The structural mutation of neuroevolution. by Wenbing Shi (5806160)

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The CGO risk prediction process based on data augmentation and neuroevolution. by Wenbing Shi (5806160)

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Evaluation indexes of different methods on the test set. by Wenbing Shi (5806160)

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The speciation of ANEAT model evolution. by Wenbing Shi (5806160)

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The analysis of feature importance. by Wenbing Shi (5806160)

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S1 Data - by Wenbing Shi (5806160)

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The parameter setting of the evolutionary neural network. by Wenbing Shi (5806160)

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The fitness of ANEAT model evolution. by Wenbing Shi (5806160)

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The structure of the ANEAT model corresponds to the optimal species genome. by Wenbing Shi (5806160)

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The construction process of the CGO prediction model. by Wenbing Shi (5806160)

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The comparison of different prediction methods on the test set. by Wenbing Shi (5806160)

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The structure of the data sample. by Wenbing Shi (5806160)

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The genome recombination of neuroevolution. by Wenbing Shi (5806160)

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The principle of sample data augmentation. by Wenbing Shi (5806160)

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The fitness of NANEAT model evolution. by Wenbing Shi (5806160)

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The speciation of NANEAT model evolution. by Wenbing Shi (5806160)

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Code by Baoqiang Chen (21099509)

SpeLL: An Agent for Natural Language-Driven Intelligent Spectral Modeling by Jiashun Fu (20888176)

“…The core strength of SpeLL lies in its dual RAG pathways. The Code RAG provides specialized code knowledge for spectral data analysis, enabling the LLM to generate robust and domain-specific analytical scripts that address the implementation and optimization of algorithms. …”

Elementary effects (EE) results for chorionic vessel generation employing the input parameter ranges from Table 1. by Diana C. de Oliveira (9220729)

data and code by PENGCHENG LIU (20680641)