Matlab code of a version using numerical optimization for Q. by Hiroko Kato Solvang (5718250)

R code for a version using numerical optimization for Q. by Hiroko Kato Solvang (5718250)

Homomorphic binary tree. by Jianhua He (341366)

“…The wavelet reconstruction algorithm can simulate all kinds of fast changes in the actual working process more accurately and compress irrelevant information while retaining key signal features, so as to optimize the simulation performance of the model. …”

Examples of random events and the respective binary outcome. by Matheus Sant’Ana Lima (9937809)

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

Algorithm optimization process. by Zhihao Li (359073)

“…Subsequently, fuzzy controllers for the driving charging mode and hybrid driving mode are designed under this rule-based EMS. Finally, the improved DBO is used to obtain the optimal control of the fuzzy controller by taking the fuel consumption of the whole vehicle and the fluctuation change of the battery state of charge (<i>SOC</i>) as the optimization objectives. …”

Optimization results of different algorithms. by Haijian Wang (746739)

“…Finally, the effectiveness of the optimization results was verified using simulation experiments. …”

Illustration of the continuation algorithm used for optimization in the inversion method. by Karoline Horgmo Jæger (6785450)

Optimization flow chart of the AO algorithm. by Haijian Wang (746739)

“…Finally, the effectiveness of the optimization results was verified using simulation experiments. …”

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

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... by Yangyang Liu (807797)

“…Simulation tests reveal that the dynamic genetic algorithm with ant colony binary iterative optimization (DGA-ACBIO) proposed in this study shortens the optimal flight range by 715.8 m, 428.3 m, 589 m, and 287.6 m compared to the dynamic genetic algorithm, ant colony binary iterative algorithm, artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO), respectively, for multiple tea field scheduling route planning. …”

An example of a type of texture of binary preferred/non-preferred ranges of raw vegetation index values type feature. by Elise Varaela Voltura (17592996)

Iteration curves of different algorithms. by Tengfei Ma (597633)

Flowchart of OP-ZOA algorithm. by Tengfei Ma (597633)

Flowchart of the operation of TLK-DBO algorithm. by Zhihao Li (359073)

“…Subsequently, fuzzy controllers for the driving charging mode and hybrid driving mode are designed under this rule-based EMS. Finally, the improved DBO is used to obtain the optimal control of the fuzzy controller by taking the fuel consumption of the whole vehicle and the fluctuation change of the battery state of charge (<i>SOC</i>) as the optimization objectives. …”

Algorithms runtime comparison. by Meilin Zhu (688698)

“…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …”

Convergence factor <i>α</i> change graph. by ZeSheng Lin (20501356)

Solution results of different algorithms. by Meilin Zhu (688698)

“…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …”

ROC curve for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. …”

Confusion matrix for binary classification. by Nicodemus Songose Awarayi (18414494)

“…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. The model further showed superior results on binary classification compared with existing methods. …”