Search Results - (( developing forecasting _ algorithm ) OR ( java application based algorithm ))

Search alternatives:

Refine Results
  1. 1
    Automated time series forecasting

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
    Get full text
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  2. 2
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
    Get full text
    Get full text
    Final Year Project
    Save to List
    Saved in:
  3. 3
    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting

    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

    Published 2013
    “…The aggregation algorithms were employed on the forecasts obtained from all individual NN models as well as on a number of the best forecasts obtained from the best NN models. …”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  4. 4
    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach

    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  5. 5
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting

    Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting by Afan H.A., Allawi M.F., El-Shafie A., Yaseen Z.M., Ahmed A.N., Malek M.A., Koting S.B., Salih S.Q., Mohtar W.H.M.W., Lai S.H., Sefelnasr A., Sherif M., El-Shafie A.

    Published 2023
    Article
    Save to List
    Saved in:
  7. 7
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…The results demonstrated the superiority of the IABO-trained algorithm in avoiding local minima, convergence speed, and accuracy compared to the benchmarking (BP and PSO) algorithms in water level forecasting tasks.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  8. 8
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…Hence, the WeSuSFTS algorithm succeeds to improve the MH-ELD forecasting accuracy.…”
    Get full text
    Get full text
    Monograph
    Save to List
    Saved in:
  9. 9
    Application of genetic algorithm and JFugue in an evolutionary music generator

    Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

    Published 2025
    “…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
    Save to List
    Saved in:
  10. 10
    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system

    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

    Published 2005
    “…The investigation is simulated using Intelligent Electricity Forecasting System (IEFS) developed in this research which written in Borland Delphi 7.0 programming.…”
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  11. 11
    Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow

    Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow by Osman A., Afan H.A., Allawi M.F., Jaafar O., Noureldin A., Hamzah F.M., Ahmed A.N., El-shafie A.

    Published 2023
    Article
    Save to List
    Saved in:
  12. 12
    Java based expert system for selection of natural fibre composite materials

    Java based expert system for selection of natural fibre composite materials by Ahmed Ali, Basheer A., Salit, Mohd Sapuan, Zainudin, Edi Syams, Othman, Mohamed

    Published 2013
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  13. 13
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  14. 14
    A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm

    A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm by Haruna, Chiroma, Khan, Abdullah, Abubakar, Adamu, Saudi, Younes, Hamza, Mukhtar Fatihu, Shuiba, Liyana, Gital, Abdulsalam, Herawan, Tutut

    Published 2016
    “…Many meta-heuristic algorithms have been proposed in literature for the optimization of Neural Network (NN) to build a forecasting model. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  15. 15
    Multi-horizon ternary time series forecasting

    Multi-horizon ternary time series forecasting by Htike@Muhammad Yusof, Zaw Zaw

    Published 2013
    “…This is mainly because state-of-the-art forecasting algorithms essentially perform single-horizon forecasts and produce continuous numbers as outputs. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  16. 16
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  17. 17
    Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model.

    Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model. by Nurul Hila Zainuddin

    Published 2018
    “…Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model. by Nurul Hila Zainuddin…”
    Get full text
    research_report
    Save to List
    Saved in:
  18. 18
    Automatic Number Plate Recognition on android platform: With some Java code excerpts

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    Get full text
    Get full text
    Get full text
    Book
    Save to List
    Saved in:
  19. 19
    Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm

    Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm by Tikhamarine Y., Souag-Gamane D., Najah Ahmed A., Kisi O., El-Shafie A.

    Published 2023
    Article
    Save to List
    Saved in:
  20. 20
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…Besides, different characteristics of each moving holiday and existence of a great number of irregularities in the load data also contribute to the forecasting inaccuracy and uncertainty. Fuzzy time series (FTS) algorithm is able to overcome moving holiday electricity load demand (MH-ELD) forecasting problem, but the FTS algorithm lacks final model interpretation, less interpretability of fuzzy logical relationship strength, and does not provide a complete FTS forecasting process. …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:

Search Tools: