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Machine learning algorithms in context of intrusion detection
Published 2016“…These machine learning algorithms develop a detection model in a training phase. …”
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2
Particle swarm optimization for neural network learning enhancement
Published 2006“…To overcome this problem, Genetic Algorithm (GA) has been used to determine optimal value for BP parameters such as learning rate and momentum rate and also for weight optimization. …”
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3
Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…In conclusion, a deep reinforcement learning algorithm was successfully developed for the substrate feeding rate optimisation in the fed-batch baker’s yeast fermentation process. …”
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5
Differential evolution for neural networks learning enhancement
Published 2008“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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7
Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error as compared to a model with single learning algorithm.…”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…This paper proposed that, combination of two algorithms into one learning algorithm for predicting mass flow rate of a flow with leakage resulting in a better mass prediction error compare to a model with single learning algorithm.…”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms
Published 2022“…The development of Management Information Systems (MIS) is impossible without the use of machine learning (ML). …”
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]
Published 2023“…Then, the percentage of detection accuracy was used to compare the detection performance of all five algorithms. The detection accuracy is calculated using the confusion matrix, which includes the False Positive Rate (FPR), the True Positive Rate (TPR), and the False Negative Rate (FNR). …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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13
Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…Early detection of prostate cancer when it is confined to the prostate gland has the best chance of successful treatment and increase in surviving rate. Prostate cancer occurrence rate varies over the three prostate regions, peripheral zone (PZ), transitional zone (TZ), and central zone (CZ) and this characteristic is one of the important considerations is development of segmentation algorithm. …”
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Recent Automatic Segmentation Algorithms of MRI Prostate Regions: A Review
Published 2021“…Early detection of prostate cancer when it is confined to the prostate gland has the best chance of successful treatment and increase in surviving rate. Prostate cancer occurrence rate varies over the three prostate regions, peripheral zone (PZ), transitional zone (TZ), and central zone (CZ) and this characteristic is one of the important considerations is development of segmentation algorithm. …”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
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Integration of image processing algorithm and deep learning approaches to monitor ginger plant
Published 2024“…This study aims to integrate image processing and deep learning algorithms to monitor the growth of ginger plants. …”
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm
Published 2001“…In this thesis, factors that govern the learning speed of the backpropagation algorithm are investigated and mathematically analyzed in order to develop strategies to improve the performance of this neural network learning algorithm. …”
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An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa
Published 2020“…The developed algorithm is reported to be reliable to assist the radiologist in ischemic PF diagnosis which is important for future healthcare needs.…”
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