A survey of adaptive resonance theory neural network models for engineering applications
This survey samples from the ever-growing family of adaptive resonance theory (ART)
neural network models used to perform the three primary machine learning modalities …
neural network models used to perform the three primary machine learning modalities …
Adaptive and intelligent robot task planning for home service: A review
H Li, X Ding - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The uncertainty and dynamic of home environment present great challenges to the task
planning of service robots. The nature of the home environment is highly unstructured, with a …
planning of service robots. The nature of the home environment is highly unstructured, with a …
Energy disaggregation of appliances consumptions using ham approach
H Liu, Q Zou, Z Zhang - IEEE Access, 2019 - ieeexplore.ieee.org
Non-intrusive load monitoring (NILM) makes it possible for users to track the energy
consumption of a household. In this paper, we present a new hybrid energy disaggregation …
consumption of a household. In this paper, we present a new hybrid energy disaggregation …
Individualized AI tutor based on developmental learning networks
WH Kim, JH Kim - IEEE Access, 2020 - ieeexplore.ieee.org
In recent years, in the field of education technology, artificial intelligence tutors have come to
be expected to provide individualized educational services to help learners achieve high …
be expected to provide individualized educational services to help learners achieve high …
Self-organizing neural networks for universal learning and multimodal memory encoding
Learning and memory are two intertwined cognitive functions of the human brain. This paper
shows how a family of biologically-inspired self-organizing neural networks, known as fusion …
shows how a family of biologically-inspired self-organizing neural networks, known as fusion …
iCVI-ARTMAP: using incremental cluster validity indices and adaptive resonance theory reset mechanism to accelerate validation and achieve multiprototype …
LEB da Silva, N Rayapati… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article presents an adaptive resonance theory predictive map** (ARTMAP) model,
which uses incremental cluster validity indices (iCVIs) to perform unsupervised learning …
which uses incremental cluster validity indices (iCVIs) to perform unsupervised learning …
An embedded deep fuzzy association model for learning and explanation
This paper explores the complementary benefits of embedding a deep learning model as a
fully data-driven fuzzy implication operator of a five-layer neuro-fuzzy system for learning …
fully data-driven fuzzy implication operator of a five-layer neuro-fuzzy system for learning …
Deep episodic memory: Encoding, recalling, and predicting episodic experiences for robot action execution
We present a novel deep neural network architecture for representing robot experiences in
an episodic-like memory that facilitates encoding, recalling, and predicting action …
an episodic-like memory that facilitates encoding, recalling, and predicting action …
Incremental class learning for hierarchical classification
Objects can be described in hierarchical semantics, and people also perceive them this way.
It leads to the need for hierarchical classification in machine learning. On the other hand …
It leads to the need for hierarchical classification in machine learning. On the other hand …
A stabilized feedback episodic memory (SF-EM) and home service provision framework for robot and IoT collaboration
The automated home referred to as Smart Home is expected to offer fully customized
services to its residents, reducing the amount of home labor, thus improving human beings' …
services to its residents, reducing the amount of home labor, thus improving human beings' …