Optimize process data and final results by Dawei Wang (471687)

Final settings for the algorithms. by Raphael Souza de Oliveira (12647110)

Optimized process of the random forest algorithm. by Hongxia Li (493545)

“…Then, a training set is randomly selected from known coal mine samples, and the training sample set is processed and analyzed using Matlab software. Subsequently, a training model based on the random forest classification algorithm is constructed, and the model is optimized using two parameters, Mtry and Ntree. …”

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:

Binary encoding scheme. by Binh Thanh Dang (12368831)

Test performance metrics for the final model. by Ramona Leenings (11167294)

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

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

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”

Training process. by Ning Zhao (84707)

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)

Firefly optimization algorithm flowchart. by Zhengyu Xu (8550660)

“…And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. …”

The Search process of the genetic algorithm. by Wenguang Li (6528113)

“…The results show: (1) Random oversampling, ADASYN, SMOTE, and SMOTEENN were used for data balance processing, among which SMOTEENN showed better efficiency and effect in dealing with data imbalance. (2) The GA-XGBoost model optimized the hyperparameters of the XGBoost model through a genetic algorithm to improve the model’s predictive accuracy. …”

Evaluation of developed intrusion detection model with different heuristic algorithms. by P. M. Vijayan (17095147)

Particle swarm optimization algorithm flowchart. by Zhengyu Xu (8550660)

“…And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. …”

XGBoost algorithm training process. by Huijun Chen (148680)

The ANFIS algorithm details. by Mohammadmahdi Taheri (21722285)

“…These selected stocks are then moved to the second stage, where the ANFIS algorithm is employed in MATLAB to predict the final closing prices and calculate the prediction error (RMSE). …”

PID controller parameters optimization process. by Hongjun Meng (5031806)

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

“…A major challenge in bioprocess simulation is the lack of physical and chemical property databases for biochemicals. A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”

Genetic algorithm flowchart. by Jintao Meng (9455366)

“…Due to the fact that fuzzy rules are formulated through a large amount of on-site temperature data and experience summary, there is a certain degree of subjectivity, which cannot ensure that each rule is optimal. …”