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RSA Encryption & Decryption using JAVA
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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An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe
Published 2017“…Java programming language is used to implement the algorithm. …”
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Secure Image Steganography Using Encryption Algorithm
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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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
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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Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…The outputs from the individual NN models were combined by four different aggregation algorithms in NNs ensemble. These algorithms include equal�weights combination of Best NN models, combination of trimmed forecasts, combination through Variance-Covariance method and Bayesian Model Averaging. …”
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A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm
Published 2016“…The proposed approach is compared with established meta-heuristic algorithms. The results show that the new proposed method out performs existing algorithms by advancing OPEC petroleum consumption forecast accuracy and convergence speed. …”
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Digitally signed electronic certificate for workshop / Azinuddin Baharum
Published 2017“…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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Automated time series forecasting
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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Monograph -
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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…Time Series method has always been used in a variety of forecasting applications. …”
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…However, the existing measurement methods are complex, costly, and time-consuming. This research was conducted to forecast poverty using classification methods. …”
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A decision support system for improving forecast using genetic algorithm and tabu search
Published 2008“…The need and relevance of forecasting tools has become a much-discussed issue and this has led to the development of various new tools and methods for forecasting in the last two decades. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023“…Forecasting; Investments; Machine learning; Development investment; Energy prediction; Evaluation metrics; Long term planning; Machine learning methods; Metric evaluation; Resource planning; Systematic literature review; Learning algorithms…”
Conference Paper -
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Hybrid optimization approach to estimate random demand
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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Conference or Workshop Item -
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Thesis -
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)
“…Hence, the WeSuSFTS algorithm succeeds to improve the MH-ELD forecasting accuracy.…”
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Monograph -
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy inference system (ANFIS) technique as a forecasting engine. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…Furthermore, EEC in ASEAN-5 countries is forecasted by autoregressive integrated moving average (ARIMA) model and first-order single-variable grey model (GM (1, 1)) and their forecasts are compared with those obtained by the proposed method.…”
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