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  1. 1

    Development of genetic algorithm for optimization of yield models in oil palm production by Hilal, Yousif Y., Wan Ismail, Wan Ishak, Yahya, Azmi, Ash’aari, Zulfa Hanan

    Published 2018
    “…Owing to this great interest in the predictions, the study aims to develop a genetic algorithm (GA) to identify the relevant variables and search for the best combinations for modelling to examine the potential of oil palm production in Sarawak and Sabah, Borneo, Malaysia, under a given set of assumptions. …”
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    Article
  2. 2

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…This research presents the development of a GA and SW as a variables selection method in ANN and NARX models for predicting oil palm yield and output energy. …”
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    Thesis
  3. 3

    Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

    Published 2018
    “…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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    Thesis
  4. 4

    elopment of Neural Network Model for Predicting Crucial Product Properties or Yield for Optimisation of Refinery Operation by Mohamad, Sharliza

    Published 2005
    “…The objectives of this project are to develop a framework for the application of neural network modeling in predicting refinery product yield and properties, to develop neural network model for three case studies (predicting crude distillation yield, diesel pour point and hydrocracker total gasoline yield) and to evaluate the suitability of using neural networkmodelingfor predicting refinery product yield and properties. …”
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    Final Year Project
  5. 5

    Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

    Published 2005
    “…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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    Thesis
  6. 6

    Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

    Published 2023
    “…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. …”
    Article
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    Feature fusion using a modified genetic algorithm for face and signature recognition system by Suryanti, Awang

    Published 2015
    “…To overcome the issue of incompatible features to be combined, Wrapper Genetic Algorithm (GA) was implemented as the feature selection algorithm due to its ability to evaluate the features irrespective of which domain by masking the features with bit number. …”
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    Thesis
  9. 9

    Identification and Grading of Manage Using Image Processing by Shukor, Syazwan

    Published 2021
    “…This project has developed an image processing algorithm for a systematic maturity identification of "Mangga Susu Thai Gold" mangos. …”
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    Final Year Project
  10. 10
  11. 11

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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    Thesis
  12. 12

    Predictive Analytics in Genetic Engineering as an Optimization Problem by Okewu, Emmanuel, Okewu Kehinde, Bukola

    Published 2024
    “…In the search for drought-tolerant cowpea, this study applied a genetic algorithm as a predictive analytics tool in the genetic engineering of three native cowpea landraces (Dan muzakkari, Gidigiwa, and Dan mesera) selected from Northern Nigeria (specifically from Kontagora in Niger State of Nigeria). …”
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  13. 13

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
    Conference paper
  14. 14

    Modelling and optimization of catalytic-dielectric barrier discharge plasma reactor for methane and carbon dioxide conversion using hybrid artificial neural network - genetic algor... by Saidina Amin, Nor Aishah, Istadi, Istadi

    Published 2007
    “…A hybrid artificial neural network-genetic algorithm (ANN-GA) was developed to model, simulate and optimize the catalytic-dielectric barrier discharge plasma reactor. …”
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    Article
  15. 15

    Natural image noise level estimation based on local statistics for blind noise reduction by Khmag, Asem, Ramli, Abd Rahman, Sy Mohamed, Sy Abd Rahman Al-haddad, Kamarudin, Noraziahtulhidayu

    Published 2018
    “…Associated with different conventional noise estimators, the proposed algorithm yields the best performance, higher-quality images, and faster running speed.…”
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    Article
  16. 16

    Development of a syncope classification algorithm from physiological signals acquired in tilt-table test by Gan, Ming Hong

    Published 2023
    “…There are 8 set of feature selection model has built and a total of 24 set of classifiers with 3 different type of classification techniques were developed. …”
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    Final Year Project / Dissertation / Thesis
  17. 17

    Facial Drowsiness Signs Detection Algorithm Using Image Processing Techniques For Various Lighting Condition by Yuri, Nur Fatin Izzati

    Published 2017
    “…In this project, the algorithm is developed based on four main algorithms which are the detection algorithm, the tracking algorithm, the preprocessing algorithm and the drowsiness signs analysis algorithm. …”
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    Thesis
  18. 18

    Development Of Human Skin Detection Algorithm Using Multilayer Perceptron Neural Network And Clustering Method by Al-Mohair, Hani Kaid Saif

    Published 2017
    “…The Differential Evolution Algorithm (DE) is used in this work to select the optimum color and texture information to achieve the optimum response. …”
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    Thesis
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    Development of submergence tolerant rice variety through marker-assisted backcross breeding between MR219 and Swarna-Sub1 by Ahmed, Fahim

    Published 2015
    “…Marker-assisted selection (MAS) is an effective approach than the conventional breeding for rice varietal development. …”
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    Thesis