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  1. 1
    Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques

    Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques by Qtaish, Osama Kayed Taher

    Published 2014
    “…In this thesis, a smart QoS-aware service composition approach is proposed. The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. …”
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  2. 2
    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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  3. 3
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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  4. 4
    A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation

    A comparative study on various ANN optimization algorithms for magnetorheological elastomer carbonyl iron particle concentration estimation by Kasma Diana, Saharuddin, Mohd Hatta, Mohammed Ariff, Bahiuddin, Irfan, Nurhazimah, Nazmi, Mohd Azizi, Abdul Rahman, Mohd Ibrahim, Shapiai, Fauzan, Ahmad, Sarah Atifah, Saruchi

    Published 2024
    “…Therefore, this paper proposed a carbonyl iron particle (CIP) concentration based MRE prediction model using neural network algorithm. …”
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  5. 5
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…Several simulated systems and real-world timedependent data are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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  6. 6
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…Several simulated systems and real-world timedependent data, are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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  7. 7
    IOT-based fertigation system / Mohamad Amir Furqan Darus

    IOT-based fertigation system / Mohamad Amir Furqan Darus by Darus, Mohamad Amir Furqan

    Published 2024
    “…It integrates the MDD3A Cytron motor driver for water pump control and the Ph sensor to monitor soil acidity or alkalinity. Using advanced algorithms and machine learning techniques, the system nalyses the collected data to determine optimal irrigation and fertilization requirements. …”
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  8. 8
    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…Several simulated systems and real-world timedependent data are used in the investigation. Comparisons based on widely used optimization performance indicators along with outcomes from other research are used. …”
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  9. 9
    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques

    Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

    Published 2018
    “…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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  10. 10
    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization

    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

    Published 2022
    “…The objective of this research is to develop and compare various ANN spray drying coconut milk models. Firstly, using MATLAB program, the ANN model is developed based on optimized topology and is then furthered optimized by genetic algorithm (GA) and particle swarm optimization (PSO) using MINITAB program. …”
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  11. 11
    An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum

    An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum by Darzi S., Tiong S.K., Tariqul Islam M., Rezai Soleymanpour H., Kibria S.

    Published 2023
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  12. 12
    DEVELOPMENT OF COMPOSITIONAL MODEL FOR PREDICTING VISCOSITY OF CRUDE OILS USING POLYNOMIAL NEURAL NETWORKS (PNN) INDUCED BY GROUP METHOD OF DATA HANDLING (GMDH)

    DEVELOPMENT OF COMPOSITIONAL MODEL FOR PREDICTING VISCOSITY OF CRUDE OILS USING POLYNOMIAL NEURAL NETWORKS (PNN) INDUCED BY GROUP METHOD OF DATA HANDLING (GMDH) by Wen Pin, Yong

    Published 2011
    “…GMDH is an inductive algorithm for computer-based mathematical modeling using neural network with active neurons that optimizes model coefficients for predetermine mathematical equation and selects the optimal model complexity. …”
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  13. 13
    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms

    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

    Published 2011
    “…Triethanolamine (TEA)-based esterquats are potential high-value products used as surfactants and softening agents. …”
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  14. 14
    CFD-based optimization of base pressure behavior on suddenly expanded flows at supersonic Mach numbers

    CFD-based optimization of base pressure behavior on suddenly expanded flows at supersonic Mach numbers by Jaimon, Dennis Quadros, Khan, Sher Afghan, Prashanth, T.

    Published 2022
    “…Furthermore, to assess the right range of conditions for maximizing base pressure, the genetic algorithm (GA), desirability function approach (DFA), and particle swarm optimization (PSO) techniques were implemented. …”
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  15. 15
    Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review

    Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

    Published 2023
    Review
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  16. 16
    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction

    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

    Published 2018
    “…The objective of this study, first, a firefly algorithm (FA) based on the k-fold cross-validation of BPNN has been suggested to predict data for keeping rapid learning and prevents the exponential increase in operating parts. …”
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  17. 17
    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach

    Analysis of parallel flow type internally cooled membrane-based liquid desiccant dehumidifier using a neural networks approach by Quadros, Jaimon Dennis, Khan, Sher Afghan, T., Prashanth

    Published 2021
    “…Backpropagation algorithm (BP), artificial bee colony (ABC), and genetic algorithm (GA) models were used to train the neural network (NN) parameters using the data collected from the CCD-based response equation. …”
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  18. 18
    Empirical modeling of hydrate formation prediction in deepwater pipelines

    Empirical modeling of hydrate formation prediction in deepwater pipelines by Hashim, F.M., Abbasi, A.

    Published 2016
    “…This model is based on temperature and pressure conditions. The correlations between temperature and pressure are developed by using MATLAB software and then optimize with optimization techniques, such as genetic algorithm and particle swarm optimization. …”
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  19. 19
    Profit Optimization of a Refrigerated Gas Plant

    Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

    Published 2007
    “…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. The success of solving the optimization problem rests on the accuracy of the plant model used, as well as the inclusion of technical and business aspects of the plant operation. …”
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  20. 20
    Profit Optimization of a Refrigerated Gas Plant

    Profit Optimization of a Refrigerated Gas Plant by Yusoff, Nooryusmiza, Ramasamy , Marappagounder, Yusup, Suzana

    Published 2007
    “…This requires continuous re-evaluation of the operating conditions through an efficient optimization algorithm. The success of solving the optimization problem rests on the accuracy of the plant model used, as well as the inclusion of technical and business aspects of the plant operation. …”
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