Search Results - (( demand prediction using algorithm ) OR ( java application optimized algorithm ))

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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The combined influence of the genetic algorithm and correlation analysis are used in this technique. …”
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    Article
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    Hybrid Real-Value-Genetic-Algorithm and Extended-Nelder- Mead Algorithm for Short Term Energy Demand Prediction by Musa, Wahab, Ku Mahamud, Ku Ruhana, Salim, Sardi, Sediyono, Agung

    Published 2024
    “…This study proposes a hybrid prediction algorithm which comprises the RVGA and the extended-Nelder-Mead (ENM) algorithm. …”
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    Article
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    Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm by Ting S.C., Ismail A.R., Malek M.A.

    Published 2023
    “…This study aims at developing a novel effluent removal management tool for septic sludge treatment plants (SSTP) using a clonal selection algorithm (CSA). The proposed CSA articulates the idea of utilizing an artificial immune system (AIS) to identify the behaviour of the SSTP, that is, using a sequence batch reactor (SBR) technology for treatment processes. …”
    Article
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    An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

    Published 2024
    “…Particularly, the proposed optimized Bagged Trees are the most effective algorithm for energy demand prediction applications, and the proposed optimized Medium Trees are the most efficient algorithm for real-time systems. …”
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    Thesis
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    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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    Conference or Workshop Item
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    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis
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    Prediction of biochemical oxygen demand in Mexican surface waters using machine learning / Maximiliano Guzmán-Fernández ... [et al.] by Maximiliano, Guzmán-Fernández, Misael, Zambrano-de la Torre, Claudia, Sifuentes-Gallardo, Oscar, Cruz-Dominguez, Carlos, Bautista-Capetillo, Juan, Badillo-de Loera, Efrén, González Ramírez, Héctor, Durán-Muñoz

    Published 2021
    “…Pearson’s correlation and Forward Selection techniques were applied to identify the parameters with the most important contribution to prediction of biochemical oxygen demand. Two groups were formed and used as input to four machine learning algorithms. …”
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    Conference or Workshop Item
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    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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    Conference or Workshop Item