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

The pareto front obtained by each algorithm. by Xiaohua Zeng (793632)

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. …”

Fitness curves for each algorithm. by Minan Tang (20389941)

Iteration curves of each algorithm. by Peng Yao (448155)

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)

Parameters of each algorithm. by Nanqi Li (11640083)

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. …”

The storage cost of each algorithm. by Shahzad Khan (15275200)

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. …”

The evaluation results of each model after five independent operations. by Bo Ni (1298154)

Model coefficients for each feature. by Amirmohammad Shahbandegan (14265549)

CPU runtime and accuracy for each model. by Minan Tang (20389941)

Overall rankings of optimization algorithms. by Máté Mohácsi (20469514)

Classification accuracy for each model test set. by Minan Tang (20389941)

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

The ANFIS algorithm details. by Mohammadmahdi Taheri (21722285)

“…For this problem, in the first stage 27 stocks were selected as samples from the (TSE) website using the proposed methods, and 23 stocks were entered into the price prediction stage. Finally, in the FGP stage, optimization and purchase amount of each share was done. …”

Model results for daily COVID-19 caused deaths after every step of the iterative optimization algorithm. by Martin Bicher (10852788)

Overall rankings of single-objective optimization algorithms. by Máté Mohácsi (20469514)

Model results for daily COVID-19 caused deaths for simulations performed during the second step of the optimization algorithm. by Martin Bicher (10852788)