Diagram of the GWO algorithm [72]. by Seyed Majid Hasani Azhdari (18476088)

Image 1_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”

Image 2_A novel inversion method of slope rock mechanical parameters using differential evolution gray wolf algorithm to optimize support vector regression.tif by Tingkai Hou (21014762)

“…</p>Methods<p>This paper proposes a displacement back-analysis (DBA) approach that utilizes support vector regression (SVR) optimized by differential evolution grey wolf algorithm (DE-GWO) to invert the RMMPs, which improves global optimization capability and inversion accuracy. …”

W₁ output by meta-heuristic algorithms. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i>_<i>δ</i>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i>_<i>δ</i>, <i>hi</i>PRS constructs <i>I</i>_<i>K</i>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …”

Statistical results of various algorithms. by ZeSheng Lin (20501356)

“…Furthermore, inspired by the grey wolf optimization algorithm, use 3 excellent particle surround strategies instead of the original random selecting particles. …”

Flowchart of KELM parameters optimized by EAWOA. by ZeSheng Lin (20501356)

“…Furthermore, inspired by the grey wolf optimization algorithm, use 3 excellent particle surround strategies instead of the original random selecting particles. …”

Main contributions. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

The minimum data set. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

Codes and related data. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

Key hyper-parameters. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

Bubble-net hunting behavior. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

BP neural network structure diagram. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

CA-WOA-BPNN model. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

The importance between 6 factors and V₀. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

Basic data of sixty debris flows. by Bo Ni (1298154)

“…Then, the improved whale optimization algorithm optimizes the final weights and thresholds in the back propagation neural network. …”

Time complexity. by Xiaotong Bai (19819284)

“…In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum Chi-Square and ReliefF Improved Grey Wolf Optimization algorithm (TMKMCRIGWO). …”

Datasets information. by Xiaotong Bai (19819284)

“…In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum Chi-Square and ReliefF Improved Grey Wolf Optimization algorithm (TMKMCRIGWO). …”

Parameter settings. by Xiaotong Bai (19819284)

“…In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum Chi-Square and ReliefF Improved Grey Wolf Optimization algorithm (TMKMCRIGWO). …”

Minimum Chi-Square value. by Xiaotong Bai (19819284)

“…In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum Chi-Square and ReliefF Improved Grey Wolf Optimization algorithm (TMKMCRIGWO). …”