Search Results - (( intelligence a ((dea algorithm) OR (bee algorithm)) ) OR ( intelligence based tree algorithm ))*
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Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
Published 2018“…Apart from that, sizing algorithm with DEA was also discovered to outperform sizing algorithms with selected computational intelligence, i.e. …”
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Optimal design of step – cone pulley problem using the bees algorithm
Published 2021“…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach
Published 2024Subjects:Conference Paper -
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Application of the bees algorithm to the selection features for manufacturing data
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A true annealing approach to the marriage in honey-bees optimization algorithm
Published 2003“…Marriage in Honey-Bees Optimization is a new swarm intelligence technique inspired by the marriage process of honey-bees. …”
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Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm
Published 2021“…The optimized parameter can be feed to a controller to provide a room with ambient intelligence.…”
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Development of a Prediction Algorithm using Boosted Decision Trees for Earlier Diagnoses on Obstructive Sleep Apnea
Published 2018“…This research develops a knowledge-based system by using computational intelligent approaches based on Boosting algorithms on decision trees augmented by pruning techniques and Association Rule Mining. …”
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E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm
Published 2022“…The model design is Decision Tree (DT) algorithm-based, with an approach to data balancing since the data set used is highly unbalanced and one more approach for feature selection. …”
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Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm
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Application of the Bees Algorithm to find optimal drill path sequence
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
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Combination of adaptive enlargement and reduction in the search neighbourhood in the bees algorithm
Published 2014“…The Bees Algorithm, a heuristic optimisation procedure that mimics bees foraging behaviour, is becoming more popular among swarm intelligence researchers. …”
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Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm
Published 2014“…Moreover, cache pollution is a drawback of traditional web caching policies such as Least Frequently Used (LFU), Least Recently Used (LRU), and Greedy Dual Size (GDS) where web objects that are stored in the cache are not visited frequently. In this work, new intelligent cooperative web caching approaches based on decision tree supervised machine learning algorithm are presented. …”
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A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli
Published 2018“…The hybrid algorithm employed the Simple Constrained Artificial Bee Colony (SCABC) algorithm, using swarm intelligence as an optimization algorithm to optimize the objective function, where lactate and succinate productions are maximized by simulating gene knockout in E. coli. …”
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Algorithm in the fluidized-bed reactor for the polymerization of propylene
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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