Search Results - (( based training data algorithm ) OR ( java implication based algorithm ))
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…As a conclusion, the MAPE obtained for the Bat Algorithm based Multi-Layer Feedforward Neural Network is 4.79 in %.…”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. Supervised classification of remotely sensed data requires systematic collection of training samples for classes of interest. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System
Published 2010“…The one hidden layer with one neuron using BFG training algorithm provides the best optimum neural network structure. …”
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Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…As a conclusion, the MAPE obtained for the Bat Algorithm based Multi-Layer Feedforward Neural Network is 4.79 in %.…”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…Following the best selection of neural network algorithm, BR algorithm is further trained using 50-70% training with 10-28 hidden neurons. …”
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Separable Recursive Training Algorithms with Switching Module
Published 2009“…This new technique for updating weights combines non linear recursive training algorithms for the optimization of nonlinear weights with recursive least square type algorithms for the training of linear weights in one integrated routine. …”
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An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability
Published 2023“…Overall, our study emphasizes the importance of addressing data leakage in the training process to ensure the reliability of ML-based IDS models.…”
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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Detection of the spread of Covid-19 in Indonesia using K-Means Clustering Algorithm / Mohammad Yazdi Pusadan ... [et al.]
Published 2023“…The data source used as training data comes from the official Kaggle website, the data used in this study is data on the spread of the coronavirus collected from 2020 to 2021 with a total of 20,816 training data. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Characterization of oil palm fruitlets using artificial neural network
Published 2014“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…Second experiment was carried out by reducing the data to 240 for training data and 60 data for testing. …”
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Sentiment analysis for malay newspaper (SAMNews) using negative selection algorithm / Nur Amalina Redzuan
Published 2013“…While in Experiment III used 900 newspaper’s sentences as the training data and 100 newspaper’s sentences as the testing data and the accuracy is unproved to 65.81%. …”
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Application of adaptive network based fuzzy inference system for model reconstruction in reverse engineering
Published 2004“…The trained ANFIS is taken as surface data model. By comparing the surface data, which is from trained ANFIS, with the data sample value, it can be found that the ANFIS model can match the real surface very well.…”
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