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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…Therefore, it is essential to develop a new technique to authenticate access to database related to web applications and prevent SQL injection vulnerabilities. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In addition, the best band selected for image classification is not necessarily the best for classification.A Best Band Selection Index (BBSI) algorithm was developed which is capable of selecting the best band combination for image visualization and supervised classification. …”
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Improvement and performance analysis on statistical selection algorithms
Published 2006“…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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Model structure selection for a discrete-time non-linear system using genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Statistical selection algorithm for peer-to-peer system
Published 2008“…Over the years, the distributed database has been developed so fast that there's a need to develop an effective selection algorithm for it. …”
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Variable block based motion estimation using hexagon diamond full search algorithm (HDFSA) via block subtraction technique
Published 2015“…Overall, the developed algorithms have similar PSNR value and lower average search point compared to superior algorithms. …”
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Channel selection strategies for co-existence between wimax and wifi
Published 2009“…The utilization of spectrum is one of the critical issues in development of cognitive radio. Therefore, channel selection algorithm is developed to select the best operating band which can maximize the total system performances. …”
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ABC: android botnet classification using feature selection and classification algorithms
Published 2017“…In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm
Published 2004“…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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The Development of an Algorithm to Determine Axial Capacity of Piles from SPT N-Values
Published 2000“…The developed IT was used for all cases of algorithm testing. …”
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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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Development of genetic algorithm-based fuzzy rules design for metal cutting data selection
Published 2002“…The authors have developed fuzzy models for machinability data selection (Int. …”
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study
Published 2020“…Proposed cfsw-SVM algorithms are then developed. Proposed formulations on SVM regularization parameter provides synergistic adjustments between prediction or classification accuracy and the level of correlations among features in the SVM implemented. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Fuzzy Rules Optimization in Fuzzy Expert System for Machinability Data Selection: Genetic Algorithms Approach
Published 2001“…Fuzzy rules optimization is always a problems for a complex fuzzy rules from more than 10 thousand combinations. (Wong et aL 1997) developed fuzzy models for machinability data selection. …”
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Long term energy demand forecasting based on hybrid, optimization: Comparative study
Published 2012“…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Thus, this thesis has developed and evaluated a filter based Information Theoretic-based Feature Selection (IFS) for machine learning. …”
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