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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…The outcome of this study will add to the body of knowledge the most important and recent proposed solutions to mitigate SQL injection attack, in particular those based on machine learning algorithm…”
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A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications
Published 2025“…Among the applied machine learning algorithms, the XGBoost ensemble model using the tenfold cross-validation test achieved improved results than existing state-of-the-art models. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…Over the years, many improvements and modifications of the back propagation learning algorithm have been reported. …”
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Provider independent cryptographic tools
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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9
Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Learning to filter text in forum message
Published 2005“…In this paper, the modification of the algorithm including pre-processing and classification will be discussed in the attempt to apply learning to filter forum messages.…”
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Three-term backpropagation algorithm for classification problem
Published 2006“…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Furthermore, the results revealed a high convergence rate, upon which the algorithm’s performance was subjected to data clustering problems and investigated using six real datasets. …”
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15
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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Direct approach for mining association rules from structured XML data
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2012“…To overcome this, a Functional Link Neural Networks (FLNN), which has single layer of trainable connection weight is used. The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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