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)

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

Schematic of iteration process of IDE-IIGA. by Ling Zhao (111365)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”

Iterative chart of control factor. by Ying Li (38224)

“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”

Table1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.docx by Haohan Xue (17892128)

“…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”

DataSheet1_Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.ZIP by Haohan Xue (17892128)

“…The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. …”

Parameter settings of the comparison algorithms. by Ying Li (38224)

“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”

UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level by Giovanni Nattino (561797)

“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”

<i>FS</i> index of KNN on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

<i>ACC</i> index of KNN on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

<i>FS</i> index of SVM on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

The flowchart of the IG-GPSO. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

<i>ACC</i> index of SVM on the selected feature subset. by Fangyuan Yang (2567629)

“…</p><p>Methods</p><p>Based on this, this paper proposes a hybrid feature selection algorithm combining information gain and grouping particle swarm optimization (IG-GPSO). …”

Image_2_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. …”

Image_1_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. …”

Image_3_A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.TIF by Qingqing Li (1505614)

“…First, we used the Fast Correlation-Based Filter (FCBF) algorithm to filter a large number of irrelevant and redundant genes in the raw dataset, and then used the wrapper feature selection method based on the he Multi-layer Perceptron (MLP) neural network and the Particle Swarm Optimization (PSO), accuracy (ACC) and mean square error (MSE) were then used as the evaluation criteria. …”

Comparison in terms of the sensitivity. by Ying Li (38224)

“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”

Parameter sensitivity of BIMGO. by Ying Li (38224)

“…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”