Data and code resources. by Sam Hall-McMaster (10343795)

“…These findings point to a possible neural implementation of an adaptive algorithm for generalization across tasks.…”

Validation tests of feature decoding during the associative memory paradigm. by Sam Hall-McMaster (10343795)

Evaluating and Improving Light Absorption Retrievals of Black Carbon Using In Situ Polar Nephelometry by Qizhi Xu (1729057)

“…In situ polar nephelometry provides a unique opportunity to improve these retrieval algorithms. …”

Comparison of city decoders trained on session one and session two data. by Sam Hall-McMaster (10343795)

Validation of the neural decoding pipeline. by Sam Hall-McMaster (10343795)

Decoding evidence for policies on each individual test task. by Sam Hall-McMaster (10343795)

Decoding results. by Sam Hall-McMaster (10343795)

Behavioral results. by Sam Hall-McMaster (10343795)

Choices on individual test tasks were not explained by model-free perseveration. by Sam Hall-McMaster (10343795)

Reward outcomes for each combination of task cue and policy in the experiment. by Sam Hall-McMaster (10343795)

Post scan feature estimates and confidence ratings. by Sam Hall-McMaster (10343795)

Associative memory paradigm used to train the feature decoders. by Sam Hall-McMaster (10343795)

Decoding evidence for feature triplets on test tasks. by Sam Hall-McMaster (10343795)

“…This figure shows average decoding evidence for features associated with the more and less rewarding training policies on test trials (y-axis) as a function of brain region (x-axis). Feature information could not be decoded above chance in the four brain regions of interest (corrected <i>p-</i>values > 0.05). …”

Learning dynamics on training tasks. by Sam Hall-McMaster (10343795)

Choice behavior on individual test tasks. by Sam Hall-McMaster (10343795)

The GA iteration result. by Jiaqing Huang (5018492)

“…<div><p>Accurate risk assessment in international trade settlement has become increasingly critical as global financial transactions grow in scale and complexity. This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

GA crossover and mutation process. by Jiaqing Huang (5018492)

“…<div><p>Accurate risk assessment in international trade settlement has become increasingly critical as global financial transactions grow in scale and complexity. This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

The framework for the proposed model and GA-FNN. by Jiaqing Huang (5018492)

“…<div><p>Accurate risk assessment in international trade settlement has become increasingly critical as global financial transactions grow in scale and complexity. This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

The structure for the FNN. by Jiaqing Huang (5018492)

“…<div><p>Accurate risk assessment in international trade settlement has become increasingly critical as global financial transactions grow in scale and complexity. This study proposes a hybrid model—Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)—to enhance bank risk identification within this context. …”

Data Sheet 1_Hybrid machine learning algorithms accurately predict marine ecological communities.pdf by Luciana Erika Yaginuma (10477013)

“…In the supervised stage, these associations were modeled as a function of the environmental features by five supervised algorithms (Support Vector Machine, Random Forest, k-Nearest Neighbors, Naive Bayes, and Stochastic Gradient Boosting), using 80% of the samples for training, leaving the remaining for testing. …”