Predictions from a Universal Value Function Approximator (UVFA) algorithm. by Sam Hall-McMaster (10343795)

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Performance profile of the four algorithms based on the function value of iteration number. by Sulaiman M. Ibrahim (20614376)

“…<p>Performance profile of the four algorithms based on the function value of iteration number.…”

Sensor value scenario for average value algorithm. by Gourab Saha (8987405)

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23 benchmark functions. by Yu Liu (6938)

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Sensor value scenario for fuzzy logic algorithm. by Gourab Saha (8987405)

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The function value of the single objective optimal solution. by Yuhang Wang (332111)

ANOVA tests for Benchmark functions. by Yu Liu (6938)

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The Wilcoxon results for Benchmark functions. by Yu Liu (6938)

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Convergence graphs of Benchmark functions. by Yu Liu (6938)

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DMTD algorithm. by Yunhu Huang (21402795)

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PFC value of algorithms on two datasets. by Xing Chen (140292)

“…<div><p>In daily life, two common algorithms are used for collecting medical disease data: data integration of medical institutions and questionnaires. …”

Water consumption due to average value and fuzzy logic algorithm. by Gourab Saha (8987405)

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Convergence graphs of CEC2021 test functions. by Yu Liu (6938)

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Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

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Benchmark function. by Kuiyuan Pan (21145338)

Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value. by Alexandria M. Jensen (6494957)

Subjects: “…community detection algorithms…”

Genetic algorithm flowchart. by Junjie He (700642)

Subjects: “…coverage attenuation function…”

The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…First, physico-chemical inputs as bulk density (BD), initial water content (W_i), saturated water content (W_s), mean weight diameter (MWD), and geometric mean diameter (GMD) of aggregates, pH, electrical conductivity (EC), and calcium carbonate equivalent (CCE) were measured. Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

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Completion times for different algorithms. by Jianbin Zheng (587000)

“…Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”