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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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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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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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4
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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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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6
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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9
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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10
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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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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Grammar-based prosody modification for explicit control Malay language storytelling speech synthesis / Muhammad Izzad Ramli
Published 2018“…Using Harmonic Noise Model (HNM) as the synthesizer, the grammar-based prosody modification rules are used to produce the synthesized storytelling speech. …”
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15
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…By considering these limitations, two modifications were made upon the conventional MVO in our proposed mMVO algorithm. …”
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16
Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques
Published 2011“…Unfortunately, the traditional mechanisms designed for protecting networks are not directly applicable to MANETs without modifications. In the past decades, machine learning methods have been successfully used in several intrusion detection methods because of their ability to discover and detect novel attacks. …”
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17
Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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18
Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives
Published 2025“…The results also suggest that it is feasible to implement a single type of model developed using the Matern 5/2 GPR algorithm for accurately predicting all the TB-CRMB properties considered. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. …”
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Development of an Adaptive Algorithm for Solving the Inverse Kinematics Problem for Serial Robot Manipulators
Published 2005“…The proposed technique does not require any prior knowledge of the kinematics model of the system being controlled; the main idea of this approach is the use of an Artificial Neural Network to learn the robot system characteristics rather than having to specify an explicit robot system model.Since one of the most important problems in using Artificial Neural Networks, is the choice of the appropriate networks' configuration, two different networks' configurations were designed and tested, they were trained to learn desired set of joint angles positions from a given set of end effector positions. …”
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