Search Results - (( java implementation phase algorithm ) OR ( layer perception study algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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Thesis -
2
Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan
Published 1998“…The Back Propagation Algorithm, which consists of the multi-layered perception model, makes possible to train the ANN training pattems. …”
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4
IoT Soil Moisture Monitoring and Irrigation System Development
Published 2020“…At the same time, with a self-sufficient and self-organized irrigation system based on the water-control algorithm. The developed system covered the three layers in IoT architecture: perception layer, network layer and application layer. …”
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Proceeding -
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Forecasting The Growth of Manufacturing Industry in Malaysia Using Artificial Neural Network
Published 2006“…The effectiveness of ANN for predicting one criterion, Y form several predictors, X, is investigated. Comparative studies are examined between the result of the predictions from the ANN model trained with Multi-Layer Feed forward Perception, a Generalised Regressions Neural Network (GRNN) algorithm and the result obtained from traditional statistical approach.…”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Data Processing - ANN Application ( Data pre-processing using Z-score, ANN design structure/architecture - parameter optimisation, training and testing the algorithm) Result & Discussion: ANN parameter optimisation - final error for learning rate, momentum rate and hidden layer size ANN final design parameter - Nodes in input layer: 7, Nodes in hidden layer size: 2, Output layer size: 1, learning rate: 0.9, Momentum rate: 0.7, Error goal: 0.01, Epochs: 100 ANN prediction: high accuracy for training and testing prediction (refer to the figure in poster) Patent & List of contributions: 1. …”
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Book Section -
7
Multivariate Time Series Forecasting Of Crude Palm Oil Price Using Machine Learning Techniques
Published 2017“…Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques.The results were assessed by using criteria of root mean square error (RMSE),means absolute error (MAE),means absolute percentage error (MAPE) and Direction of accuracy (DA).Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method. …”
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Article -
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Artificial neural network modeling of grinding of ductile cast iron using water based sio2 nanocoolant
Published 2014“…An artificial neural network model is developed for predicting the surface roughness and MRR. Multi-layer perception and a batch back propagation algorithm are used. …”
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Article -
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Cyber-Crime Detection: Experimental Techniques Comparison Analysis
Published 2023“…The objective of this research paper is to conduct experimental techniques comparison analysis for cyber-crime detection by reviewing all possible machine learning algorithms for automatic detection. The key focus of the study is on the use of eight classifiers models which are Logistic Regression (LR), Decision Tree (DT), K-nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and Multiple layer perception (MLP). …”
Conference Paper -
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Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function
Published 2012“…Artificial neural network (ANN) model is developed for predicting the results of the surface roughness and MRR. Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. …”
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Undergraduates Project Papers -
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