Steps involved in genetic algorithm for feature selection. by Mohd Sakib (20565228)

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

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)

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

Implementation steps of ICEEMDAN. by Beibei Hu (5347559)

Basic steps of ReliefF. by Xiaotong Bai (19819284)

Flow chart of particle swarm algorithm. by Nour Eldeen Mahmoud Khalifa (19259450)

“…However, the increasing yields also put a lot of pressure on the classification step afterward. Image recognition based on deep learning algorithms can help to identify and classify the date fruit species, even in natural light.…”

Summary of classification algorithms. by Stephen R. Piccolo (8367780)

Curve of step response signal of 6 algorithms. by Guangwei Liu (181992)

Methodological steps. by Luan Carlos de Sena Monteiro Ozelim (16914117)

Algorithm parameters. by Ruyi Dong (9038174)

“…Therefore, it can be shown that LLSKSO can be used as an effective optimization algorithm and engineering assistance.…”

Optimization of an Oil and Gas Separation Plant for Different Reservoir Fluids Using an Evolutionary Algorithm by Erik R. Olsen (10219987)

“…The optimization of an oil and gas separation plant operating revenue has been performed for different characteristic reservoir fluid types (gas condensate, volatile oil, and black oil) using an evolutionary algorithm. …”

Flow chart of the two-step method. by Dai Wan (20108122)

“…This paper first introduces an assessment model of maximum DG hosting capacity in distribution network based on optimal power flow (OPF). Then, a two-step method that combines the linearization method and the recursive method is proposed, which consists of two parts: firstly, using linearization method to quickly calculate the preliminary assessment value of maximum DG hosting capacity, and then using a recursive method to accurately correct the preliminary assessment value. …”

Parameter values of the compared algorithms. by Huimin Lu (4434682)

“…Then, we proposed a feature extraction method to extract time-frequency-based statistical (TF-ST) features from dynamic handwriting features in terms of their temporal and frequency characteristics. Finally, we proposed an escape Coati Optimization Algorithm (eCOA) for global optimization to enhance classification performance. …”

Summary of predictive performance per dataset when using gene-expression and clinical predictors and performing hyperparameter optimization. by Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using clinical predictors. by Stephen R. Piccolo (8367780)

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. …”

Summary of predictive performance per dataset when using gene-expression predictors. by Stephen R. Piccolo (8367780)

Summary of predictive performance per dataset when using gene-expression and clinical predictors. by Stephen R. Piccolo (8367780)