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  1. 1
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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    Final Year Project
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  2. 2
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
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  3. 3
    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe

    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

    Published 2017
    “…Java programming language is used to implement the algorithm. …”
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  4. 4
    Secure Image Steganography Using Encryption Algorithm

    Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

    Published 2016
    “…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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  5. 5
    Digitally signed electronic certificate for workshop / Azinuddin Baharum

    Digitally signed electronic certificate for workshop / Azinuddin Baharum by Baharum, Azinuddin

    Published 2017
    “…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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  6. 6
    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.…”
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  7. 7
    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. …”
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  8. 8
    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
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  9. 9
    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.…”
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  10. 10
    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
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  11. 11
    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. …”
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  12. 12
    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. …”
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  13. 13
    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
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  14. 14
    Balanced Stochastic Realization Algorithm For Development Of Rainfall Model

    Balanced Stochastic Realization Algorithm For Development Of Rainfall Model by Azhari, Fahimy

    Published 2014
    “…In this research, Balanced Stochastic Realization (BSR) subspace algorithm is used to develop a rainfall model for Malaysia. …”
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  15. 15
    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. …”
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  16. 16
    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
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  17. 17
    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
    “…Real-world optimizations, such as forecasting streamflow, are a complicated process that is highly non-linear and multi-modal, demanding the use of a suitable modeling tool, with an emphasis on artificial intelligence algorithms, to get befitting forecast results. …”
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  18. 18
    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
    “…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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  19. 19
    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.…”
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  20. 20
    Rainfall-funoff modelling in batang layar and oya sub-catchments using pre-developed ann model for tinjar catchment

    Rainfall-funoff modelling in batang layar and oya sub-catchments using pre-developed ann model for tinjar catchment by Awangku Faizal Sallehin, Awangku Brahim

    Published 2009
    “…Artificial Neural Network (ANN) has been widely used to forecast Rainfall-Runoff relationships. Many ANN has been developed by experts in order to forecast RainfallRunoff relationships in certain catchment. …”
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    Final Year Project Report / IMRAD
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