Search Results - (( knowledge activation function algorithm ) OR ( java learning classification algorithm ))
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Recently, various techniques based on different algorithms have been developed. However, the classification accuracy and computational cost are not satisfied. …”
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Thesis -
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin
Published 2012“…The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. The result from the SVM algorithms will be used as database for the machine learning in Microsoft Azure. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024Conference Paper -
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Object-Oriented Programming semantics representation utilizing agents
Published 2011“…Generally, these source codes go through the preprocessing, comparison, extraction, generate program semantics and classification processes. A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The results reveal that the proposed hybrid algorithm is capable of achieving classification accuracy values of (95.82 % and 97.68 %), detection rates values of (95.8 % and 99.3 %) and false alarm rates values of (0.083 % and 0.045 %) on both KDD CUP 99 and NSL KDD. …”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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DEVELOPMENT OF A MULTI-OBJECTIVE OPTIMZATION FRAMEWORK FOR INDUSTRIAL PROCESSES
Published 2014“…The proposed framework is introduced as the 'surgery framework (SF)' since its prime functionality is to dissect the algorithm and add certain mechanisms into it. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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Semantic analysis system by using latent semantic analysis (LSA) algorithm on khutbah texts / Ammar Zuber
Published 2019“…As nowadays, some muslims attend the Friday Prayers just to obey God instruction instead of willingly come to gain new knowledge. This is where the khutbah texts needs to have a certain level of quality and also new knowledge to ensure muslims does not go back home empty-handed. …”
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023“…The proposed algorithm has the ability to improve cloudlet allocation to meet the objective function. …”
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Prediction of nanostructure of SnO2 properties using artificial neural networks / Khadijah Mohd Suhami ... [et al.]
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Knowledge of extraction from trained neural network by using decision tree
Published 2017“…These knowledge are described within topology, using activation function and connection weight at hidden neurons and output neurons. …”
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Rule extraction from multi-layer perceptron neural network using decision tree for currency exchange rates forecasting
Published 2015“…Neural network can be used in acquiring hidden knowledge in datasets. However, knowledge acquired by neural network was presented in its topology, the weights on the connections and by the activation functions of the hidden and output nodes. …”
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Medical sign language translator in healthcare facility using yolo version 7 algorithm / Nurin Qistina Zaini
Published 2023“…In addition, people who work worked at a front desk in healthcare institutions also have a limited knowledge on this sign language. Hence, this creates barrier for these impairment people to do communication in their daily activities, especially when dealing at the healthcare facility. …”
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IMPACT OF NUMBER OF ATTRIBUTES ON THE ACCURACY OF HUMAN MOTION CLASSIFICATION
Published 2018“…The impact of the number of attributes on classification accuracy is evaluated via Bayes, Function, Lazy, Meta, Rule and Trees classifier algorithms supported by the WEKA tool. …”
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