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:

Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

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

Binary encoding scheme. by Binh Thanh Dang (12368831)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

“…<div><p>An image classification algorithm based on adaptive feature weight updating is proposed to address the low classification accuracy of the current single-feature classification algorithms and simple multifeature fusion algorithms. …”

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple tea fields.XLSX by Yangyang Liu (807797)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”

CSTP-MAC algorithm backoff time-slots vs IEEE 802.15.4 binary backoff exponential algorithm backoff time-slots. by Innocent Uzougbo Onwuegbuzie (9243166)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

Subjects:

Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

<i>De Novo</i> Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization by Alberga Domenico (9356272)

“…In the present study, we conceived a novel pair-based multiobjective approach implemented in an adapted SMILES generative algorithm based on recurrent neural networks for the automated <i>de novo</i> design of new molecules whose overall features are optimized by finding the best trade-offs among relevant physicochemical properties (MW, logP, HBA, HBD) and additional similarity-based constraints biasing specific biological targets. …”

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

DE algorithm flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Test results of different algorithms. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

ROC comparison of machine learning algorithm. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”