Recent advances in neuro-fuzzy system: A survey
Neuro-fuzzy systems have attracted the growing interest of researchers in various scientific
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
and engineering areas due to its effective learning and reasoning capabilities. The neuro …
[HTML][HTML] Neuro-fuzzy systems in construction engineering and management research
Neuro-fuzzy systems (NFS) can explicitly represent and model the input–output
relationships of complex problems and non-linear systems, like those inherent in real-world …
relationships of complex problems and non-linear systems, like those inherent in real-world …
Actuator fault detection and isolation on multi-rotor UAV using extreme learning neuro-fuzzy systems
Undetected partial actuator faults on multi-rotor UAVs can lead to system failures and
uncontrolled crashes, necessitating the development of accurate and efficient fault detection …
uncontrolled crashes, necessitating the development of accurate and efficient fault detection …
A comparative evaluation of supervised machine learning algorithms for township level landslide susceptibility zonation in parts of Indian Himalayas
Landslide susceptibility zonation (LSZ) has generally been regarded as the appropriate
stride to begin scientific studies in mountainous terrains to alleviate the socio-economic …
stride to begin scientific studies in mountainous terrains to alleviate the socio-economic …
Prediction of landslide displacement with controlling factors using extreme learning adaptive neuro-fuzzy inference system (ELANFIS)
Landslide is a major geo-environmental hazard which imparts serious threat to lives and
properties. The slope failures are due to adverse inherent geological conditions triggered by …
properties. The slope failures are due to adverse inherent geological conditions triggered by …
An adaptive neurofuzzy inference system for the assessment of change order management performance in construction
Change order management is a major challenge in the construction business due to the
associated disputes, claims, productivity losses, delays, and cost implications. As a result …
associated disputes, claims, productivity losses, delays, and cost implications. As a result …
Knowledge workers mental workload prediction using optimised ELANFIS
The competitive society in the new era calls for more research to improve the well-being of
workers as well as to improve their productivity. Knowledge workers face a high mental …
workers as well as to improve their productivity. Knowledge workers face a high mental …
Research on air pollutant concentration prediction method based on self-adaptive neuro-fuzzy weighted extreme learning machine
In order to improve the prediction accuracy and real-time of the air pollutant concentration
prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning …
prediction, this paper proposes self-adaptive neuro-fuzzy weighted extreme learning …
K-Means clustering based Extreme Learning ANFIS with improved interpretability for regression problems
In this paper, a novel network called K-Means clustering based Extreme Learning ANFIS
(KMELANFIS) with improved interpretability for regression problems is presented. Grid input …
(KMELANFIS) with improved interpretability for regression problems is presented. Grid input …
Adaptive Nonstationary Fuzzy Neural Network
Fuzzy neural network (FNN) plays an important role as an inference system in practical
applications. To enhance its ability of handling uncertainty without invoking high …
applications. To enhance its ability of handling uncertainty without invoking high …