Prediction performance of different optimization algorithms. حسب 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). …"

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

"…Output is given by the vascular response, measured as the change in speed of red blood cells flowing inside a capillary proximal to the recorded neuronal activation (in yellow, right panel). 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). …"

The image of the Aekley function. حسب Zhengyu Xu (8550660)

The ALO algorithm optimization flowchart. حسب Wenjing Wang (181404)

"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"

The IALO algorithm solution flowchart. حسب Wenjing Wang (181404)

"…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …"

The benchmark functions. حسب Shuhui Yu (1535500)

The pseudocode for the NAFPSO algorithm. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

PSO algorithm flowchart. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

Flowchart for Algorithm 1. حسب Sagvan Y. Musa (17797611)

Flowchart for Algorithm 2. حسب Sagvan Y. Musa (17797611)

Scheduling time of five algorithms. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

Convergence speed of five algorithms. حسب Huichao Guo (14515171)

"…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …"

General idea of alternative structures of aptamers binding the same ligand and its specific implementation scheme for the BioRS function. حسب Alexander V. Spirov (11302085)

Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

الموضوعات:

Completion times for different algorithms. حسب 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 effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"

The average cumulative reward of algorithms. حسب 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 effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …"

Feature selection algorithm. حسب Mahmoud Zeydabadinezhad (12289570)

"…Our analysis pipeline included pre-processing steps, feature extraction from both time and frequency domains, a voting algorithm for selecting features, and model training and validation. …"

CEC2017 basic functions. حسب Tengfei Ma (597633)

"…During experimental evaluation, the efficiency of OP-ZOA was verified using the CEC2017 test functions, demonstrating superior performance compared to seven recently proposed meta-heuristic algorithms (Bloodsucking Leech Algorithm (BSLO), Parrot Optimization Algorithm (PO), Polar Lights Algorithm (PLO), Red-tailed Hawk Optimization Algorithm (RTH), Bitterling Fish Optimization Algorithm (BFO), Spider Wasp Optimization Algorithm (SWO) and Zebra Optimization Algorithm (ZOA)). …"

Algorithm process of BPNN. حسب Xiaoxiang Cao (12644851)

Automatic cropping algorithm. حسب Thomas W Georgi (12427189)