Prediction performance of different optimization algorithms. by Ali-Kemal Aydin (10968731)

“…<p>(A) 3 algorithms were compared in terms of the residuals of the cost function of the optimized TF on 7 mice datasets (Derivative free algorithm failed in optimizing a TF in a mouse). …”

Power flow and cost optimization with Improved PSO algorithm (b). by Muhammad Ahmad Iqbal (11851338)

Convergence curves of the voltage profile improvement by using (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

Subjects:

Convergence curves of voltage stability enhancement based on (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

Subjects:

Convergence curves of total fuel cost minimization based on (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

Subjects:

Convergence curve of reactive power transmission line loss minimization based on (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

Subjects:

Convergence curve of real power transmission line loss minimization by using (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

Subjects:

Power flow and cost optimization with APSO variant-16 of APSO algorithm (b). by Muhammad Ahmad Iqbal (11851338)

(a) Flow chart for PSO algorithm (b) position and velocity update of particles (c) convergence of PSO. by Waqas Anjum (8415186)

Continuous Probability Distributions generated by the PIPE Algorithm by LUIS G.B. PINHO (14073372)

“…The PIPE algorithm can generate several candidate functions to fit the empirical distribution of data. …”

Flow chart diagram of blind quantum algorithm. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Comparison of deconvolution and optimization algorithms on a batch of data. by Ali-Kemal Aydin (10968731)

“…Both experimental data have been resampled at 50ms and used to compute a set of TFs (in orange) either with direct deconvolution approaches (Fourier or Toeplitz methods, middle-upper panel TFs) or with 1-Γ function optimization performed by 3 different algorithms (middle-lower panel TFs). …”

VFH algorithm flow chart. by Qing Liang (654718)

“…In this paper, we mainly propose an obstacle avoidance method composed of three modules: environment perception, algorithm obstacle avoidance and motion control. Our method realizes the function of reasonable and safe obstacle avoidance of UAV in low-altitude complex environments. …”

Flow chart diagram of quantum hash function. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Completion times for different algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

Simulation settings of rMAPPO algorithm. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. …”

Model intrinsic parameter flow. by Dawei Wang (471687)

“…A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. …”

Iteration versus fitness function. by B. Venkatesh (17202747)