Search Results - (( data normalization _ algorithm ) OR ( variable training based algorithm ))

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Daily streamflow forecasting using simplified rule-based fuzzy logic system by Mohd Shafiek, Yaacob, Dr., Hishamuddin, Jamaluddin, Sobri, Harun

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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

“…Based on result obtained, it shows that IWO learning algorithm is capable to produce accurate prediction load demand. …”
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Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

“…On the contrary, CF+N technique requires some enhancements as the results were below expectations because of the tendency of CF to produce big differences in the prediction of raw data. It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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Daily streamflow forecasting using simplified rule-based fuzzy logic system by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin, Harun, Sobri

“…Verifications of the calibrated models were done using the data set of the following year. The performances of the simplified fuzzy logic system and the normal fuzzy logic system are compared,with each model having the same number of adjustable parameters. …”
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Developing a model to predict mathematics performance using neural network / Normaziah Abdul Rahman, Fadzilah Siraj and Noor Aishikin Adam by Abdul Rahman, Normaziah, Siraj, Fadzilah, Adam, Noor Aishikin

“…A neural network technique, using Multi Layer Perceptron (MLP) and back propagation algorithm is employed. A total of 391 data samples of diploma students were collected, trained and tested using this model. …”
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Academic Achievement Prediction Model Using Neural Networks by Normaziah, Abdul Rahman

“…This model allows the system administrator to train and normalize data as well as trains. Once the model has been established by the administrator, the future student achievement can be forecast by the model. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler High Temperature Superheater Trip using Artificial Intelligence Monitoring System by Alnaimi, F. B. I., Al-Kayiem, Hussain H.

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Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm by Acharya, U.R., Faust, O., Molinari, F., Sree, S.V., Junnarkar, S.P., Sudarshan, V.

“…These classification algorithms are trained using the features extracted from the patient data in order for them to learn the relationship between the features and the end-result (FLD present or absent). …”
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Early Admission Selection Process Into Sixth Form Science Streams Using Neural Networks Model by Wong, Tuck Sung

“…It also showed that the data were only slightly skewed and were normally distributed. …”
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Sleep as a predictor of depression level using Naïve Bayes / Nur Syakinah Md Roduan by Md Roduan, Nur Syakinah

“…Future work on this subject should improve the findings by modifying the variables used and/or by using other methods in term of data collection or the algorithm itself.…”
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What, how and when to use knowledge in neural network application by Wan Ishak, Wan Hussain, Abdul Rahman, Shuzlina

“…The methodology comprises five steps namely variable selection, data collection, data preprocessing, training &validation, and testing.…”
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Production quantity estimation using an improved artificial neural network by Dzakiyullah, Raden Nur Rachman

“…The cross-validation is common technique used to prevent over fitting problem by dividing the data into two categories namely data training and data test. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

“…Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. …”
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Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

“…The selection of the relevant variables for the neural networks is based on merging between theoretical analysis base and the plant operator experience. …”
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Effect of normalization and effect of normalization and training algorithm on radial basis training algorithm on radial basis function network performance function network performa... by Wani, Eddie

“…To recognize the effect of normalization of data and training algorithm on Radial Basis Function (RBF) performance.…”
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