Mathematical Model of Weather Changes Based on Neural Networks