Search Results - (( developing data modeling algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…There are several techniques to mine association rules from XML data. The basic approach is to map the XML documents to relational data model and to store them in a relational database. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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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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Development of decentralized data fusion algorithm with optimized kalman filter.
Published 2016“…This thesis proposes a data fusion model that facilitates selection of algorithm and recommends selected algorithm to be optimized. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…Inference procedures are developed for modelling multiple events intervalcensored data through AFT models. …”
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Hybrid DE-PEM algorithm for identification of UAV helicopter
Published 2014“…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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Implementation of New Improved Round Robin (NIRR) CPU scheduling algorithm using discrete event simulation
Published 2015“…The main objective of this research is to validate the NIRR algorithm by developing a comprehensive simulation model using Discrete Event Simulation (DES). …”
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Classification model for hotspot occurrences using spatial decision tree algorithm
Published 2013“…We improved the ID3 decision tree algorithm such that it can be utilized on spatial data in order to develop a classification model for hotspots occurrence. …”
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Sentiment analysis using negative selection algorithm for Twitter’s messages / Nazirah Che Alhadi
Published 2012“…In order to develop this model classification and prototype, 480 Twitter’s messages were used as training data and 120 Twitter’s messages for testing data to determine the accuracy of the classification model. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The autoregressive model is a mathematical model that is often used to model data in different areas of life. …”
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Comparison between multi-objective and single-objective optimization for the modeling of dynamic systems
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Working Paper -
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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Conference or Workshop Item
