A convolution-LSTM-based deep neural network for cross-domain MOOC forum post classification
Learners in a massive open online course often express feelings, exchange ideas and seek
help by posting questions in discussion forums. Due to the very high learner-to-instructor …
help by posting questions in discussion forums. Due to the very high learner-to-instructor …
An adaptive Gaussian process based manifold transfer learning to expensive dynamic multi-objective optimization
Expensive dynamic multi-objective optimization problems (EDMOPs) is one kind of DMOPs
where the objectives change over time and the function evaluations commonly involve …
where the objectives change over time and the function evaluations commonly involve …
[HTML][HTML] Short-term electric load prediction using transfer learning with interval estimate adjustment
Although we are currently in the era of big data, it is always challenging to obtain complete
and large-scale data due to the information protection for users and enterprises. In most …
and large-scale data due to the information protection for users and enterprises. In most …
Transfer-learning based gas path analysis method for gas turbines
S Tang, H Tang, M Chen - Applied Thermal Engineering, 2019 - Elsevier
Data-driven gas path analysis is a state-of-health diagnostic method. The method utilizes
input-output information to solve the health assessment problem of gas turbine engines. In …
input-output information to solve the health assessment problem of gas turbine engines. In …
[HTML][HTML] CO2 emission based GDP prediction using intuitionistic fuzzy transfer learning
The industrialization has been the primary cause of the economic boom in almost all
countries. However, this happened at the cost of the environment, as industrialization also …
countries. However, this happened at the cost of the environment, as industrialization also …
From discourse to narrative: Knowledge projection for event relation extraction
Current event-centric knowledge graphs highly rely on explicit connectives to mine relations
between events. Unfortunately, due to the sparsity of connectives, these methods severely …
between events. Unfortunately, due to the sparsity of connectives, these methods severely …
A general domain specific feature transfer framework for hybrid domain adaptation
Heterogeneous domain adaptation needs supplementary information to link up different
domains. However, such supplementary information may not always be available in real …
domains. However, such supplementary information may not always be available in real …
Coupled local–global adaptation for multi-source transfer learning
This paper presents a novel unsupervised multi-source domain adaptation approach,
named as coupled local–global adaptation (CLGA). At the global level, in order to maximize …
named as coupled local–global adaptation (CLGA). At the global level, in order to maximize …
A critical survey of GEOBIA methods for forest image detection and classification
C Kwenda, MV Gwetu, JV Fonou-Dombeu - Geocarto International, 2023 - Taylor & Francis
Modern earth observation sensors have revolutionized the remote sensing community by
improving remote sensing image quality. However, Pixel-based image analysis methods …
improving remote sensing image quality. However, Pixel-based image analysis methods …
Deep autoencoder based domain adaptation for transfer learning
The concept of transfer learning has received a great deal of concern and interest
throughout the last decade. Selecting an ideal representational framework for instances of …
throughout the last decade. Selecting an ideal representational framework for instances of …