Adaptive neuro-fuzzy inference system: Overview, strengths, limitations, and solutions
MNM Salleh, N Talpur, K Hussain - Data Mining and Big Data: Second …, 2017 - Springer
Adaptive neuro-fuzzy inference system (ANFIS) is efficient estimation model not only among
neuro-fuzzy systems but also various other machine learning techniques. Despite …
neuro-fuzzy systems but also various other machine learning techniques. Despite …
Novel hybrid intelligence models for flood-susceptibility prediction: Meta optimization of the GMDH and SVR models with the genetic algorithm and harmony search
Floods are among the deadliest natural hazards for humans and the environment.
Identifying the most flood-susceptible areas is a fundamental step in the development of …
Identifying the most flood-susceptible areas is a fundamental step in the development of …
Determination of bubble point pressure and oil formation volume factor: Extra trees compared with LSSVM-CSA hybrid and ANFIS models
Successful field development relies on effective reservoir management, which, in turn, is, to
a great extent, influenced by the knowledge of reservoir fluid properties and phase …
a great extent, influenced by the knowledge of reservoir fluid properties and phase …
Evolutionary optimization of biogas production from food, fruit, and vegetable (FFV) waste
OO Olatunji, PA Adedeji, N Madushele… - Biomass Conversion …, 2024 - Springer
The success of anaerobic digestion (AD) process for biogas production is contingent upon
complex mix of operating factors, process conditions, and feedstock types, which could be …
complex mix of operating factors, process conditions, and feedstock types, which could be …
A hierarchical procedure for the synthesis of ANFIS networks
M Panella - Advances in Fuzzy Systems, 2012 - Wiley Online Library
Adaptive neurofuzzy inference systems (ANFIS) represent an efficient technique for the
solution of function approximation problems. When numerical samples are available in this …
solution of function approximation problems. When numerical samples are available in this …
Comparing methods for creating a national random sample of twitter users
Twitter data has been widely used by researchers across various social and computer
science disciplines. A common aim when working with Twitter data is the construction of a …
science disciplines. A common aim when working with Twitter data is the construction of a …
Distributed learning of random weights fuzzy neural networks
In this paper, we propose a scalable, decentralized learning algorithm for Random Weights
Fuzzy Neural Networks, when training data is distributed through a network of …
Fuzzy Neural Networks, when training data is distributed through a network of …
A novel FMEA model using hybrid ANFIS–Taguchi method
Failure mode and effects analysis (FMEA) is a useful method to analyze and then prioritize
failure, but it has many drawbacks. First of them is risk factors, severity, occurrence and …
failure, but it has many drawbacks. First of them is risk factors, severity, occurrence and …
PCA Esaslı Hibrit ANFIS-Taguchi Yöntemi ile Kan Bankası için Talep Tahmini
Kan; hastalıklar, ameliyatlar veya yaralanmalar nedeniyle her gün binlerce insan tarafından
ihtiyaç duyulan hayati bir üründür. Bu nedenle hastanelerin kan ihtiyacını karşılayan kan …
ihtiyaç duyulan hayati bir üründür. Bu nedenle hastanelerin kan ihtiyacını karşılayan kan …
PCA Esaslı Hibrit ANFIS-Taguchi Yöntemi ile Kan Bankası için Talep Tahmini.
S Hatice GÖKLER, S BORAN - International Journal of …, 2020 - search.ebscohost.com
Kan; hastalıklar, ameliyatlar veya yaralanmalar nedeniyle her gün binlerce insan tarafından
ihtiyaç duyulan hayati bir üründür. Bu nedenle hastanelerin kan ihtiyacını karşılayan kan …
ihtiyaç duyulan hayati bir üründür. Bu nedenle hastanelerin kan ihtiyacını karşılayan kan …