One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

Subjects:

S1 Data - by Haoqiang Liu (193675)

DataSheet1_Improving the convergence of an iterative algorithm for solving arbitrary linear equation systems using classical or quantum binary optimization.pdf by Erick R. Castro (11243697)

Binary contingency table. by Lu Xiao (314030)

Resilts of Friedman and Iman-Davenport tests (<i>α</i> = 0.05). by Nebojsa Bacanin (13932723)

S1 Dataset - Novel chaotic oppositional fruit fly optimization algorithm for feature selection applied on COVID 19 patients’ health prediction by Nebojsa Bacanin (13932723)

Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

Proposed Algorithm. by Hend Bayoumi (22693738)

“…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)

Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

Data_Sheet_1_Posiform planting: generating QUBO instances for benchmarking.pdf by Georg Hahn (12530469)

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

Subjects:

Binary leaf image rotated anti-clock wise from the origin degree to 40^<i>o</i>, 80^<i>o</i>, 120^<i>o</i>, and 160^<i>o</i> from left to ri... by Ali Ahmed (2567584)

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf by Sai Sakunthala Guddanti (17739363)

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…<b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …”

The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)