Search Results - (( data identification based algorithm ) OR ( variable learning based algorithm ))

Search alternatives:

Refine Results
  1. 1
    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor

    Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

    Published 2009
    “…In this paper, a novel gas identification approach based on Cluster-k-Nearest Neighbor. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  2. 2
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…The proposed data store management technique is combined with the central finite difference based gradient estimate to generate a model robust against both correlated data and irregular sampled data. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  3. 3
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
    Save to List
    Saved in:
  5. 5
    Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region

    Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region by Anees, Shoaib Ahmad, Mehmood, Kaleem, Khan, Waseem Razzaq, Sajjad, Muhammad, Alahmadi, Tahani Awad, Alharbi, Sulaiman Ali, Luo, Mi

    Published 2024
    “…Through the utilization of openly accessible fine-resolution data and employing the RF algorithm, the research demonstrated promising outcomes in the identification of optimal predictor-algorithm combinations for forest AGB mapping. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  6. 6
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    A machine learning approach of predicting high potential archers by means of physical fitness indicators

    A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

    Published 2019
    “…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction

    An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

    Published 2023
    “…Existence of missing data (known as data sparsity) have made the traffic prediction tasks even more sophisticated. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  9. 9
    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things

    Non-fungible token based smart manufacturing to scale Industry 4.0 by using augmented reality, deep learning and industrial Internet of Things by Ahmed Khan, Fazeel, Ibrahim, Adamu Abubakar

    Published 2023
    “…The next phase was deploying deep learning algorithms on a dataset having data generated from IIoT devices and sensors. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Zero distortion-based steganography for handwritten signature

    Zero distortion-based steganography for handwritten signature by Iranmanesh, Vahab

    Published 2018
    “…Thus, developing a steganographic algorithm to use cover media (c) without raising attention is the most challenging task in data hiding. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    An optimized ensemble for predicting reservoir rock properties in petroleum industry

    An optimized ensemble for predicting reservoir rock properties in petroleum industry by Kenari, Seyed Ali Jafari

    Published 2013
    “…The first method isbased on fuzzy genetic algorithm to overcome the premature convergence. The second method is based on two other functions instead of traditional fitness function in genetic algorithmnamely MSE to determine the individual's weight in an ensemble.This approach is based on Huber and Bisquare functions which are meant to avoid the influence of outliers that can be found in many real data such as geosciences data. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  12. 12
    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke

    Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

    Published 2019
    “…Third, to propose orientation invariant based deep spare autoencoder methods for automatic complex activity identification to minimize orientation inconsistencies and learn adequate data patterns. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
    Get full text
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  14. 14
    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi

    Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi by Nik Effendi, Nik Ahmad Faris

    Published 2022
    “…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  15. 15
    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis

    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…A comparison between one variable at a time, Taguchi method and artificial neural network shows that both Taguchi and ANN can reduce the amount of enzyme, amount of molecular sieve, reaction time and molar ratio in solvent based and solvent free system. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test

    Fsm-Based Enhanced March C- Algorithm For Memory Built-In Self-Test by CH’NG , MING ZONG

    Published 2017
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Recursive Subspace Identification Algorithm Using The Propagator Based Method

    Recursive Subspace Identification Algorithm Using The Propagator Based Method by Jamaludin, Irma Wani, Abdul Wahab, Norhaliza

    Published 2017
    “…In this paper, the recursive subspace identification algorithm based on the propagator method which avoids the SVD computation is proposed. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  18. 18
    Date store management in sliding window based on-line identification algorithms

    Date store management in sliding window based on-line identification algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2001
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  19. 19
    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data

    Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

    Published 2016
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  20. 20
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:

Search Tools: