Search Results - (( java application learning algorithm ) OR ( changes optimization means algorithm ))

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    A new soft computing model for daily streamflow forecasting by Sammen S.S., Ehteram M., Abba S.I., Abdulkadir R.A., Ahmed A.N., El-Shafie A.

    Published 2023
    “…Climate change; Data streams; Floods; Forecasting; Genetic algorithms; Hydroelectric power plants; Mean square error; Multilayer neural networks; Particle swarm optimization (PSO); Soft computing; Soil conservation; Water conservation; Water management; Water supply; Flow quantification; Multi layer perceptron; Optimization algorithms; Predicting models; Root mean square errors; Soft computing models; Streamflow forecasting; Watershed management; Stream flow; algorithm; forecasting method; hydroelectric power plant; numerical model; optimization; principal component analysis; streamflow; watershed; Helianthus…”
    Article
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    CUCKOO SEARCH OPTIMIZATION NEURAL NETWORK MODELS FOR FORECASTING LONG-TERM PRECIPITATION by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said

    Published 2024
    “…This paper presents the application of a novel optimization algorithm, Cuckoo Search Optimization (CSO), to train feedforward neural networks to forecast long-term precipitation using three climate models, namely HadCM3, ECHAM5, and HadGEM3‐RA. …”
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    Book Chapter
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    A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization by Jia Hui Ong, Jason Teo

    Published 2018
    “…In this study, three different selection mechanisms for Hyper-heuristics are introduced and compared against one of the top performing expensive optimization algorithms known asthe Mean-Variance Mapping Optimization (MVMO) as described in the CEC 2015 and 2016 expensive optimization competitions. …”
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    Article
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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    Conference or Workshop Item
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Thesis
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    Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

    Published 2014
    “…Reservoir systems require a continuous development of models for optimal operations in the context of future climate change. …”
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    Thesis
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    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2021
    “…Then, these two features were fused into a set of hybrid spectral-entropy attributes ( SEA). Consequently, optimization algorithms including binary gravitation search algorithm (BGSA) and binary particle swarm optimization (BPSO), were employed to identify the optimal channels for gender classification. …”
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    Article
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    An efficient control implementation for inverter based harmony serach algorithm by Najeeb, Mushtaq, Hamdan, Daniyal, Ramdan, Razali, Muhamad, Mansor

    Published 2017
    “…The mean absolute error (MAE) is used as an optimization problem to minimize the output voltage error for the developed controller (PI-HS) as compared to the PI controller based particale swarm optimization algorithm (PI-PSO). …”
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    Article
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    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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    Thesis
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    An Efficient Control Implementation for Inverter Based Harmony Search Algorithm by Najeeb, Mushtaq, Hamdan, Daniyal, Ramdan, Razali, Muhamad, Mansor

    Published 2017
    “…The mean absolute error (MAE) is used as an optimization problem to minimize the output voltage error for the developed controller (PI-HS) as compared to the PI controller based particale swarm optimization algorithm (PI-PSO). …”
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    Article
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    Multi-objective AGV scheduling in an FMS using a hybrid of genetic algorithm and particle swarm optimization by Mousavi, M., Yap, Hwa Jen, Musa, S.N., Tahriri, F., Md Dawal, Siti Zawiah

    Published 2017
    “…In the main draw of the research, a mathematical model was developed and integrated with evolutionary algorithms (genetic algorithm (GA), particle swarm optimization (PSO), and hybrid GA-PSO) to optimize the task scheduling of AGVs with the objectives of minimizing makespan and number of AGVs while considering the AGVs' battery charge. …”
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    Article
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    An efficient control implementation for inverter based harmony search algorithm by Najeeb M., Daniyal H., Razali R., Bin Mansor M.

    Published 2023
    “…The mean absolute error (MAE) is used as an optimization problem to minimize the output voltage error for the developed controller (PI-HS) as compared to the PI controller based particale swarm optimization algorithm (PI-PSO). …”
    Article
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    Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem by Abdelraheem Elhaj, Hazir Farouk

    Published 2005
    “…This means that it is highly unlikely to find a polynomial algorithm to solve the problem. …”
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    Thesis
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