Achieving sustainability in heat drying processing: Leveraging artificial intelligence to maintain food quality and minimize carbon footprint
The food industry is a significant contributor to carbon emissions, impacting carbon footprint
(CF), specifically during the heat drying process. Conventional heat drying processes need …
(CF), specifically during the heat drying process. Conventional heat drying processes need …
Neuro-fuzzy and networks-based data driven model for multi-charging scenarios of plug-in-electric vehicles
In recent times, significant progress has been achieved in the domain of intelligent and eco-
friendly transportation. Electric mobility emerges as a viable and effective solution, offering …
friendly transportation. Electric mobility emerges as a viable and effective solution, offering …
A smoothing group lasso based interval type-2 fuzzy neural network for simultaneous feature selection and system identification
Inspired by the life philosophy, an ingenious gate (membership) function, which can mimic
the open and close of the gate in the real world, is proposed to realize feature selection (FS) …
the open and close of the gate in the real world, is proposed to realize feature selection (FS) …
Hyperspectral image classification based on dense pyramidal convolution and multi-feature fusion
In recent years, hyperspectral image classification techniques have attracted a lot of
attention from many scholars because they can be used to model the development of …
attention from many scholars because they can be used to model the development of …
Dg-aletsk: a high-dimensional fuzzy approach with simultaneous feature selection and rule extraction
Fuzzy or neuro-fuzzy systems have been successfully employed in many areas, but their
limitation in solving high-dimensional problems remains a challenging task. On the other …
limitation in solving high-dimensional problems remains a challenging task. On the other …
Neuro-fuzzy random vector functional link neural network for classification and regression problems
The random vector functional link (RVFL) neural network has shown the potential to
overcome traditional artificial neural networks' limitations, such as substantial time …
overcome traditional artificial neural networks' limitations, such as substantial time …
Security-aware resource allocation scheme based on DRL in cloud-edge-terminal cooperative vehicular network
Virtual network embedding (VNE) refers to the process of map** virtual networks onto
physical networks, which can improve the utilization and flexibility of network resources …
physical networks, which can improve the utilization and flexibility of network resources …
Convergence analysis of sparse TSK fuzzy systems based on spectral Dai-Yuan conjugate gradient and application to high-dimensional feature selection
D Ji, Q Fan, Q Dong, Y Liu - Neural Networks, 2024 - Elsevier
Dealing with high-dimensional problems has always been a key and challenging issue in
the field of fuzzy systems. Traditional Takagi–Sugeno–Kang (TSK) fuzzy systems face the …
the field of fuzzy systems. Traditional Takagi–Sugeno–Kang (TSK) fuzzy systems face the …
Pseudo inverse versus iterated projection: Novel learning approach and its application on broad learning system
Broad learning system (BLS) has attracted widespread attention owing to its concise
structure and efficient incremental learning based on ridge regression approximation of …
structure and efficient incremental learning based on ridge regression approximation of …
Research on Large Scene Adaptive Feature Extraction Based on Deep Learning
The proliferation of intelligent monitoring devices has led to the widespread adoption of
background extraction technology across a multitude of domains, including intelligent …
background extraction technology across a multitude of domains, including intelligent …