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

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

One advantage of our algorithm is that it is not binary in nature. حسب 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. حسب Olaide N. Oyelade (14047002)

الموضوعات:

Binary encoding scheme. حسب Binh Thanh Dang (12368831)

MSE for ILSTM algorithm in binary classification. حسب 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. …"

DE algorithm flow. حسب 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. …"

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

Test results of different algorithms. حسب 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. …"

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 حسب Yangyang Liu (807797)

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

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

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

Table 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"

Presentation 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"

Table 2_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.pdf حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"

Image 1_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.png حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"

Image 2_A computational framework for optimizing mRNA vaccine delivery via AI-guided nanoparticle design and in silico gene expression profiling.png حسب Valentina Di Salvatore (6296114)

"…Parallelly, we trained a Random Forest regression model on simulated lipid nanoparticles formulations to predict immune activation values and embedded this model into a genetic algorithm to identify optimal lipid nanoparticles design parameters (size, charge, polyethylene glycol content, and targeting). …"

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

الموضوعات:

Algorithm for generating hyperparameter. حسب 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. …"