Predictive analytics for crude oil price using RNN-LSTM neural network

N Aziz, MHA Abdullah, AN Zaidi - … International conference on …, 2020 - ieeexplore.ieee.org
Prediction of future crude oil price is considered a significant challenge due to the extremely
complex, chaotic, and dynamic nature of the market and stakeholder's perception. The crude …

Stability of classification performance on an adaptive neuro fuzzy inference system for disease complication prediction

S Kusumadewi, L Rosita… - … International Journal of …, 2023 - search.proquest.com
It is crucial to detect disease complications caused by metabolic syndromes early. High
cholesterol, high glucose, and high blood pressure are indicators of metabolic syndrome …

ANFIS learning using expectation maximization based Gaussian mixture model and multilayer perceptron learning

S Jabeen, M Baig, MM Awais - Applied Soft Computing, 2023 - Elsevier
Abstract The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid learning algorithm
that combines the learning ability of neural networks with fuzzy inference systems. While …

The application of a hybrid model using mathematical optimization and intelligent algorithms for improving the talc pellet manufacturing process

D Buntam, W Permpoonsinsup, P Surin - Symmetry, 2020 - mdpi.com
Moisture is one of the most important factors impacting the talc pellet process. In this study, a
hybrid model (HM) based on the combination of intelligent algorithms, self-organizing map …

[PDF][PDF] A Novel Metaheuristic Approach to Optimization of Neuro-Fuzzy System for Students' Performance Prediction

K Hussain, N Talpur, MU Aftab - Journal of Soft Computing …, 2020 - publisher.uthm.edu.my
Data mining is being increasingly leveraged in educational settings for achieving various
different outcomes including students' learning patterns, course and teaching outcome …