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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  6. 6
    Loss reduction in distribution networks using new network reconfiguration algorithm

    Loss reduction in distribution networks using new network reconfiguration algorithm by Kashem, M.A., Moghavvemi, M., Mohamed, A., Jasmon, G.B.

    Published 1996
    “…The first stage of this solution algorithm finds a loop which gives the maximum loss reduction in the network. …”
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  7. 7
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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  8. 8
    Network reconfiguration and control for loss reduction using genetic algorithm

    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…The proposed solution to this problem is based on a general combinatorial optimization algorithm known as Genetic Algorithm, and the load flow equations in distribution network. …”
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  9. 9
    Loss reduction in distribution networks by network reconfiguration: a two stage solution approach

    Loss reduction in distribution networks by network reconfiguration: a two stage solution approach by Nallagownden, Perumal

    Published 2004
    “…The first stage of this solution algorithm finds a loop, which gives the maximum loss reduction in the network. …”
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  10. 10
    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…An integrated solution for the above problem is the ECQ Routing Algorithm. …”
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  11. 11
    Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime

    Fine-tuning approach in metaheuristic algorithm to prolong wireless sensor networks nodes lifetime by Rahiman, Amir Rizaan, Williams, Temitope Betty, Zakaria, Muhammad D.

    Published 2022
    “…A set of simulations has been performed using MATLAB R2018b on the proposed solution, namely the energy efficient of genetic (EEG) algorithm and has revealed that the solution outperforms the network lifetime and cluster head load of the existing solution.…”
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  12. 12
    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network

    Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

    Published 2006
    “…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
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  13. 13
    Decentralized traffic signal control for grid traffic network using genetic algorithm

    Decentralized traffic signal control for grid traffic network using genetic algorithm by Min Keng Tan, Helen Sin Ee Chuo, Kiam Beng Yeo, Renee Ka Yin Chin, Sha Huang, Kenneth Tze Kin Teo

    Published 2019
    “…Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. …”
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  14. 14
    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain

    Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain by Sadrnia, Abdolhossein

    Published 2014
    “…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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  15. 15
    A survey of state of the art: hierarchical routing algorithms for wireless sensor networks

    A survey of state of the art: hierarchical routing algorithms for wireless sensor networks by Kareem, Husam, Hashim, Shaiful Jahari, Sali, Aduwati, Subramaniam, Shamala

    Published 2014
    “…Many researches have been done to solve this problem or at least find a solution to decrease the energy consumption. One of those solutions is using efficient routing algorithm. …”
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  16. 16
    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network

    Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network by Ismail Abdullah, Kalid Abdlkader Marsal

    Published 2024
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  17. 17
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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  18. 18
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…The algorithm introduces the fuzzy Pareto dominance concept to compare two solutions and uses the scalar decomposition method when one solution cannot dominate the other in terms of the fuzzy dominance level. …”
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  19. 19
    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems

    Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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  20. 20
    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems

    Hybrid NSGA-II Optimization for Improving the Three-Term BP Network for Multiclass Classification Problems by Ibrahim, Ashraf Osman, Shamsuddin, Siti Mariyam, Qasem, Sultan Noman

    Published 2015
    “…The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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