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Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…The performance of three machine learning (ML) algorithms was assessed to predict the wild blueberry harvest losses on the ground. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…In this study, the emergency control algorithms based on ensemble machine learning algorithms (XGBoost and Random Forest) were developed for a low-inertia power system. …”
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Efficient Algorithms for Constructing Preset Distinguishing Sequences for Nondeterministic Finite State Machines
Published 2016Subjects: Get full text
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Android Malware Detection Using Machine Learning
Published 2024“…In this work, several machine learning algorithms were utilized, namely k-Nearest neighbor (KNN), Decision Trees (DT), Naive Bayes (NB), Support Vector Machine (SVM) and other ensemble classifiers including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM) and CatBoost. …”
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An Optimized Feature Selection Technique in Diversified Natural Scene Text for Classification Using Genetic Algorithm
Published 2021“…The Support Vector Machine (SVM) algorithm is used for classification and the average F-Score is used as fitness function and target condition. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…GA is enhanced by adding a multi-objective function, which selects the best features and achieves improved fitness outcomes to explore the essential features and helps minimize dimensions, enhance the true positive rate (TPR), and lower the false positive rate (FPR). …”
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Using machine learning algorithm for detection of cyber-attacks in cyber physical systems
Published 2022“…In the event of a violation in internet security, an attacker was able to interfere with the system's functions, which might result in catastrophic consequences. …”
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Evolution Of Activation Functions for Neural Architecture Search
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Multi-Target Tracking Resources Allocation Using Multi-Agent Modeling and Auction Algorithm
Published 2023“…The results show an optimum resource allocation with an information-based cost function that is optimized by an Auction Algorithm.…”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The main objective of this paper is to apply GOA to estimate the optimal parameters of the Gaussian membership function in an IT2-FLS. The antecedent part parameters (Gaussian membership function parameters) are encoded as a population of artificial swarm of grasshoppers and optimized using its algorithm. …”
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Ensemble Deep Random Vector Functional Link Neural Network for Regression
Published 2022“…<p dir="ltr">Inspired by the ensemble strategy of machine learning, deep random vector functional link (dRVFL), and ensemble dRVFL (edRVFL) has shown state-of-the-art results on different datasets. …”
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…The research work carried out, in relation to attack detection ensemble learning, mainly aims to increase the performance of machine learning algorithms by combining their results. …”
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Iterative Least Squares Functional Networks Classifier
Published 2007“…A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. …”
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A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models
Published 2024“…The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
Published 2017Get full text
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Boosting the visibility of services in microservice architecture
Published 2023“…Experimental results demonstrated that the CatBoost algorithm achieved the highest level of accuracy (90.42%) in predicting microservice quality.…”
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Machine Learning Model for a Sustainable Drilling Process
Published 2023Get full text
doctoralThesis