Search Results - (( pattern prediction model algorithm ) OR ( java application using algorithm ))
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Financial time series predicting using machine learning algorithms
Published 2013“…Therefore, the findings of this research help in improving the accuracy of prediction model.…”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2023“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
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A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm.
Published 2009“…In this paper, to provide online predicting effectively, we develop a model for online predicting through web usage mining system and propose a novel approach for classifying user navigation patterns to predict users’ future intentions. …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Book Section -
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Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier
Published 2013“…FP-Growth (frequent pattern growth) algorithm was employed as a feature extraction technique. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…The selected algorithms effectively show increase in prediction performance with decreasing features. …”
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A Web-Based Recommendation System To Predict User Movements Through Web Usage Mining
Published 2009“…The approach in the offline phase is based on the new graph partitioning algorithm to model user navigation patterns for the navigation patterns mining. …”
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A new classification model for online predicting users' future movements
Published 2008“…To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. …”
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Predicting Cheaters in PlayerUnknown’s Battlegrounds (PUBG) using Random Forest Algorithm
Published 2023“…Utilising the selected features, the Random Forest model is then trained to produce a robust prediction model. …”
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Final Year Project Report / IMRAD -
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…To address these challenges, this study proposes a hybrid prediction model that combines the salp-swarm algorithm and the artificial neural network (SSA-ANN). …”
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Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
Published 2013“…Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and learned by Artificial Neural Network algorithm, and Dynamic Time Warping algorithm is used to predict the near future trends.Our experiment result shows a satisfactory result using the proposed approach.…”
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Conference or Workshop Item -
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New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks
Published 2024“…Traditional single machine learning models struggle to capture complex temporal patterns, especially considering the influence of vaccination campaigns on confirmed cases, leading to suboptimal predictions. …”
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Computing the autopilot control algorithm using predictive functional control for unstable model
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction
Published 2025“…These findings highlight the effectiveness of adaptive and genetic algorithms in enhancing LSTM model performance for VLE prediction, offering valuable insights for educational technology advancement.…”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
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Artificial neural network model for predicting windstorm intensity and the potential damages / Mohd Fatruz Bachok
Published 2019“…In addition, the mean square error (MSE) values for ANN model algorithms (pattern recognition tool) for 5 prediction processes are low from 0.00 to 0.0286 and errors from 0.00 to 0.0309. …”
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