Search Results - (( trained selection process algorithm ) OR ( java implication based algorithm ))

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  1. 1

    Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection by Chia, Yee Shin

    Published 2015
    “…Results show that the reinforced network classifier with GA feature selection algorithm has successfully increased the classification accuracy of training process and testing process by 13.87% and 14.21% respectively compared to the conventional neural network classifier. …”
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    Thesis
  2. 2

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

    Published 2005
    “…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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    Thesis
  3. 3

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. …”
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    Article
  4. 4

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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    Article
  5. 5

    Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim by Ibrahim, Erman

    Published 2007
    “…This project is about recognizing hand gesture for sign language using backpropagation (BP) algorithm that is one of the training algorithms used in the Artificial Neural Network (ANN). …”
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    Thesis
  6. 6

    Diabetes prediction system using clonal selection algorithm / Nor Aishah Mustapa by Mustapa, Nor Aishah

    Published 2012
    “…Diabetes Prediction system using clonal selection algorithm is available to test whether patients suffering from diabetes or not. …”
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    Thesis
  7. 7

    Evaluation of feature selection algorithm for android malware detection by Mazlan, Nurul Hidayah, A Hamid, Isredza Rahmi

    Published 2018
    “…The Android features were filtered before detection process using TF-IDF algorithm. However, IDF is unaware to the training class labels and give incorrect weight value to some features. …”
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    Article
  8. 8

    Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

    Published 2004
    “…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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    Thesis
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    Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M... by Mohamad Salehuddin, Mohamad Firdaus

    Published 2020
    “…There were 1 optimized model selected from the classification process. The accuracy from the selected most optimized models were 100%. …”
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    Student Project
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    Image classification using two dimensional wavelet coefficients with parallel computing by Ong, Yew Fai

    Published 2020
    “…In addition, this research does not require any pre-stored database to train the algorithm. This research requires the supervision from the users to train the algorithm by naming the region. …”
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    Final Year Project / Dissertation / Thesis
  14. 14

    An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

    Published 2019
    “…K-means clustering is applied to select the highly promising company; MGWO is implemented for feature selection and training; finally, MGWO-NN is applied to predict the stock price. …”
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    Thesis
  15. 15

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…In the experimental phase, academic leadership competency data were collected from a selected higher learning institution as training data-set based on 10-fold cross validation. …”
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    Conference or Workshop Item
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    Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

    Published 2017
    “…The EANN modelling was used to represent the biogas production process. One of the issues of ANN implementation is to correctly select the output activation function in achieving higher output. …”
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    Thesis
  18. 18

    An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration by Momeni, M., Hosseini, S.J., Ridha, S., Laruccia, M.B., Liu, X.

    Published 2018
    “…When drilling a new well, bit selection process requires the maximum ROP of a bit that corresponds to the optimum drilling parameters being obtained by combining the trained ANN model with GA. …”
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    Article
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    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…Altogether, for BOD, the BR algorithm with 60% training and 12 hidden nodes gives R=0.7825 whereas for COD, the BR algorithm with 70% training and 10 hidden nodes gives R=0.6716. …”
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    Monograph
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    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…The implementation and the computational aspects of the training algorithm are also highlighted. Three examples of discrete-time nonlinear systems are used in the simulation study to show the effects of user selected conditions on the identification process. …”
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    Article