Search Results - (( adaptive _ difference evolution algorithm ) OR ( adaptive k different optimization algorithm ))*

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    Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

    Published 2024
    “…Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. Post-optimization ANN model was trained using eleven different leaning algorithms. …”
    Article
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    Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain by Monowar, Hossain

    Published 2017
    “…For these purposes, the standalone ANFIS, ANFIS-PSO (particle swarm optimization),ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) prediction algorithms have been developed in MATLAB platform. …”
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    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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    Document clustering based on firefly algorithm by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…Document clustering is widely used in Information Retrieval however, existing clustering techniques suffer from local optima problem in determining the k number of clusters.Various efforts have been put to address such drawback and this includes the utilization of swarm-based algorithms such as particle swarm optimization and Ant Colony Optimization.This study explores the adaptation of another swarm algorithm which is the Firefly Algorithm (FA) in text clustering.We present two variants of FA; Weight- based Firefly Algorithm (WFA) and Weight-based Firefly Algorithm II (WFAII).The difference between the two algorithms is that the WFAII, includes a more restricted condition in determining members of a cluster.The proposed FA methods are later evaluated using the 20Newsgroups dataset.Experimental results on the quality of clustering between the two FA variants are presented and are later compared against the one produced by particle swarm optimization, K-means and the hybrid of FA and -K-means. …”
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    A comparative study for parameter selection in online auctions by Gan, Kim Soon

    Published 2009
    “…In this work, three different models of genetic algorithms are considered. …”
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    Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

    Published 2020
    “…The median convergence traces have been compared with two different algorithms based on differential evolution, i:e: Ensemble of Constraint Handling Techniques (ECHT) and Stochastic Ranking Differential Evolution (SRDE). …”
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    Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme by Abdulhasan, Muntadher Qasim

    Published 2014
    “…This thesis proposes an adaptive feedback algorithm that uses a threshold scheme to enhance the system throughput while maintaining low Block Error Rate (BLER), Bit Error Rate (BER), and overhead. …”
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    Evolution strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

    Published 2013
    “…It becomes a vital problem to achieve CB as the distributed sensor nodes are unaware of their phase relationship. An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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    Thesis
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