Feature selection algorithm. حسب Mahmoud Zeydabadinezhad (12289570)

الموضوعات:

Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

الموضوعات:

Features selected by optimization algorithms. حسب Afnan M. Alhassan (18349378)

"…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. The suggested strategy facilitates the acquisition of precise functionality attributes, hence simplifying the detection procedure. …"

Eight commonly used benchmark functions. حسب Guangwei Liu (181992)

"…The proposed algorithm was evaluated on eight standard benchmark functions, CEC2019 benchmark functions, four engineering design problems, and a PID parameter optimization problem. …"

Flowchart of DAPF-RRT algorithm. حسب Zhenggang Wang (1753657)

الموضوعات: "…target gravitational function…"

Performance comparison of different algorithms. حسب Zhenggang Wang (1753657)

الموضوعات: "…target gravitational function…"

Hybrid feature selection algorithm of CSCO-ROA. حسب Afnan M. Alhassan (18349378)

"…Next, we propose a hybrid chaotic sand cat optimization technique, together with the Remora Optimization Algorithm (ROA) for feature selection. The suggested strategy facilitates the acquisition of precise functionality attributes, hence simplifying the detection procedure. …"

Comparison of deconvolution and optimization algorithms on a batch of data. حسب Ali-Kemal Aydin (10968731)

"…Both experimental data have been resampled at 50ms and used to compute a set of TFs (in orange) either with direct deconvolution approaches (Fourier or Toeplitz methods, middle-upper panel TFs) or with 1-Γ function optimization performed by 3 different algorithms (middle-lower panel TFs). …"

The eVIP algorithm uses RNA-seq data to predict the function of somatic mutations. حسب Alexis M. Thornton (11068403)

الموضوعات:

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

الموضوعات:

Scenarios for algorithms using IEEE 33 bus. حسب Bachirou Bogno (20485724)

Scenarios for algorithms using IEEE 69 bus. حسب Bachirou Bogno (20485724)

Pseudo-code of DMDDPG algorithm. حسب Guohua Cao (697580)

"…First, we analyze the stages of hole-seeking, alignment, and insertion in the shaft-hole assembly process, based on a comprehensive study of the interactions between shafts and holes. Next, a reward function is designed by integrating the decoupled multi-agent deterministic deep deterministic policy gradient (DMDDPG) algorithm. …"

In this example the MPC algorithm perfectly tracks the noisy signal , which results in many false spikes. حسب Nicholas A. Rondoni (21573261)

الموضوعات:

Standard functions to test. حسب Kemal Gökhan Nalbant (18858009)

Efficient algorithms to discover alterations with complementary functional association in cancer حسب Rebecca Sarto Basso (6728921)

"…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …"

Tuned parameters of algorithms. حسب Kaveh Faraji Googerdchi (18778727)

Algorithm Parameter Setting. حسب Tong Zhou (3770)

"…This strategy uses the improved D3QN algorithm combined with the excellent smoothness of the sine function to evaluate driving safety, helping vehicles find suitable gaps in traffic flow. …"

Continuous Probability Distributions generated by the PIPE Algorithm حسب LUIS G.B. PINHO (14073372)

"…<div><p>Abstract We investigate the use of the Probabilistic Incremental Programming Evolution (PIPE) algorithm as a tool to construct continuous cumulative distribution functions to model given data sets. …"

23 benchmark functions. حسب Yu Liu (6938)

"…<div><p>The competition of tribes and cooperation of members algorithm (CTCM) is a novel swarm intelligence algorithm, which increases the diversity of the population to a certain extent through tribal competition and member cooperation mechanisms. …"