Datasets and their properties. by Olaide N. Oyelade (14047002)

“…<div><p>Feature selection problem represents the field of study that requires approximate algorithms to identify discriminative and optimally combined features. …”

Optimization algorithm comparison. by Wang Linfeng (17102068)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

Subjects:

RE for partial flow prediction results of single and dual water level models based on the GA-BP algorithm. by Xiying Wang (4859998)

Optimization results of MBB multi-material structure under different methods. (a) A level-set method for multi-material topology optimization [33].... by Zhao Li (300229)

“…(a) A level-set method for multi-material topology optimization [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0321100#pone.0321100.ref033" target="_blank">33</a>]. …”

Parameter settings. by Qingbo Tu (22641033)

“…<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning methods. …”

Indicator settings. by Qingbo Tu (22641033)

“…<div><p>To improve the intelligent and refined management level of power distribution systems in equipment operation and maintenance as well as emergency support, this work proposes an integrated “prediction-optimization” model that combines genetic algorithm (GA) with machine learning methods. …”

Parameter sets of the chosen algorithms. by WanRu Zhao (18980374)

“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”

The flow chart of IERWHO algorithm. by WanRu Zhao (18980374)

“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”

The flow chart of WHO algorithm. by WanRu Zhao (18980374)

“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”

Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”

The convergence curves of all the 10 algorithms. by WanRu Zhao (18980374)

“…According to the encouraging research results in this paper, the IERWHO algorithm proposed has a place in the field of optimization.…”

Algorithm flow of the GA-BPNN model. by Xiying Wang (4859998)

“…<div><p>This work explores an intelligent field irrigation warning system based on the Enhanced Genetic Algorithm—Backpropagation Neural Network (EGA-BPNN) model in the context of smart agriculture. …”

AI Algorithm Workflow: Image pre-processing with highest pixel intensity identification (a), RGB channel breakdown, Fluorescence isolation and grayscale conversion (b), Computation... by Gareth Gallagher (20874910)

Data_Sheet_1_A Global Optimizer for Nanoclusters.PDF by Maya Khatun (7437011)

“…This method is implemented in PyAR (https://github.com/anooplab/pyar) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries. …”

Unsupervised Machine Learning Neural Gas Algorithm for Accurate Evaluations of the Hessian Matrix in Molecular Dynamics by Michele Gandolfi (11613834)

“…The algorithm belongs to the family of unsupervised machine learning methods, and it is based on the neural gas idea, where neurons are molecular configurations whose Hessians are adopted for groups of molecular dynamics configurations with similar geometries. …”

SNR comparison of real-field seismic profile. by Zhenjing Yao (22189970)

“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”

Table 2_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.docx by Xinrui Wang (488330)

“…</p>Methods<p>In this study, we propose an intelligent method for identifying sugarcane foliar disease severity based on physiological traits. Field-collected data—including Soil and Plant Analyzer Development (SPAD) values, leaf surface temperature, and nitrogen content—were acquired using a plant nutrient analyzer (TYS-4N) from sugarcane leaves infected with brown stripe disease, ring spot disease, and mosaic disease at four severity levels (mild, moderate, moderately severe, and severe). …”

Table 1_Intelligent grading of sugarcane leaf disease severity by integrating physiological traits with the SSA-XGBoost algorithm.xlsx by Xinrui Wang (488330)

“…</p>Methods<p>In this study, we propose an intelligent method for identifying sugarcane foliar disease severity based on physiological traits. Field-collected data—including Soil and Plant Analyzer Development (SPAD) values, leaf surface temperature, and nitrogen content—were acquired using a plant nutrient analyzer (TYS-4N) from sugarcane leaves infected with brown stripe disease, ring spot disease, and mosaic disease at four severity levels (mild, moderate, moderately severe, and severe). …”

Kurtograms of different signals. by Hang Zhao (143592)